Ingineria Automobilului Society of

Transcription

Ingineria
Automobilului
Romanian
Automobile
Register
Society of
Automotive
Engineers
of Romania
distr ibu ted with au totest mag a zine
Vol. 6, no. 3, September 2012
research and development institute
Transilvania University of Braşov
Editorial
Prof. Dr.-Ing. habil. Prof. E. h. Dr. h. c. Cornel Stan
Interview with George-Adrian Dincă
Director of Romanian Auto Register
Romanian Motorisation II
Prof. Guenther Hohl - Past President EAEC
The Gas Exchange
in a Variable Valve Actuation Engine
Conf. Dr. Ing. Adrian Clenci
SIAR is affiliated to
Vehicle Dynamics.
Systemic Approach
Prof. Dr. Ing. Ion Copae
Vehicle Suspension Oscillation
in case of Bump Traveling
Prof. Dr. ing. Victor Oţăt
Student Contest
„Kart Low Cost 2012”
University of Piteşti
international
federation of
automotive
enGineering
societies
european
automobile
engineers
cooperation
VIEWEG HANDBUCH KRAFTFAHRZEUGTECHNIK
Vieweg Manual Automotive Engineering 6th Edition
This updated manual was completed with 1214 graphical representations and 122 indexes. More than 100 authors contributed to the creation of this manual. The intention of this manual is to give automotive
engineers a detailed and quick overview of the basic knowledge of engineering. The authors kept in mind the progress in the conventional
automotive industry, but they especially focused on the developments
in hybrid vehicles and electric vehicles which have an influence on all
subdivisions of the automotive industry. This also includes the new
active and passive security systems in vehicles. This manual consists of
regulations and form which include aerodynamics, the latest propulsion systems, primary charge, motorfuels and materials, traction, electronics, internal power supply, acoustics, air condition, output of the
lightning, drivers assistance systems, simulation process, experimental runs, autobodies, racing cars etc. The book addresses to engineers,
to everybody who is intersted in automotives, authorities, insurances,
approval and licensing authorities , professors, associate professors,
teachers and students as well as specialized journalists. Responsible
editors: Prof. Dr.- Ing. Dr.- Ing. E.h. Hans –Hermann Braes and Ulrich
Seifert.
VERBRENNUNGSMOTOREN
Engines with internal combustion
The paper draws a bow from the basic principles of thermodynamics of
engines with internal combustion up to the more complex model of generating of fuel mixtures, ignition, combustion and the creation of polluted substances, keeping in mind the additional sets of Otto and Diesel
engines. The main focus of the book is on simulations and the way they
are created as well as the circulation of gases, thermodynamics and the
mixing of motor fuels. The author included this to show how inevitable
these factors are for the new generation of engines with an internal combustion. The newest edition has the following topics:
The possibilities and limits of simulations, the potentials of Otto and
Diesel engines, hybrid engines, gas engines, heavy crude oil engines, the
possibilities of measuring the exhaust gases and polluting particles and
strategies in optimizing processes. The paper addresses to construction
engineers in the automotive sector at universities with a faculty which
has a focus on calculating and developing engines with internal combustion, conceptual and developomental engineering in the area of the
automotive industry, cooperators from the faculty of economy who are
involved in the research and in the development of engines. Responsible
editors Univ. -Prof. em Dr.- Ing. Habil. Günter P. Merkel, Institut für Technische Verbrennung Universität Hannover,
Prof. Dr.- Ing. Habil. Christian Schwarz Abteilungsleiter bei der BMW AG. München, Dr. Ing.- Rüdiger Teichmann,
Manager bei der AVL List GmbH.
Ingineria Automobilului
The future of the Romanian
automobile engineer
T
he worldwide production and development of automobiles crest
in the last year at a level, which
was never reached until now and similarly
increased the demand for engineers and
specialists in this domain, especially in
Germany. We hope that the recent singular
perturbations of this stream do not signalize the zenith of theautomobile industry.
The most of the international automotive events of this year confirm the tendency of the polarization of automobiles in distinct
classes, corresponding to their utilization:
- SUV and luxury big cars with high power with hybrid
propulsion – thermal and electric
- medium size cars with medium power with compact
piston engines, super- / turbochargeable with 1-2 devices,
with electrically controlled functions in base on the electric
energy from a fuel cell working as APU (Auxiliary Power
Unit), with the same fuel as for the piston engine itself
- compact cars for urban use, with electric motor and battery
- small/medium size cars for urban and regional utilization, with electric propulsion, the energy being provided
by a generator which is driven by a thermal machine - wankel engine, gas turbine, stirling engine, two stroke engine
– or by a fuel cell
- low price cars for multiple use – such as the Dacia fam-
ily – with spark ignition engine, without direct injection,
turbocharging or variable valve control, but respecting the
legal limits of pollution and safety
At the present, the own contribution of an OEM to the development and production of a vehicle is of 18-20%, the most important
part being the assembly, the function modules, the subsystems and
parts coming from suppliers – Bosch, ZF, INA Schaeffler, Denso,
Mahle, Johnson Controls.
But the process of an automobile creation has a higher complexity
than given by the production of modules: their development and
design being ensured by well specialized subcontractors – IAV,
Höfer, Bertram, Rückert; the research is the part of institutes at or
in universities – FEV, IAV, FKFS or my institute, FTZ.
As a last component of the system complexity should be mentioned, that the most part of the above companies are acting
worldwide.
In this profitable, eventful, complex and global market, the
Romanian automobile engineers, with a solid and competitive
scientific and technical formation in respectable Romanian universities will find their appropriate places – I have a lot of good
examples in this sense.
A good market need a good bourse, we will do all the possible efforts in order to create such a bourse on the platform offered by
our journal.
Prof. Dr.-Ing. habil. Prof. E. h. Dr. h.c. Cornel Stan
SAE Fellow
Summary „Ingineria Automobilului“ No. 23 (vol. 6, no. 3)
3 – The future of the Romanian automobile engineer
5 – Interviu cu dl. George-Adrian Dincă,
Director General al RAR-RA
6 – The Romanian Automotive History (II)
8 – Experimental Study Concerning the Gas Exchange
in a Variable Valve Actuation Engine
12 –Experimental Study of Vehicle Dynamic
Based on a Systemic Approach
16 –The Study of a Vehicle Suspension Oscillations
in Case of Bump Travelling
18 –Uncertainty Assessment in Crash Analysis
by Coupling Transient Dynamic Finite Element
Analysis with the Fuzzy Concept – Part 1: Theory
21 –Utilization of Traffic Simulation Programs in the Creation
of Road Traffic Strategies in Order to Reduce Pollution
25 –University Research
26 –Challenge KART LOW COST
3
romanian
automobile
register
General Manager
George-Adrian DINCĂ
Technical Manager
Flavius CÂMPEANU
SOCIETY OF AUTOMOTIVE ENGINEERS OF ROMANIA
President: Conf. Dr. Ing. Adrian Clenci, Universitatea din Piteşti
Honorary President: Prof. Dr. Ing. Eugen Negruş, Universitatea Politehnica din Bucureşti
Vice-president: Prof. Cristian Andreescu, Universitatea Politehnica din Bucureşti
Vice-president: Prof. Anghel Chiru, Universitatea Transilvania din Braşov
Vice-president: Prof. Ioan Tabacu, Universitatea din Piteşti
General Secretary: Dr. Cornel Armand Vladu
SCIENTIFIC AND ADVISORY EDITORIAL BOARD
Prof. Dennis Assanis
University of Michigan,
Michigan,
United States of America
Auto Test
Chief Editor
Lorena BUHNICI
Editors
Radu Buhăniţă
Emilia PETRE
Prof. Rodica A. Bărănescu
University of IIlinois at Chicago
College of Engineering, United States of America
Prof. Nicolae Burnete
Technical University of Cluj-Napoca, Romania
Prof . Giovanni Cipolla
Politecnico di Torino, Italy
Contact:
Calea Griviţei 391 A,
sector 1, cod poştal 010719,
Bucureşti, România
Tel/Fax: 021/202.70.17
E-mail: [email protected]
Dr. Felice E. Corcione
Engines Institute,
Naples, Italy
Prof. Georges Descombes
Conservatoire National
des Arts et Metiers de Paris,
France
SIAR
Prof. Cedomir Duboka
University of Belgrade
Serbia
Contact
Faculty of Transport
University POLITEHNICA
of Bucharest
Splaiul Independenţei 313
Room JC 005
Cod poştal 060032, sector 6
Bucureşti, România
Tel/Fax: 021/316.96.08
E-mail: [email protected]
Prof. Pedro Esteban
Institute for Applied
Automotive Research
Tarragona, Spain
printing
Full or partial copying
of text and pictures
can be done only with
Auto Test Magazine approval,
of the Romanian Automobile
Register and of SIAR
4
Prof. Peter Kuchar
University for Applied Sciences,
Konstanz, Germany
Prof. Mircea Oprean
University Politehnica of Bucharest,
Romania
Prof. Nicolae V. Orlandea
Retired Professor,
University of Michigan
Ann Arbor, M.I., USA
Prof. Victor Oţăt
Universitatea din Craiova, România
Prof. Pierre Podevin
Conservatoire National
des Arts et Metiers de Paris, France
Prof. Andreas Seeliger
Institute of Mining and Metallurgical
Machine, Engineering,
Aachen, Germany
Prof. Ulrich Spicher
Kalrsuhe University, Karlsruhe,
Germany
Prof. Radu Gaiginschi
Technical University
„Gh. Asachi”of Iaşi, Romania
Prof. Cornel Stan
West Saxon University of
Zwickau, Germany
Prof. Berthold Grünwald
Technical University
of Darmstadt, Germany
Prof. Dinu Taraza
Wayne State University,
United States of America
editorial board
ART GROUP INT SRL
Str. Vulturilor 12-14, sector 3
Bucureşti
Eng. Eduard Golovatai-Schmidt
Schaeffler AG & Co. KG
Herzogenaurach, Germany
Editor in chief: Prof. Dr.-Ing. habil. Prof. E. h. Dr. h.c. Cornel Stan
Executive editor in chief: Prof. Mircea OPREAN Universitatea Politehnica Bucureşti
Deputy Editors
Prof. Gheorghe-Alexandru RADU Universitatea Transilvania Braşov
Prof. Dr. Ing. Ion COPAE Academia Tehnică Militară, Bucureşti
Conf. Ştefan TABACU Universitatea din Piteşti
Editors
Conf. Adrian SACHELARIE Universitatea Gh. Asachi Iaşi
Conf. Dr. Ing. Ilie Dumitru Universitatea din Craiova
Lector Cristian COLDEA Universitatea Cluj-Napoca
Lector Dr. Ing. Marius BĂŢĂUŞ Universitatea Politehnica Bucureşti
Dr. Ing. Gheorghe DRAGOMIR Universitatea din Oradea
Editorial secretary: Dr. ing. Cornel Armand VLADU Secretar general SIAR
New series of the Revista Inginerilor de Automobile din România (RIA), 1992-2000
Cod ISSN 1842 - 4074
Interview with George-Adrian Dincă
Director of Romanian Auto Register
Automotive
Engineering:
Dear Mr. Director General,
how are you appreciating the
recent and future evolutions
of the European regulations
in the field of road vehicles,
particularly regarding the road
vehicles emissions reducing
strategies and promotion
of the new technologies for
electric and hybrid vehicles,
and how those regulations will
be reflected in our national
legislation?
In order to assure a sustainable
long and medium term
development of the European
automotive industry, a new
global strategy in this field is now
under discussion in the CARS
21 Group comprising experts
of the European Commission,
Member States, automotive
industry and other bodies in
connection with this field.
On the other side, in accordance
with the former strategy issued
by the CARS 21 Group, the whole EU legislation in the field of road
vehicles is now in an accelerated simplification and improvement
process (so called “better regulation”).
Regarding the pollutant emissions domain, based on the existing
strategy, the efforts of the Commission’s and Member States’
experts participating to the working parties (including Romania
through RAR’s experts), led to the adoption of new regulations,
applicable in Romania as well, aiming the continuous reduction
of the emissions generated by the vehicles (see the Euro 6 Norms
for light duty vehicles and Euro VI for heavy duty vehicles), CO2
emissions reduction and the creation of a legislative framework
regarding the approval and the placing on the market of the
vehicles using the non-conventional fuel (including hydrogen)
and the hybrid or electric vehicles, as well.
What possibilities are you seeing for a better cooperation between
RAR’s technical bodies and research centers from the universities
at the central, local and even individual level, eventually by
promotion of the actual research subjects that could be solved even
by master or doctor thesis?
I consider very useful the
extension of the collaboration
with the technical academic
environment, having in view the
great actuality of the emissions
problems of the road vehicles
being the object of the research
and studies performed also by
our institution in the last 20
years.
We appreciate that the approach
of theoretical and experimental
studies regarding the impact of
the road traffic on ambient and
human factors in the field of
atmospheric pollution, noise
pollution and traffic safety
(accident, passive and active
safety), could be materialized
both, by a common solving
of a research subjects within
national and international
partnership science programs
and by developing of some
specific academic thesis at
different levels.
How do you appreciate the skills of the university graduated people
being hired in RAR and what could be done in order to assure an
appropriate training according to the actual requirements in
the field of automotive engineering and specific for the necessary
requirements in RAR’s activity? A summer training period in RAR
would it be useful for students?
In the year 2011 eight bachelors of the University of Transport has
been hired in RAR, one of them had finished the courses in 2011.
It is generally found a good basic preparation, especially theoretical
of the university graduated people and a big assimilation capacity
of the skills belonging to RAR’s specific activity.
We appreciate that a summer training performed by students of
automotive faculties could be useful for those aiming to work
in RAR or in activities managed by RAR, but practically, the
possibilities are limited. In connection with this aspect, with a
view of students’ professional orientation and based on university
requests, some presentation of the RAR’ activities could be done
by our specialists.
5
The Romanian Automotive History (II)
The first motor races and the most famous drivers
Brigadier ret. Prof. Günter Hohl
Past FISITA Vice President Europe
Past EAEC President
ÖVK Vice President
The first motor car race (Bucharest-Giurgiu) took
place in 1904, Romania being among the first six
nations in the world to have organized speed motor races. George Valentin Bibescu, with an average speed of 66 km/h, won the contest.
The first Romanian to be awarded in an international speed competition was Ion Maican. In
1906, he come the third from 90 competitors in
the Chateau-Thierry race (France).
In 1907, took place the first auto-rally in Romania.
The first non-stop driving race Bucharest-ParisBucharest took place in 1926, and was managed by Romanian team Henri Manu and N.
Constantinescu.
The Monte Carlo rally the most famous rally
in the world, had at the start of the 4th edition
(1927) the Romanians Alexandru Racovita,
who left Bucharest with a Steyr, and George
Ghica, who left Brussels with a Buick. Racovita
ranked five, and Ghica ranked 30 at general event
and first at comfort.
Petre G. Cristea (middle), Gogu
Constantinescu and Ionel Zamfirescu at the
Monte Carlo Rally (1936)
6
In 1936, Petre Cristea together with Gogu
Constantinescu and Ionel Zamfirescu won the
Monte Carlo Rally on a Ford modified by the
three. This was the first victory of Ford in this famous rally.
Petre G. Cristea (1909 –1995) is still considered
by many to be Romania’s best racing driver.
Jean Calcianu drove in every national race, winning most of them, with just one equal rival: Petre
Cristea. In 1914, he decided to go to France, where he became an employee of Renault Company.
In 1934, he organized Brasov Grand Prix the first
closed circuit race in the country.
Calcianu set one more record on Feleac, where
he defeated the hill climb expert, Hans Stuck.
Calcianu’s most beautiful victory came in 1939
in the Belgrade Grand Prix, where he defeated
with an Alfa Romeo all the elite of German and
French drivers.
Alexe de Vassal (1910-2006) the descendant of
a Count of de Vassal was the last “prince of motoring” in Romania. His father, a well-known public person and chairman of General Motors in
Romania at that time, succeeded in getting him
an approval for the test for driving license just at
the age of only 15 years.
Alexe Vassal was part of the “golden generation
of the Romanian motor racing”, primarily between 1930 and 1939. The last remarkable race he
competed in together with Petre Cristea was the
Monte Carlo Rally of 1938.
After the war, he succeeded in bringing back to
public attention the traditions of the Romanian
motor racing. He actively supported the creation,
in 1948, of the Romanian Federation of Motor
and Motorcycle Racing (FRAM). In 1960, he
was among the founders of the Romanian CarDrivers Association and in 1967 he contributed
to the revival of the Automobil Clubul Roman
which gradually reunited the whole motor-car
movement in Romania.
Marin Dumitrescu was the link between the
golden generation illustrated by Calcianu and
Cristea, and the classics generation, which came
after 1967. He made his debut in 1948, in the
speed circuit races, with modified Jeeps. Enjoying
favorable conditions, Marin Dumitrescu became,
between 1949 and 1958, the collector of most of
the absolute champion titles at circuit speed and
hill climb. He was a competitor in rallies, along
with Petre Vezeanu. He won his last champion
title on a Dacia 1300, in 1976.
Jean Calcianu
Marin Dumitrescu
Aurel Puiu
Eugen Ionescu-Cristea
Eugen Ionescu-Cristea (1938-2011) was one
of the most gifted modern Romanian car-drivers.
He succeeded in getting 36 national champion
titles, in all the three specialties: hill climb, circuit
and rally speed. As fellow team members, he had
Petre Vezeanu, Dan Amarica, Petre Parcalaboiu
and Tudor Bucataru. Among the international awards: two victories in the Balkan Rally
(1968 and 1972), second place in the Gunaydin,
Turkey, Rally (1978) and two victories in the
Iron Gates Rally (1972 and 1973 together with
Petre Vezeanu).
Aurel Puiu was an architect and he was over
35 years old when he started in a motor race in
Brasov for the first time. After a short while, he
had his first great success when he won in the
Romania Rally and was taken on in the ACR
team. In a Renault 8 Gordini, he came fourth in
the Danube Rally. In the same year, he won the
first place at class event and the third place at
general in the Balkan Rally in Yugoslavia. After
an unsuccessful season, he succeeded in getting
three national champion titles in rallies: 1969,
1970 and 1971.
Stefan Iancovici became acquainted for the first
time with motorcycle racing at the age of 19 years.
He won three champion titles at motocross, three
titles at speedway, two titles at regularity events
and set two records on the circuits of Feleac and
Medias. He won two golden medals at the Six
Days Races in Austria and Czechoslovakia.
He made his debut in car racing in 1966 when
together with C. Radovici he won the first place
in the 1150 ccm event on a Renault 10 Major. In
1968, having Marin Dumitrescu as a teammate,
he got the first place at class and the second place
at “general” in the Trans-Balkan Rally. His peak
year was in 1977, when he became the first motor
racing driver of Romania, winning five champion
titles (two at class and three absolute).
Petre Vezeanu made his debut in motor racing
at the Rally of Bucharest in 1966, being an exceptional co-driver. In 1967, he made his entrance
in international competitions, taking part in the
Trans-Balkan Rally and in 1968 he won the Rally
of Romania together with Marin Dumitrescu on
a Fiat 1500. He died in France, in a traffic accident
while on his way to the Rally of Portugal.
Dorin Motoc started as a cyclist. In 1973 he
became a national champion at hill climb speed
with a Fiat 128. The same year, he took part in the
first international race, the Iron Gates Rally and
he came second. In 1974, he won two national
champion titles at hill climb and ranked second
in the Danube Rally.
Ludovic Balint (1948-1994) made his debut in
motor racing in 1975, when he took part as a navigator in the Youth Rally of Brasov. In the same
year, he made his entrance in the National Rally
Championship and won the title of vice-champion in the Dacia 1300 event. In 1976, he won his
first title of national champion, at circuit speed.
In 1977 and 1978, he won at the same event four
more national titles of champion at speed (hill
climb and circuit). He entered the Dacia team
in 1980. Having Constantin Zarnescu as co-driver he won six national titles of absolute rally
champion in 1981, 1982, 1986, 1987, 1989 and
1991. He got his seventh and last title in 1993.
During that time he also won four titles of national champion with the Dacia team. He is the only
Romanian driver who succeeded in the Danube
Rally (1987). Ludovic Balint was named for five
times the best Romanian motor racing driver of
the year in 1984, 1987, 1989, 1991 and 1993. He
died on February 1, 1994, a day before his 46th
birthday in a traffic accident.
Nicu Grigoras (1948-1999) was the best speed
drivers in Romania. He made his debut in racing
in 1976 and won his first title of champion in 1977
in hill climb speed. His peak season was in 1980
when he won five individual titles and two with
the team. In 1986, besides the two titles on circuit and hill climb, Nicu Grigoras won the international race of Resita, being the first Romanian
driver to succeed in such a performance in the
Friendship Cup. He was named for five times the
best Romanian motor racing driver of the year.
Constantin Aur (n. 1963) made his debut in
1986 at the Rally of Brasov, on a private Dacia.
In 1963, he graduated from the French school of
motor driving „Jean Michel Fabre” from CergiPontoise-Paris.
He won eight Romanian Rally Championships
(1995, 1997, 1998, 1999, 2000, 2001, 2002 and
2006) and two hill climb national championship titles. He was the first Romanian rally driver participating in a full season of World Rally
Championship in 2003. He opened a school for
defensive driving and racing.
Summary:
Based on a long and also convoluted history,
Romania can now look optimistically to a successful revival of the automotive activities in production, research and development as well as in
education. The founding of new automobile production companies and research institutions are
positive signals for the future.
7
Experimental Study Concerning the Gas Exchange in a
Variable Valve Actuation Engine
Adrian Clenci
University of Pitesti, Romania, str.
Tg. din Vale nr. 1, Pitesti – 110040,
Romania
LGPE2S-EA21, Le Cnam, 292 rue
St. Martin, 75003, Paris, France
Table 1. Main parameters of the VVA prototype
NB. Exhaust and intake valves law parameters
are given for a 0.2 mm reference lift
Victor Iorga-Simăn
University of Pitesti, Ro
mania, str. Tg. din Vale nr.
1, Pitesti – 110040, Romania
Alain Delacroix
Introduction
As an energetic source, from the power density,
stored energy and autonomy standpoint, the internal combustion engine still remains an attractive solution for ensuring the mobility. Engines
have improved dramatically over the past two
decades and they will continue to improve [1].
The increasing focus on the environmental
impacts of hydrocarbon fuel based power generation has led to increased research efforts to
reduce CO2 emissions, which mean improving
the engine thermal efficiency. The current scientific developments described in [2] suggest that
there could be 6–15% improvements in the efficiency in the coming decade, although the filters required to meet the more and more severe
emissions legislation reduce these gains.
During most of its life, a passenger car engine is
run under low loads and speeds. It is known that
load reduction in spark-ignition engines is traditionally realized by introducing additional losses
during the intake stroke by means of a throttle
plate. In these operating points, the engine efficiency decreases from the peak values (already
not very high) to values dramatically lower.
The introduction of a variable valve actuation
(VVA) provides significant improvement especially at low part loads and speeds operation,
[3–8]. For instance, the ability to control valve
8
lift certainly offers the possibility to
9
control intake air mass (see throttle8
less operation – [4]) but also has the
7
added benefit that it improves fuel-air
6
mixing process and controls air mo5
tion. This is particularly important
at idle and low part loads when low
4
lifts are to be used to overcome the
3
inherent reduction in flow velocity at
2
the valve gap, thus for improving the
1
engine’s fuel economy [3,4,7,9].
0
Given this context, an original port
0
60
fuel injected (PFI) spark ignition
(SI) engine featuring VVA (see appendix 2) was experimentally investigated when operating at idle
with low intake valve lift [10]. Briefly, these
experimental investigations showed an important improvement of engine operation when using minimum intake valve lift. Namely, the fuel
consumption and coefficient of variance applied
to IMEP, used to evaluate the cyclic dispersion,
decreased by 18.2%, respectively 41.4%, while
using a 30 CAD spark advance. Pumping work
wasn’t discussed due to the experimentation
methodology, which imposed different throttle
openings to attain the idle speed target in both
cases approached, minimum (Hmin) and maximum (Hmax) intake valve laws. Therefore, as
the effect of solely the intake valve law upon the
pumping work couldn’t be isolated, this aspect
even though quantified was not at issue.
This paper aims to bring more insights about
gas exchange by using the engine motored at the
corresponding idle speed. By doing this way, a
TDC
BDC
Valves Lift [mm]
Pierre Podevin
Exhaust
120
180
240
300
BDC
Intake
VVA
360
420
a [CAD]
480
540
600
660
720
Fig.1.1.Valve
Valve
laws
Fig.
laws
complete comparative analysis, Hmax vs. Hmin,
was possible.
ExperimentaTION
The study was conducted on the single-cylinder
resulted from deactivation of three others of the
VVA engine prototype mentioned above, whose
main parameters are presented in table 1.
A graphical representation of the VVA prototype engine’s valve laws is given figure 1.
The experimental apparatus for this study consists of the prototype engine, instrumented for
accurately acquiring the instantaneous in-cylinder, intake and exhaust pressure evolutions
(figure 2). Besides these measurements, some
others were performed thanks to having access
to the engine management control system, such
as: throttle opening, intake manifold absolute
pressure (MAP), engine and air temperatures.
Out of these, MAP information served only to
have an averaged value needed for rapid visual
Fig. 2. Schematic diagram of the experimental set-up
monitoring of changes caused by different factors. During tests, air and engine temperatures
were set to 200C respectively 400C. As for the
inside engine cell atmospheric pressure, it was
maintained at 1 bar.
a)
b)
Fig. 3. Indicated diagrams
a. pressure vs. crank angle / b. low loops
Due to inherent characteristics of in-cylinder
pressure piezoelectric transducer, referencing
its output to absolute pressure is needed, i.e.
the measured pressure must be referenced to
a known absolute pressure at some point in an
engine cycle.
This is what usually is known as pegging.
Reference [11] presents the pegging methods
with their influence on the indicated calculated
parameters. For our study, the cylinder pressure
data was pegged by assuming the in-cylinder
pressure at 10 CAD after the intake BDC (±
20) was equal to the mean intake manifold absolute pressure. Apparently, this method is the
one suited for low speeds and untuned intake
system, as is our case [11].
Data acquisition performed with AVL’s
Indimodul 621 Hardware was conducted over
100 complete engine cycles for each sampling
session. Analysis of cycle-related parameters
was done with AVL’s Concerto software. So, the
evolutions to be taken into discussion were the
results of averaging these 100 cycles.
The experimentation was made at a speed corresponding to the usual engine idle (i.e. 800
rpm) and for a 21.60 throttle opening angle.
These values are specific to the experimentation performed on combustion cycle by [10].
As seen from figure 2, the engine is motored at
this speed by an electric motor. This kind of experimentation is used especially to study the gas
exchange processes and its effects on the compression process [12,13].
Experimental results.
Discussion
Figure 3, showing the in-cylinder pressure evolutions for the two cases, Hmin and Hmax, reveals the following:
- a peak pressure slightly greater for Hmin
(9.4 bar comparing with 9.18 bar at Hmax),
generated by a higher effective compression ratio (ECR) due to an early intake valve closing
(EIVC) – see table 1; calculations revealed an
8.1 ECR for Hmin, while for Hmax it is 5.8;
- quasi-identical evolutions during the exhaust strokes;
- very different evolutions during the intake
strokes showing a higher pumping for Hmin.
The first two observations are also valid for combustion cycle [10].
About the pumping work, it is usually illustrated
by pumping mean effective pressure (PMEP),
9
Fig. 4. Pumping work evaluation
which is found by two methods:
- calculation of the low loop area thanks to
the accurate determination of the intersection
point between the two usual loops of the indicated diagram (see the B area and the red point
in figure 4); in this paper, this method is entitled
pV_loop;
- integration between the begining of the exhaust stroke and the end of intake stroke, which
means taking into consideration the C area from
figure 4; here, this method is entitled Int_E&I.
Unlike the pV_loop method, Int_E&I method
allows an analysis of the pumping work, as an
exclusive result of exhaust and intake strokes.
Figure 5 presents in a radar-type diagram the
results on the pumping work evaluation. In order to have more details, in this diagram, the
values of the mean pressures during th eintake
and exhaust strokes are added. The conclusion is
that operating with Hmin caused an increasing
of PMEP_pV_loop with 66.9% and of PMEP_
Int_E&I with 38.7%.
Further on, the following is to be used for evaluating the gas exchange: Dpi – pressure difference between intake manifold absolute pressure
(PMAN) and in-cylinder pressure (PCYL). If Dpi >
0, the flow is normal, i.e. air is inducted into the
cylinder; otherwise, if Dpi < 0 then backflow
occurs, i.e. the air is pushed towards the intake
manifold.
Figure 6 helps to understand the gas exchange
processes. As expected, when using Hmin,
gas recirculation through the intake port is
cancelled. In this situation, the intake valve
opens when in-cylinder pressure drops below
intake manifold pressure (see IVO in fig 6, a).
However, as a consequence of the late EVC, a
certain recirculation through the exhaust port
occurs (see the IVO – EVC range in figure 6, a).
Proceeding with the analysis, one can notice another advantage of using Hmin at this particular
engine speed: maximum piston speed (Wpmax)
takes place when flow area at the intake valve
gap is still very small (hiv = 0.7 mm), generating
– on the one hand – an important Dpi of about
300 mbar (see the black curve in figure 6, a) and,
on the other hand, a much greater flow velocity
than in the Hmax situation. About the latter situation, when Wpmax occurs, Dpi is barely positive
(about 10 mbar – see the black curve in figure 6,
b. NB. In order to better view the sign changing
of Dpi at Hmax, negative value=backflow, positive value=normal flow, Dpi was represented at a
very narrow scale in figure 6, b).
Fig. 5. Pumping evaluation
10
Regarding the phenomena taking place between
the intake BDC (-180 CAD in figure 6) and
IVC, one can notice there is virtually no backflow when using Hmin, Dpi being still positive
(figure 6, a), which is not the case for Hmax
(figure 6, b).
Due to an advanced IVO (see table 1), operating with Hmax causes a backflow towards the intake manifold (see the IVO – TDC / 360 CAD
in figure 6, c). The pressure difference of about
320 mbar correlated with the small intake valve
lifts will certainly generate very high backflow
velocities. These backflows occurs even in the
beginning of the intake stroke and cease to exist in the neighborhood of the green point from
figure 6, b. Afterwards, when flow towards the
cylinder is physically possible, first enter the cylinder the exhausted gases introduced within the
intake manifold after IVO, as explained before.
Analyzing figure 6, b, it is clear that the IEGR
takes also place through the exhaust port (see
TDC / -360 CAD – EVC range). The same figure 6, b shows the fresh air is forced backward at
the beginning of compression stroke (see BDC
– IVC range). In the last part, just before the
Abbreviations and notations
ABDC – after bottom dead center;
Aiv – flow area at the intake valve gap [m2];
ATDC – after top dead center;
BBDC – before bottom dead center;
BTDC – before top dead center;
CAD – crank angle degrees;
CFD – computational fluid dynamics;
DPi – “in-cylinder/intake manifold” pressure drop
[bar];
deg – degrees of crank angle [CAD];
ECR – effective compression ratio;
ECU – electronic/engine control unit;
EIVC – early intake valve closing;
EVC – exhaust valve closing;
EVO – exhaust valve opening;
hiv – intake valve lift/height [mm];
Hmin – minimum intake valve law;
Hmax – maximum intake valve law;
IEGR – internal exhaust gas recirculation;
IMEP – indicated mean effective pressure [bar];
IVO – intake valve opening;
IVC – intake valve closing;
LIVO – late intake valve opening;
MAP – (intake) manifold absolute pressure [bar];
MVL – maximum valve lift [mm];
P – pressure [bar];
PCYL – averaged in-cylinder pressure over 100 cycles [bar];
PFI – port fuel injected;
PMEP – pumping mean effective pressure [bar];
SI – spark ignition;
TDC – top dead center;
VVA – variable valve actuation;
Wiv – flow velocity at the intake valve [m/s];
a)
b)
c)
Fig. 6. Gas exchange evaluation
a. TDC – IVC pressure evolutions@Hmin
b. TDC-IVC pressure evolutions@Hmax
c. IVO – TDC pressure evolutions @ Hmax
IVC, the increasingly higher values of Dpi corroborated with the smaller and smaller values of
intake valve lift generate as before an increase in
backflow velocities at the valve gap.
Certainly, the discussions about the flow velocities are only of a qualitative manner (greater or
smaller). Quantitative figures are to be provided
in a sequel of this paper, thanks to a CFD simulation.
CONCLUSIONS AND PERSPECTIVES
This paper presented the experimental results
concerning the gas exchange of a variable intake
valve lift engine driven at the corresponding
idle speed. Certainly, in this case, gas exchange
means air exchange.
Given the test conditions, the purpose of this investigation was to isolate the effect of the intake
valve law upon the gas exchange.
The results obtained by using this test arrangement could be extrapolated for the situation of
engine autonomous operation: pumping work
will increase when using Hmin and internal exhaust gas recirculation (IEGR) will increase, as
well, when using Hmax.
The work presented in this paper is actually part
of a larger research program concerning the
improvement of idle and low loads and speeds
operation by using low intake valve lifts. One
objective of this research program is to have
some insights about the internal aerodynamics
of the original PFI SI engine when using low
intake valve lift. For this purpose, a 3D CFD
dynamic simulation of the motored engine was
also performed and the presented experimental
results were used to calibrate and validate the
CFD model.
REFERENCES
[1] S.E. Plotkin, Examining fuel economy and carbon standards for light vehicles, Energy Policy. 37 (2009) 3843–
3853.
[2] A.M.K.P. Taylor, Science review of internal combustion engines, Energy Policy. 36 (2008) 4657–4667.
[3] S.M. Begg, M.P. Hindle, T. Cowell, M.R. Heikal, Low intake valve lift in a port fuel-injected engine, Energy.
34 (2009) 2042–2050.
[4] L. Bernhard, Less CO2 thanks to the BMW 4-cyl. Valvetronic engine, ATA. 56 (2003) 96–102.
[5] W. Hannibal, R. Flierl, L. Stiegler, R. Meyer, Overview of current continuously variable valve lift systems for
four-stroke spark-ignition engines and the criteria for their design ratings, SAE Paper. 01-1263 (2004).
[6] H. Hong, G.B. Parvate-Patil, B. Gordon, Review and analysis of variable valve timing strategies--eight ways
to approach, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.
218 (2004) 1179–1200.
[7] I. Pietsch, H. Tschoke, Reduced intake valve lift of SI engines to improve mixture formation, fuel consumption
and exhaust emissions, Ingénieurs de l’Automobile. 9 (2002) 81–85.
[8] P. Podevin, A. Clenci, Technologies de distribution variable pour moteurs à combustion interne, Techniques de
l’Ingenieur. BM2580 (2012).
[9] T.-Y. Wang, Z.-J. Peng, G.-D. Wang, In-cylinder air motion characteristics with variable valve lift in a spark
ignition engine. Part 1: swirl flow, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. 225 (2011) 479–497.
[10] A. Biziiac, Cercetări privind ameliorarea performanţelor energetice ale unui MAS prin variaţia înălţimii
de ridicare a supapelor de admisie, Teză de doctorat, University of Piteşti, 2011.
[11] K. Lee, M. Yoon, M. Sunwoo, A study on pegging methods for noisy cylinder pressure signal, Control Engineering Practice. 16 (2008) 922–929.
[12] S.H. Joo, K.K. Srinivasan, K.C. Lee, S.R. Bell, The behaviourt of small- and large-scale variations of incylinder flow during intake and compression strokes in a motored four-valve spark ignition engine, International
Journal of Engine Research. 5 (2004) 317–328.
[13] R.F. Huang, H.S. Yang, C.-N. Yeh, In-cylinder flows of a motored four-stroke engine with flat-crown
and slightly concave-crown pistons, Experimental Thermal and Fluid Science. 32 (2008) 1156–1167.
11
Experimental Study of Vehicle Dynamic
Based on a Systemic Approach
Ing. George BIVOL
Ministry of National Defence, Bucharest
[email protected]
Prof. univ. dr. ing. Ion COPAE
Military Technical Academy, Bucharest
[email protected]
ABSTRACT
The paper presents the main elements regarding
systemic study of car dynamics that takes into
consideration driver’s actions, road influence and
constructive element’s characteristics. The nonlinearities that are introduced by the driver, the
road and by the constructive vehicle characteristics are presented, and nonlinear mathematical
models can be deducted based on the experimental data.
The vehicle dynamics beneficiated of theoretical
and experimental studies depending on the level
of knowledge of researchers, as well as on the
practical possibilities that were available in order
to conduct the experimental tests [3;4]; added to
that, the approaches were depended on the actual
technology level that the vehicle was fitted, classic
or electronically controlled. The developments in
theoretical terms of certain subjects, the invention of certain investigation hardware that gets
better and better in time and the vehicle fitting
with electronic control systems…all these represent main influence factors onto the theoretical
and experimental study of vehicle dynamics [2].
In the classical approach described by the litera-
Fig.1. The throttle’s position and vehicle speed in the case of two experimental
test-runs using the Logan Laureate vehicle
ture, vehicle dynamics is mostly theoretical and
it does not have a systemic character because it
does not take into consideration the driver’s action. The study only relies on engine’s characteristics (engine exterior characteristic). However
practice has proven that partial loads are the most
commonly encountered situations during normal exploitation and thus it is necessary to tackle
a systemic approach that will take into consideration the driver’s actions [1;2].
As a result, in studying vehicle dynamics it must
be analyzed the driver’s actions influence by the
way he steps on the gas pedal and the time it takes
to react. Both of these parameters are introducing
static nonlinearities. Similarly the nonlinearities
introduced by the road and by the uncertainty of
Fig.2. Examples of gas pedal operation
12
its rolling resistance coefficient and slope angle
need to be better understood. Finally the influence of vehicle constructive elements needs to
be analyzed by the uncertainty it introduces onto
the values of their own parameters [1].
The driver influences the vehicle dynamics
through his driving style (the way it acts onto the
gas and brake pedals) and through his reaction
time [1,2]. This paper is interested in the way the
driver acts onto the gas pedal which introduces
nonlinearities. These nonlinearities are called
within system theory static nonlinearities of relay
type.
Gas pedal operation may be performed in various
ways. Its operation affects the throttle’s angular
position ξ (its opening and closing). The throttle’s
Fig.3. The driver’s actions influence onto the vehicle dynamics by the way he steps
on the gas pedal
position is considered to describe the engine’s
load, because the driver acts on it to change vehicle dynamic behavior (acceleration, maintaining
a constant speed, overpassing etc.); the technical
literature recommends the engine load to be described by the inlet manifold air pressure pa.
The upper graphs from figure 1 presents the values for the throttle’s position and vehicle speed in
the case of two experimental test-runs using the
Logan Laureate automobile. Added to that, the
lower graphs from figure 1 presents the functional dependency between throttle’s position and
vehicle speed; these graphs highlight the fact that
operating the throttle has as effect the introduction of static nonlinearities by the driver.
Figure 2 presents four such examples, which
consist of four static nonlinearities of relay type
[1]. Thus figure 2a presents a static characteristic of ideal relay type, for exemplification on the
horizontal axes is vehicle speed, and on the vertical the gas pedal p; this shows that the driver
acts suddenly on the gas pedal between the two
positions from which one is minimum (of –c
value) and a maximum (of +c value); the maximum movement of the gas pedal is 2c (meaning
100%), but the representation is done according
to the acknowledged procedure, symmetrically
towards the axis origin. The mentioned characteristic shows the neglecting of inertia in operating the pedal, the lack of a constant positioning
area around the origin, the existence of a maximum value and the inexistence of a closed loop;
thus, it is a static characteristic of relay type with
no inertia, no insensibility (no dead zone), with
Fig.4. The influence of the road (the rolling resistance coefficient f) over vehicle dynamics,
60 experimental test-runs using the Logan Laureate automobile
saturation and no hysteresis, being a symmetric
and bipositional nonlinearity (with two active
positions in this case).
Figure 2b presents a relay type characteristic with
a dead zone (there is a zone of constant position around axes origin), with no inertia (pedal
is pressed swiftly), with saturation and without
hysteresis (lack of closed loop); added to that it
is a symmetrical characteristic that has three positions (two active positions and an inactive position). The characteristic shows that the driver
does not press the pedal in an area of 2b length
around the origin, and the pedal operation is performed swiftly both on its pressing as well as on
its release.
Figure 2c presents static nonlinearity of saturated
relay type, with no insensibility (dead zone) and
without hysteresis, but on which inertia is taken
into consideration at the time of pedal operation.
Figure 2d presents a nonlinearity of polarized relay type, without inertia, saturated with hysteresis
and which includes an area of insensibility (dead
zone).
All nonlinearities are described through nonlinear analytic expressions. For example, the polarized relay type nonlinearity from figure 2d is described by the expressions ( ∧ represents the
logical operator for „and”, V ′ represents the
speed’s derivation):
V < −b ∧ V ′ > 0

− c, pentru 

V < b ∧ V′ < 0

p=
′
c, pentru V > b ∧ V < 0


V < b ∧ V′ > 0
(1)
Practically this shows that the driver, wishing to
maintain constant speed within the limits (-b,b)
at an imposed value ( 90 ± 5 km/h ,for example, so
b=5), he performs the following movements:
- Through AB area he maintains a constant position for the pedal (of c value), after which he swiftly releases it in point B, where he acknowledges
he reached the maximum allowed deviation value
b (95 km/h in the presented example);
- through area CD maintains a constant pedal
position (of –c value), after which he swiftly
presses it in point D, where he acknowledges he
reached the maximum –b imposed allowed value
(85km/h in the presented example).
Figure 3 presents the driver’s influence onto vehicle dynamic behavior through the existence of
a ramp (sees fig. 2c, line AB), for its three values:
15 degrees, 45 degrees and 65 degrees; it is being concluded that in the latter case the driver
pressed the pedal suddenly, getting closer to the
13
Fig.5. The friction influence onto vehicle speed, 39th experimental test-runs using the Logan Laureate automobile
ideal relay characteristic from figure 2a. As we can
see from figure 3, for experimental test-run L25,
when the driver presses more and more violently
on the gas pedal, the vehicle’s dynamic behavior
increases (average speed and 2nd norm increase).
The graph from figure 3 highlights another important aspect, which has implications in the establishment of mathematical models for driver’s
actions: we can see that the average speed and
2nd norm have lower values than the experimen-
tal ones at a 45 degrees ramp, but higher at a 65
degrees ramp. This means that at this test ramp
we can adopt an equivalent nonlinearity of ramp
type in order to model driver’s actions, which in
this case has a value that ranges between 45÷65
degrees; this aspect is covered by the Hammerstein-Wiener mathematical model.
The road on which the vehicle is moving influences the vehicle’s dynamic behavior through its
non-linearity introduced and through its uncer-
tainties that it has over the rolling resistance coefficient and slope angle. The nonlinearities that
the road is introducing are similar with the ones
that the driver introduces, thus the analysis is performed in the same manner. The sudden overpass
from one type of road onto another (for example
from tarmac onto dirt road) is similar with the
ideal relay; the same phenomenon happens in the
case the vehicle runs over a hole in the road.
Regarding the uncertainties, considering a vehicle
Fig.6. The friction influence onto vehicle speed, 60 experimental test-runs using the Logan Laureate automobile
14
moving onto a horizontal road (as is the experiments were performed), than we take into consideration only the uncertainties that affect the
rolling resistance coefficient f. In this case f varies
between certain limits, for example a tarmac road
or concrete f=0,012÷0,022. In consequence, the
differential equation for vehicle dynamics is:
(2)
ηig
g
kSg 2 v′ = t t M e − f −
v
δGa rr
δ
δGa
where f varies between a minimum value fm and a
maximum one fp:
f = [ f m ; f p ] = [0, 012; 0, 022]
(3)
In expression (2) we noted: v – vehicle speed; g –
gravitational acceleration; δ - coefficient for masses that have rotational movement; Ga – vehicle’s
weight (ma – vehicle mass); Me – engine torque;
it – total transmission gear – ratio; ηt – transmission efficiency; rr – wheel rolling radius; Ra – air
resistance; k – aerodynamic coefficient; S – vehicle transversal surface.
In differential equation (2) there is a single uncertainty f, and the other parameters’ values are
adopted in the middle of their variation interval,
as frequently is done. For example, transmission efficiency, that has values in the range ηt
=[ ηtm;ηtp]=0,82-0,92, is chosen ηt =0,87; the
other values are: k=0,25; Ga=12311,6 N; ks=0,87;
rr=0,3; δ=1,04 (values specific for Logan Laureate
vehicle). In the end we obtain a differential equation having the following form:
2
(4)
v′ = c1M e − [c2 m ; c2 p ] − c3 v
the values for coefficients c(⋅) are deducted immediately; the expression (4) is a differential equation whose coefficients vary into an interval and
they are not constant as in the classic case.
Thus we achieve the results presented in figure 4, including the values for the main statistic
characteristics: average value and 2nd norm. The
graph highlights that the road’s influence is small,
obviously when looking from the uncertainty
level for a certain road, in this case tarmac road
or concrete. Truly from figure 4 we can conclude
that for the 60 experimental test-runs, the average value varies with only 1.5%, and 2nd norm
with only 1.3%, so small values. As we can see in
expression (3), the rolling resistance coefficient f
varied with 83,3%. From the graphics we can also
see the maximum variations, for the experimental test-run L16, which are 2,5% for the average
value, respectively 2,3% for 2nd norm; so small
Fig.7. The influence of vehicle’s gravitational force onto vehicle speed,
19th experimental test-runs using the Logan Laureate automobile
values as well.
The constructive elements influence the vehicle
dynamic behavior by its nonlinearities that are
introduced through the uncertainties over the
values specific for certain element parameters.
The nonlinearities that are introduced by the constructive elements are static, both essential (relay
type: friction, gap, stopper, hysteresis etc.), and
nonessential, the latter being represented by the
well-known static characteristics (for example the
static characteristics of thermal engine).
For example, the figure 5 presents the concomitant influence of dry friction and viscous friction
onto speed on one experimental test, for two values of friction coefficient µ.
The graph from figure 5 shows a major influence
of friction onto vehicle dynamic behavior; a double increase of friction coefficient leads to a decrease of vehicle dynamicity as the average value
and 2nd norm of vehicle speed show.
The graph from figure 6 confirms the major influence of friction onto vehicle dynamic behavior
for all experimental test-runs; a double increase
of friction coefficient leads to a double decrease
of vehicle dynamicity.
The uncertainties that are introduced by the constructive elements are studied similarly as those
that are introduced by the road; the conducted
studied revealed that the uncertainties introduced
by the constructive elements have considerable
higher importance than the ones introduced by
the road. The analysis is being performed starting
from the differential equation (2), on which it is
being considered that there are uncertainties only
on the vehicle’s weight. So, it is considered that the
vehicle’s weight is Ga=mag=[Gam; Gap]=9564,75-
15058,4 N, and the other parameters have average values within the given interval. Thus we
reach an expression of (4) form:
2
(5)
v′ = [ c ; c ] M − c − [ c ; c ] v
1m
1p
e
2
3m
3p
This represents a differential equation for vehicle dynamics that operates with ranges of values
because we took into consideration the vehicle’s
weight uncertainties. Based on differential equation (5) we obtain the result presented in figure
7 from which we can observe a higher level of influence over vehicle dynamic behavior caused by
the uncertainties afferent to vehicle’s weight.
Conclusions: We can conclude that the systemic
study of vehicle dynamics based on experimental data allows us to highlight the influences
produced by the driver, the road and vehicle’s
constructive elements onto its dynamicity and
efficiency. Besides, it can be established the systemic mathematical models for vehicle’s dynamics (differential equations, Hammerstein-Wiener
mathematical models etc), which take into account the vehicle’s constructive characteristics,
road influence and driver’s action.
REFERENCES
[1] Copae I. Teoria reglării automate cu aplicaţii la autovehiculele militare. Sisteme automate neliniare. Editura Academiei Tehnice Militare, Bucureşti, 1998
[2] Copae I., Lespezeanu I., Cazacu C. Dinamica autovehiculelor. Editura ERICOM, Bucureşti,2006
[3] Gillespie D. T. Fundamentals of Vehicle Dynamics.
SAE Inc., S.U.A, 1992
[4] Pereş Gh., ş.a. Dinamica autovehiculelor. Tipografia Universităţii Transilvania, Braşov,1988
15
The Study of a Vehicle Suspension Oscillations
in Case of Bump Travelling
where: F(t) is the projection of the external
forces resultant on the oscillation direction, m is
the mass of the vehicle, x is the vertical displacement of the center of mass of the vehicle and Fl
is the link force.
The vertical movement of the lower end of the
link is noted with „e”, which appears from the
road irregularities. Thus the deformation of the
link will be: u = x − e .
If applying the previous relation the Laplace
transform we will obtain:
(2)
m( s 2 ⋅ x − s ⋅ x0 − v0 ) = F − Fl Marinescu Oţăt Oana
Oţăt Victor
Gabriel Cătălin
Universitatea din Craiova, România
ABSTRACT
This paper presents an approach for the dynamic
modeling and simulation of a Mac Pherson suspension system, considering the oscillations due
to the shape of the road. The first part of the paper describes the mathematical model of a single DOF spring-mass-damper system. The study
of vibrations was simplified by considering the
vehicle as a rigid body, with only one degree of
freedom, moving on the vertical axis. Using this
hypothesis, a 3D model of suspension mechanism was created and analyzed, respecting the
properties of a real model.
Kinematic and dynamic results were obtained
and their applicability was analyzed for providing input data for other simulations.
THE SINGLE DEGREE
OF FREEDOM MODEL
The vehicle can be modeled through a mechanical system with continuously distributed and
concentrated masses being interrelated by elements with elastic and dissipative properties.
The use of such a model is not practical due
to the high difficulties that appear both
while
s +a
x=
determining the measures which
( s + acharacterize
) + ( w −a )
the vehicle vibrations and while extracting the
conclusions regarding their behavior in relation to the variation of some key parameters
of the system. For this reason, the study of the
vehicle’s vibrations is completed by using simplified mechanical models, with certain degrees
of freedom, which are selected according to the
desired purpose and the size of the allowed travels and the existing relations among different
subassemblies of the vehicle.
The model regards the vehicle as a single DOF
rigid, which oscillates on the vertical axis, according to figure 1.The Newton motion law is:
2
••
m x = F (t ) − Fl
16
2
2
Fig.1. Representation
of the single DOF model
K
K
K 2 − 2a t 
1 
−a t 2
−a ( t +T 1) 2
(9)
(3) = ⋅ A e ⋅ 1 − 2 
2
2
2
 d 
From (3) Laplace image is determined for m
mass movement:
The relationship between the mechanical enerF ( s ) + E ( s ) ⋅ e( s ) + R( s ) + m( s ⋅ x0 + v0 ) (4) gy, dissipated throughout a pseudo-period, and
x( s ) =
m ⋅ s 2 + E (s)
the energy value in the maximal point is:
(
)
(
)
m( s 2 ⋅ x − s ⋅ x 0 ∆
−E
v0 )== F −AE⋅(es ) ⋅ ( x −−e) + RA
( s⋅) e
The movement x(t) of the suspended mass is
(10)
1  
r = 1 − 2 
obtained by inverting the relation Laplace (4).
 d 
In case of free amortized vibrations, the oscillation mass is linked by a Kelvin model, and the Thus, for a relationship d=4 between the first
motion equation in Laplace images becomes:
and the second amplitude of the oscillation, the
(5) shock absorber absorbs and converts into heat
93.75% of the energy oscillation transmitted
where α is the amortizing factor.
to the suspended mass. Normally the amortizIn case of subcritical amortization, the relation ing process within the first period is between
(5) can be written as:
92 and 98 % from the energy transmitted to
the suspended mass, which corresponds to
a x0 + v0
s +a
w2 − a 2
x=
+
⋅
2
(s + a ) 2 + ( w 2 − a 2 ) 2
w 2 − a 2 ( s + a ) 2 + ( w 2 − a 2 )d=3,7...22,4.
(6)
In case of overcritical amortization, relation (5)
ax +v
w −a
+
⋅
can be written as:
w −a
(s + a ) + ( w − a ) 0
2
2
2
0
2
2
2
2
2
2
x=
The vibration of the oscillating mass can have a
shorten form:
(7)
x(t ) = A ⋅ e −a t sin(w1t + j ) 1
a x0 + v0
 x0 −
2 
a 2 − w2

a x0 + v0
 x0 +

a 2 − w2


1
1

+ ⋅

2
2
2
 s +a + a −w

1
⋅

2
2
 s +a − a −w
(11)
Inverting Laplace relation (11) we obtain the
The motion law (7) shows that in this situation movement of the suspended mass.
we can obtain a vibration unamortized motion
whose amplitude decreases in time. An indica
a x0 + v0  −(a + a −w ) t 1 
a x 0 + v 0  − (a −
1
⋅e


+ ⋅  x0 +

tor of the amortization intensity is given by the x(t ) = 2  x0 − a 2 − w 2  ⋅ e
2 
a 2 − w2 
(12)
relationship of two successive amplitudes.
a x0 + v0  −(a + a −w ) t 1 
a x0 + v0  −(a − a −w ) t
1
⋅e
 ⋅ e (8)
A ⋅ e −a t
x(t ) =  x0 −
+ ⋅  x0 +
2
2 
2
2 
d=
= e a T 2
2
A ⋅ e −a ( t +T 1)
1
2
a −w 
2
2
2 
2
2
a −w 
The variation of the mechanical energy through- Using the functions hyperbolic sine and hyperout a pseudo-period is:
bolic cosine leads to the following expression of
(1)
the movement:
a 2 −w 2 ) t
(13)
It can be noticed that in this situation the movement has no oscillating character, as it is aperiodic. The movement tends to cancel itself after
an infinite time interval. In reality the movement
stops after a finite time interval.
In case of critical amortization, if considering
that ω=α, equation (5) becomes:
s
1
x = x0 ⋅
+ (2a x0 + v0 )
(14)
2
2
(s + a )
(s + a )
Fig.2. 3D modeling of a Mac Pherson type
suspension mechansim
Fig.3. Simulation of a road bunp encountering,
modeled with the Adams View software
Using the transformations:
(15)
The reverse Laplace relationship (14) is:
x(t ) = x0 ⋅ e −a t ⋅ (1 − a t ) + (2a x0 + v0 )t ⋅ e −a t = e −a t [(1 + a t ) x0 + v0 t ]
(16)
a t ) + (2a x0 + v0 )t ⋅ e −a t = e −a t [(1 + a t ) x0 + v0 t ]
In this case the movement has an aperiodic
character as well. [1]
3D MODELING AND SIMULATION OF
ENCOUNTERING A ROAD BUMP
In order to evaluate the mathematical model
the virtual simulation of the behavior of a vehicle suspension was needed. For creating a 3D
model there was chosen a Mac Pherson suspension system type, from a Daewoo Matiz model.
The components were modeled using th Solis
Works software, taking into consideration their
geometrical characteristics, as shown in figure
2 as well. There was made the export towards
the Adams View software as parasolid elements.
There was also taken into consideration their
positioning on the real model, and there were
created the links of the mechanism by kinematic
couplings, followed by the kinematic analysis
of the model. [2] Elastic, mass and amortization characteristics were attributed as following:
constant of the spring k = 15 000 N/m, damping coefficient of the damper c =1200 Ns/m,
and half of the loading mass for the front axle
m =320 kg. The road was simulated by inserting
a bump, having the height e =60 mm and a 45°
angle, as shown in figure 3.
There were considered the movement of the
vehicle in speed conditions of 10, 20 and 30
km/h.
Fig.4. Spring deformation in time, when passing encountering an obstacle
the behavior of the suspension mechanism when
crossing the inclined portion of the obstacle, up
to the height of e=60 mm. The results have been
extracted as kinematic and dynamic measures.
An example has been provided within figures 4,
5 and 6, where one can observe the deformation, the deformation speed and the vertical
force in the spring, depending on time.
CONCLUSIONS
The obtained results have general character;
however, they allow us a more complex approach concerning both the one DOF model,
and a completed simulation for the working
conditions of the vehicle suspension.
The dynamic model with one DOF can be used
in order to observe the vehicle’s oscillations,
though for a more detailed research, it has to
be taken into consideration the fact that the
suspended masses act to the road through tires.
Consequently there had to be taken also into account the elastic and the amortizing characteristics of the tires. This aspect is equivalent to an
approach of the vehicle’s oscillations using the
2 DOF model, to obtain values that are more
closer to experimental results.
The results of this research study contribute to
the establishing of the kinematic and dynamic
Following the simulation there were analyzed parameters, which are transmitted to those sys-
tems that interact with the suspension, like for
example the steering system, which can provide
us with input parameters needed for the simulation of their own functioning.
Fig.5. Spring deformation force dependence
on time
Fig.6. Vertical force variation in time
REFERENCES
[1] Oţăt V., Bolcu, D., Thierheimer W., Simniceanu
L., Dinamica autovehiculelor, Editura Universitaria,
Craiova, 2005, ISBN 973-742-023-3
[2] Dumitru N., Mecanisme spaţiale. Modelare cinematică şi dinamică prin metode computerizate, Editura
Universitaria, Craiova, 1999, ISBN 973-9271-83-1
17
Uncertainty Assessment in Crash Analysis
by Coupling Transient Dynamic Finite Element Analysis
with the Fuzzy Concept – Part 1: Theory A. D. M. Sîrbu
University POLITEHNICA of Bucharest, Chair of Road Vehicles
LMS International, Simulation
Division, Belgia
e-mail: [email protected]
L. Farkas
Division, Belgia
e-mail: [email protected]
S. Donders
Division, Belgia
H. Van der Auweraer
Division, Belgia
D. Moens
Lessius Mechelen University College,
Department of Applied Engineering,
Belgium
KU Leuven, Department of
Mechanical Engineering, Belgium
E. M. Negruș
University POLITEHNICA of
Bucharest, Chair of Road Vehicles
Rezumat
În prototiparea virtuală, este important de avut în
vedere sursele cheie de incertitudini din produsul de
proiectat și impactul acestora în performanța acestuia. Această lucrare adresează incertitudinile care
afectează performanța la impact. Incertitudinile unui
sistem pot fi considerate folosind o abordare neprobabilistică cu metoda elementelor finite fuzzy. Se investighează cuplajul intern dintre analiza cu elemente finite explicită și conceptul fuzzy prin analiza tranzitorie
dinamică a unui sistem simplu solicitat la impact cu
incertitudini. Programul de calcul tranzitoriu dinamic este bazat pe metoda elementelor finite explicită
cu formularea diferențierii centrale, fiind cuplat cu
conceptul fuzzy. Se studiază efectul incertitudinilor
pe diferite rezultate ale analizei.
18
Abstract
In virtual prototyping, it is important to be
aware of the key sources of uncertainty in the
designed product and the impact on the product
performance. This paper addresses uncertainties
that affect the crashworthiness performance.
Uncertainties of a system can be considered
by using a non-probabilistic approach with the
fuzzy finite element method. Investigations are
conducted on internal coupling of explicit finite
element analysis with the fuzzy concept through
transient dynamic analysis of a simple system
subjected to impact loading with uncertainties.
The transient dynamic solver is based on the
explicit finite element method with central difference formulation, which is coupled with the
fuzzy concept. Effects of uncertainties on various analysis outputs are investigated.
Introduction
Simulation techniques are standard in automotive design, with cycle time and costs being continuously reduced by sustainable improvements
in computer aided design and analysis tools.
Finite element modelling capabilities evolved
with technology, advancing with exponential
growth of model detail throughout the last decades. Crashworthiness holds an important place
in automotive passive safety research. Ideally,
mathematical expressions replicate the real life
behaviour of a structure.CAE models are deterministic models, providing a prediction of the
structural performance based on the chosen
geometry and material/loading parameter settings.
However, in reality, model parameters are not
always exactly known or defined and parameters
may differ between identically manufactured
products. Therefore, a parameter formulation
limited to deterministic (“crisp”) may quantities
provides a limited perspective to reality. Including non-determinism in the finite element analysis process by adding uncertainties enhances the
trustworthiness of the model. For crash analysis,
typically an explicit formulation of the finite element method is used.
Generally, when a non-deterministic method
takes optimal use of the (possibly adapted) solver scheme of the numerical solver, additional ef-
ficiency gains can be envisaged, for instance by
efficiently re-using part of a previous calculation
to facilitate the next calculation[1]. For the purpose of investigating and studying the analysis
possibilities from the basic fundamental level of
the mathematical apparatus, a simple transient
explicit crash solver is implemented in MATLAB programming environment and validated
for accuracy by correlating its outputs with a
commercially available solver. Uncertainty assessment is investigated by coupling the implemented impact algorithm with the fuzzy concept for finite element modelling.
Finite element method and
explicit formulation
Basics
Finite element modelsare approximate representations of real systems or structures.Applying
the finite element method to predict the behaviour of a system by using finite element models
is referred to as finite element analysis. This paper is focused on transient dynamic structural
finite element analysis, where the condition
of the system is a function of time. Spatial approximation using the finite element method
and time approximation where the ordinary
differential equations are further approximated
in time domain are computed by reaching the
dynamic equilibrium equation at every time
step[2]. Considering
as the displacement
nodal values vector,
as the nodal velocities
vector and
as the nodal accelerations vector, the dynamic equilibrium equation is computed at each time step is expressed as:
(1)
,
and
are m × 1 vectors,
is the
m × m mass matrix,
is the m × m damping
matrix,
is the m × m stiffness matrix and
is the m × 1 total forces vector, while m
is the number of nodal degrees of freedom per
finite element.
Explicit time integration
Complete control and understanding of uncertainty assessment can be obtained by developing
a fully interactive solving algorithm for explicit
analysis. The implemented mathematical proc-
information required for the next step at the
present time step. This way, analysis stability
is maintained.The time iterations initiate from
time step zero, with information being known
from the initial conditions. It is assumed that
=
, in order to solve expression (5) and
begin the time integration routine.
Fig. 1. Flow chart of central difference time integration for step n
ess is presented as follows. In transient dynamic
analysis, equation (1) is integrated in time domain by applying specific simplifications. The
resulting mathematical expression is
(2)
Where the mass matrix [M] is diagonalized for
simple inversion (if it is not already diagonal) by
specific mathematical algorithms, as described
in detail in[3][4][5][6]. Stiffness or damping (if considered) matrix inversion are not required, as they are included in the force vector
definition[7].Newmark’s algorithm is the most
common time integration method used in dynamic analysis [8]. The scheme approximates
the displacements, velocities and accelerations
at time step n+1 by using the following explicitequations, resulting from the Newmark’s algorithm [9][10][11]:
(3)
(4)
Looking at the explicit routine equations, it is
observed that the information at time step n+1
Non-determinism
Deterministic analysisis limited to crisp inputs
and cannot cope with non-deterministic data.
Uncertainties may arise from insufficiently or
partially known data, such as imprecisely defined impact velocity, mass or material definitions. Additionally, finite element analysis is
merely an approximation of the continuum
problem, leaving room for results interpretation.
Importance of non-determinism in engineering
design was mentioned by many researchers in
works like[14][15][16]. Non-determinism can
be found in every stage of product development.
It is classified by Oberkampf[17] in two main
categories: parameter variability and parameter
uncertainty. Variability refers to the variation
inherent to the physical system or the environment under consideration, while uncertainty is
a potential deficiency in any phase or activity
of the modelling process that is due to lack of
knowledge. Variability is typically treated with
probabilistic analysis, e.g. reliability analysis to
calculate the probability that a failure is attained
as a result of input variability. A reliable design
has a low failure probability with respect to predefined failure constraints.In order to describe
variability, a large quantity of data must be
gathered for characterization of the parameter
distributions. In contrast, uncertainty methods
are typically treated with a possibilistic method
such as the fuzzy finite element approach, which
are able to deal with lack of knowledge in the
parameter distributions. This paper focuses on
addressing parameter uncertainty for crashworthiness applications.
is obtained by using the information from the
previous step. Most finite element analysis solvers based on the explicit algorithm have adapted
the Newmark scheme[11][12] into a staggered
time marching routine. In this routine, the nodal
velocities are computed at half time steps (
)
and displacements at full time steps (
), giving the so-called central difference method, Interval and fuzzy analysis
which is expressed with the following equa- Lately, non-deterministic methods are receiving
increasing interest from finite element analysts,
tions:
with examples such as the interval method,a
concept introduced by Moore[18]. This is a
method for expressing quantities with limited
(5)
information availability (also regarded as the
“anti-optimization” approach).Considering
(6) to be the parameter vector, contained within
and the
The computation cycle for every time step n is the interval vector (hypercube)
briefly presented, as[7][9][11][12][13]. Figure deterministic analysis symbolized by function
, applied to each parameter, the inter1 illustrates the general flow chart of the time
is
integration scheme commonly used in crash val finite element analysis solution set
defined
as[19]:
analysis.
As presented, the central difference algorithm
(23)
has the particularityof calculating part of the
19
is performed by α-cuts.Figure
2 shows the discretization by
Acknowledgements
α-cuts of a fuzzy set with triAndrei DragoşMirceaSîrbu gratefully
angular membership function,
acknowledges the PhD funding from
which will be used later on in
the Sectoral Operational Programme
the practical application.
Human Resources Development 2007Each α-cut gives set values
2013 of the Romanian Ministry of
with equal membership level,
Labour, Family and Social Protection
basically creating intervals that
through the Financial Agreement
are further used for interval
POSDRU/88/1.5/S/61178.
analysis. Outputs are similarly
Furthermore, the authors kindly acassembled as intervals and
knowledge IWT Vlaanderen for
fuzzified into fuzzy outputs at
supporting the research projects
each α-cut. The fuzzy finite elIWT-070401
”Simulation-Based
ement analysis has the downDevelopment of an Innovative Bumper
Fig. 2 Discretisation of a fuzzy set by α-cuts
side of lack of implementation
Beam Concept with Integrated
on currently available comCrashbox Functionality (I-CRASH)”,
where
is the general result of the interval fimercial solvers. Coupling crash solvers with the
and the SBO project 060043 “Fuzzy
nite element analysis. Therefore, the set
fuzzy concept can be achieved by complete inFinite Element Method”. In addiis composed of all vectors
that are obtained
teraction with the crash analysis process. In this
tion, we gratefully acknowledge the
from finite element analysis
of all the vecwork, the coupling is made possible by develEuropean Commission for supporttors contained in the interval vector
.
oping dedicated MATLAB algorithms for both
ing the Marie Curie FP7 IAPP project
Most research by using interval finite element
crash and fuzzy analysis.
285808 “INTERACTIVE” (see http://
analysis aims towards obtaining an interval vecIn the following article (Part 2), an application case
www.fp7interactive.eu/).
tor approximation for the exact solution set,
will be presented and coupling will be demonstrated
by neglecting interdependencies between the
on a concept model of an automotive bumper.
components of the output vector. This method
is referred to as the hypercube approximation REFERENCES
of results[20], in which each vector component [1] L. Farkas, An efficient fuzzy non-deterministic approach for structural finite element analysis, PhD Thesis
gets its range of values, but not all combinations from Katolieke Universiteit Leuven, Leuven, Belgium (2012).
of these ranges are part of the exact solution set. [2] J. N. Reddy, An Introduction to Nonlinear Finite Element Analysis, Oxford University Press, USA (2004).
The interval analysis can be further extended [3] A. A. Shabana, Computational Continuum Mechanics, Cambridge University Press (2008).
[4] C. Felippa, Introduction to Finite Element Methods, University of Colorado courses, retrieved in 2012 from
towards analysis with the fuzzy set concept.
www.colorado.edu/engineering
Adding supplemental information to the un[5] S. R. Wu, W. Qiu, Nonlinear transient dynamic analysis by explicit finite element with iterative consistent mass
certainty assessment process is possible by us- matrix, Communications in Numerical Methods in Engineering, Vol. 25, No. 3 (2008), pp. 201-217.
ing fuzzy sets, firstly introduced by Zadeh[21]. [6] P. Solin, Partial Differential Equations and the Finite Element Method, John Wiley & Sons, USA (2006).
The membership function
differentiates ANSYS, ANSYS LS-DYNA User’s Guide Release 13.0, USA (2010).
a fuzzy set from a conventional crisp set, giving [7] O. C. Zienkiewicz, R. L. Taylor, The Finite Element Method – Fifth Edition – Volume 1: The Basics, Buttereach containing object a grade of membership worth-Heinemann, USA (2000).
in the fuzzy set . This degree of membership [8] O. C. Zienkiewicz, R. L. Taylor, The Finite Element Method – Fifth Edition – Volume 2: Solid Mechanics,
ranges between zero and one, creating gradual Butterworth-Heinemann, USA (2000).
transition between the quality of being a mem- [9] G. R. Liu, S. S. Quek, The Finite Element Method: A Practical Course, Butterworth-Heinemann (2003).
[10] M. A. Crisfield, Non-linear Finite Element Analysis of Solids and Structures – Volume 2: Advanced Topics,
ber and not being a member of the set:
(24)
whereU is the domain. Linguistically, fuzzy sets
distinguish between members by including the
information of being “less a member” or “more a
member” of the set; the ‘degree of membership’
is quantified by the membership function. The
“crisp member” is a special case, corresponding to ”full membership” (μ=1). For a general
uncertain parameter, the non-deterministic,
uncertain, fuzzy value is quantified through the
process of fuzzification[20].
Since a fuzzy set is a continuum in itself, it
has an infinite range of possible. A method
of discretization is required for implementation in the numerical context of finite element
analysis. Herein, the description of fuzzy sets
20
John Wiley & Sons, England (1997).
[11] RADIOSS, Radioss Theory Manual 10.0, USA (2009).
[12] J. Bonet, R. D. Wood, Nonlinear continuum mechanics for finite element analysis, Cambridge University
Press, USA (1997).
[13] L. Farkas, S. Donders, G. Rocca, B. Peeters, H. Van der Auweraer, D. Moens, Importance of uncertainties
in non-linear simulation and testing for engineering design, EURODYN, Leuven, Belgium (2011).
[14] L. Farkas, C. Canadas, S. Donders, T. Van Langenhove, N. Tzannetakis, Optimization study of a parametric vehicle bumper subsystem under multiple load cases using LMS Virtual.Lab and OPTIMUS, 7th European
LS-DYNA Conference, DYNAmore GmbH, (2009).
[15] M. Thiele, M. Liebscher, W. Graf, Fuzzy analysis as alternative to stochastic methods a comparison by
means of a crash analysis, 4th German LS-DYNA Forum, Bamberg (2005).
[16] W. Oberkampf, S. DeLand, B. Rutherford, K. Diegert, K. Alvin, A new methodology for the estimation
of total uncertainty in computational simulation, Proceedings of the 40th AIAA/ASME/ASCE/AHS/ASC
Structures, Structural Dynamics and Materials Conference (1999), pp. 3061-3083.
[17] R. Moore, Interval Analysis, Prentice Hall, Englewood Cliffs, England, 1966.
[18] D. Moens, M. Hanss, Non-probabilistic finite element analysis for parametric uncertainty treatment in applied
mechanics: Recent advances, Finite Elements in Analysis and Design, Elsevier (2011), No. 47, pp. 4-16.
[19] T. J. Ross, Fuzzy logic with engineering applications, 3rd edition, John Wiley and Sons, USA (2010).
[20] L. A. Zadeh, Fuzzy Sets,Information and Control (1965), No. 8, pp. 338-353.
Utilization of Traffic Simulation Programs in the Creation of
Road Traffic Strategies in Order to Reduce Pollution
software platform (software developed by the
company TSS - Transport Simulation Systems,
which integrates three types of traffic models
– microscopic, mesoscopic and macroscopic)
simulations of road traffic at any level of detail, by default quantification of the values for
Ing. Lucian MATEI
emissions generated by vehicles with internal
SC IPA CIFATT Craiova
combustion engines, are obtained. Therefore
considering as inputs, the measured values, values characteristic to road traffic parameters, we
Dr. mat. George OPRICĂ
Departamentul Autovehicule
can model and simulate traffic solution at comşi Transporturi Facultatea de
parative level (fixed control / actuated control)
Mecanică din Craiova
obtaining reports that allow quantification of
Ing. Laurenţiu PLESEA
URCOSYS Craiova
road traffic and hence the chemical pollution.
Through modeling, simulation and verification
of traffic solutions before their implementation,
Abstract
we can avoid expensive solutions that ultimately
The need for intelligent road transport systems may prove ineffective.
led to the development of the software industry for planning, modeling and simulation The necessity of urban traffic
of the road traffic behavior, regardless of the fluidization
environment (urban or rural), type of traffic Urban flow for road traffic, affects almost everyand the infrastructure of the area considered. thing about modern life (the environment - polDevelopment of software packages capable of lution, noise, heat, traffic accidents, traffic safety,
simulating road traffic patterns is required to as- degree of nervousness of people in traffic, travel
sess the performance and reliability of the con- times between two targets in the city, the pace
trol systems that will be implemented.
of life, economy and so on). These are just part
Based on these premises in the Vehicles and of what it means in the total context the influTransport Department of Craiova there are pre- ence of fluidization / urban traffic decongestion
occupations to elaborate different strategies for in the today cities on our daily life.
optimizing road traffic. Thus using AIMSUN Road traffic pollution can reach different levels
Conf. univ. dr. ing.
Ilie DUMITRU
Departamentul Autovehicule
şi Transporturi Facultatea de
Mecanica din Craiova
[email protected]
of intensity and severity, depending on location
and traffic conditions.
Modern solutions aimed at the coordination and
the management of traffic, in order to ensure the
best possible driving conditions for traffic participants. This is reflected by the decreasing of
risks, of congestions and if you cannot avoid
this some measures can be set to overcome the
situation, resulting in reduced emissions and
fuel consumption, thus reducing travel time
and drivers stress increasing their safety and
comfort, minimum delay for the route; access
routes clearing for assisting vehicles in special
missions.
Based on this premise in the Department of
Vehicle and Transport of the University of
Craiova there are concerns about traffic strategies for optimizing road traffic. Thus using
AIMSUN software platform (product made
by the company TSS - Transport Simulation
Systems, which integrates three types of traffic
patterns - microscopic, mesoscopic and macroscopic) traffic simulations are obtained at any
level of detail, implicitly quantification of emission values generated by vehicles with internal
combustion engines. Thus considering as input
data, specific parameters and characteristics
of traffic, traffic solutions at comparative level
can be simulated and modeled (fixed control /
adaptive control) obtaining reports that allow
quantifying of road traffic and hence chemical
Fig. 1 Signal group generation
21
Fig. 2 Traffic simulation in a intersection
pollution. By modeling, traffic simulation and
verifying the solutions before their implementation, high costs for solutions that ultimately may
prove ineffective, can be avoided.
The importance of chemical
pollutants values in road
traffic determinations
In the traffic domain literature [4,5], for example, there are multiple approaches for estimates
of traffic emission rates.
Chemical pollutants emission rates calculated
for light and heavy vehicles is determined by
the relationship:
Fig. 3 Cinematic parameters evolution
Where:
Vmed pr = medium projection speed
A, B, C = class emissions coefficients (CO2,
NOx, PM, VOC) for a simplified hypothesis of
two vehicles categories (light and heavy)
Finally the emission concentration calculated
according to the flow composition of vehicles
is determined by a weighted average that takes
into account vehicle categories (light or heavy)
and emission rates.
To estimate the amount of emissions (g) a couple of things are taken into account: weight of
the multiples emission rate for vehicles in a total time, volume and length of the road.
Moreover in Fistung approaches for the dimension of the environmental of transport
[3], there are highlighted the related cost categories: air pollution, noise, congestion, road
accidents and the reduce externalities caused
by transport activities.
Air pollutants emitted by road transport require special attention and the most important
22
Fig. 4 Number of stops made by a vehicle
is the assessment of products risks on the environment and health. To develop strategies
in urban traffic it is imposed to estimate the
pollutants quantities generated on the road
(especially in the analysis). Studies are developed for the impact of harmful effects on the
affected population, focusing on the impact of
every pollutant agent.
In the domain literature [2] there are some
methods for solving these problems. Thus in
1994 Ostro proposed method that requires
two steps:
1. Quantifying the effects of pollutant emissions on vehicles with internal combustion engines that are used to fit road vehicles; resulting values can be so-called made “cause-effect
functions”, which highlights the influence of a
certain quantity of a pollutant on health.
2. Estimating the costs (monetary impact) on
health by the relation: (2)
(2)
where:
Pi - Represents the quantification of the economic health changes due to adverse influence
of specific pollutants in traffic
- Change in the population at time “i”
depending on specific pollutant “j”;
t - The type of engine (spark ignition engines,
compression ignition engine)
b - Specific health function
- Population exposed to pollutant “j”
- Concentration of the pollutant “j” given
the type “t” engine.
The greatest difficulty in assessing external
costs due to air pollution, is the best estimate
of the impact of different types of pollutants
on health
Using Aimsun software in the
estimation of the pollutant
emissions variation for
different road traffic
strategies
Creating groups of signal
(Groups of current traffic)
Based on field
measurements current traffic groups
will be made, and
will be used further
in the fluency (traffic light), specifying
the class of vehicles
for which the current traffic group is
created.
Entering parameters
in Aimsun software
The input for the
traffic volumes is
achieved for each
vehicle separately,
and if necessary,
create separate categories of vehicles to make the simulation as
real as the real traffic.
Based on field measurements and laboratory
calculations, we will introduce the parameters
in the simulation software, we will calculate the
parameters of perception - reaction in intersection and road sections, we will introduce the
degree of adventurous maneuvers and illegal
occupations of lanes etc.
Intersection simulation in Aimsun program
To test the model created for the studied intersection or section, a new scenario and a
experiment belonging to the scenario will be
created. You can create an unlimited number
of scenarios. It integrates into the scenario the
plan for traffic light control, i.e. control plan for
transportation. Simulation scenario imposes
the creation of a reply.
Fig. 5 Travel time values
When running a simulation some information
on cars (attributes on network speeds and positions and so on) can be obtained.
Case Studies
For this work were taken into consideration
two ca ses (i.e. isolated traffic intersection
from a section) specific traffic from Craiova,
for which were studied the reduction of chemical pollution by making simulations under varying conditions of traffic lights (fixed and then
adaptive traffic light).
The simulated intersection is one of a major importance for traffic roads in Craiova, because it
is a road junction between several districts of
the city and the center of Craiova.
To simulate the intersection and the studied
section it was taken into consideration the
current traffic lights plan, vehicle flow, the cur-
Fig. 6 Print – screen from the traffic simulation, highlighting of the pollution values
23
rent geometry structure of the intersection and
origin destination matrix for both the road section and the intersection studied.
As with other simulation programs and traffic
forecasting model after the modeling of the road
geometry or of the intersection, another step
is to proceed with the calibration, to create a
virtual model close to reality.
For the calibration of the road section and the
intersection there were used 36 inductive loops
that were used in the generation of the simulation model and then used to calculate the origin / destination matrix; the traffic flow that
was used in the simulation was based on the
Craiova Municipality traffic study. Simulating
this section aims to introduce a virtual adaptive traffic light system in comparison with the
existing system, a fixed, exceeded in all points
of view, both technologically and morally. For
this simulation we used a matrix origin / destination that has contains 41 points of origin
/ destination, a total of 9127 vehicles traveling
on this section during
an hours. To get a more
complete picture of the
chemical pollution from
the simulation the vehicles
were divided into 3 categories (light vehicles, taxis
and vans). Heavy vehicles
were not introduced in this
simulation because they
are restricted to the town.
Conclusions
Road traffic is characterized
by random phenomena and
the variables used to describe them are discrete or
continuous, which requires
the use of complicated
and complex mathFig. 7 The difference between the adaptive control and fix control,
on the estimated values for NOx
ematical approaches, so
specialized developed
programming environment are an effective alFig. 8 Forecasting ternative for planning, modeling and simulation
NOx type emission of traffic behavior. Considering input data, the
values of a road specific traffic characteristic parameters a model
section, comparing
can be created and simulated giving us solutions
fixed traffic light
programs with at comparative level (fixed control / adaptive
adaptive management control), resulting reports that allow road traffic
quantifying and hence chemical pollution.
In the research carried out for the two case
studies, the reduction of pollution for adaptive
management system on traffic intersections or
networks can be seen.
By modeling, simulation and verification of traffic solutions before their implementation, high
costs for solutions that ultimately may prove ineffective can be avoided and determine the optimal solution specific to the research done.
Fig. 9 Forecasting PM
type emission values
of a road section,
comparing fixed
traffic light programs
with adaptive
management
REFERENCES
[1] Dumitru, I., Trafic rutier. Aspecte aplicative, Editura Universitaria, Craiova, 2010;
[2] Fistung, D., Transporturi, teorie economică, ecologie, legislaţie, Editura All Beck, Bucureşti, 1999;
[3] Ostro, B., Estimating the healt effects of air pollution: a methodology with an application to Jakarta policy, WP 1301, World Bank, Washington DC, 1994;
[4] ***** Land transport NZ’s Economic evaluation
manual. Volume 1. Appendix 9 Vehicle emissions,
First Edition, Effective from 1 october 2006;
[5] ***** www.nzta.govt.nz
24
University Research
University „Politehnica” Bucharest / Power Engineering Faculty
Investigation of architectures and control strategies of hybrid propulsion systems for motor-vehicles.
Author: Ing. Andrei-Nicolae MACIAC
Scientific advisor: Prof .Dr. Ing. Gheorghe Frăţilă
Progress achieved in automotive engineering has allowed the
development of vehicles with outstanding energy performances and
low pollutant emissions. Further, there are stringent requirements for
reducing emissions of gases with greenhouse effect (CO2) which mainly
are directly proportional to fuel consumption.
In this sense, the electric car has remarkable performances, estimating to
be the most “cleanest” and with very good efficiency of the propulsion
system. But, until electrical energy storage devices will be developed
enough to enable their implementation for affordable electric cars, hybrid
cars are an intermediary step, representing various compromises between
electric cars and conventional cars, with internal combustion engine.
This PhD thesis details the current stage in hybrid electric propulsion
systems for vehicles, also showing the influence of their control strategies
on economic performance and comfort. The main objective of this thesis
is to develop complex models of hybrid systems that include also the
control modelling, for this purpose being developed new models for
some components of the hybrid system (hybrid vehicle controller, power
electronics, vehicle). Simulation studies have been performed on power
dimensioning of electric motor, fuel consumption, influence of electrical
system voltage on the dynamic and economic performances and also, on
considering the possibility of covering the torque gap while changing gear.
Measurements for validation of the mathematical models are based on an
experimental hybrid vehicle, developed under a national research project,
the author participating as a member of the research team.
This paper was prepared as a result of continuous and complex training
in the Automotive Department of the University POLITEHNICA of
Bucharest and the French company LMS Imagine, during a period of
training for AMESim simulation environment., energy exchange.
Modern drives using unconventional energy storage devices – hybrid electric vehicles
Author: Ing. Valerian Crooitorescu
Scientific advisor: Prof .Dr. Ing. Eugen Mihai Negruş
which requires further investigation. The batteries, as an important component of the hybrid system, require investigation of both their functional and
thermal behavior.
This thesis aims to present the functional and the thermal behavior of an
electric machine (SRM 8/6), of a transmission (Van Doorne CVT) and of
a battery package (Lithium) in order to study their respective energy flows
and the interaction between them. Their efficiency, as well as the global
efficiency for the hybrid powertrain will therefore be determined. Based on
thermal resistances, a thermal network was developed to compute internal
losses for different parts of these three components. Using simulation, the
components and their thermal models were integrated in a mock-up virtual
hybrid electric vehicle to study their behavior during a predefined driving
cycle.
In order to validate the mock-up vehicle, a real time simulation and testing
rig was used to evaluate and improve interaction of control systems on several levels, indicating interaction problems between several virtual and physical components during an early stage of the system development process.
2012 brings new European Union regulations concerning harmful emissions for road vehicles. The hybrid electric and electric mobility constitutes
a technology revolution for the automotive industry. In response to the
stringent regulations and requirements enforced, vehicle manufacturers
are developing new strategies, using hybrid electric or electric powertrain
solutions. In order to reach the goal of using alternative powertrain solutions, it is important to integrate different devices from the early stages and to
optimize their behavior. However, with a minimum of one electric machine, two different energy storage devices, and one transmission architecture,
a hybrid electric powertrain triggers more concerns surrounding energy
flows. During operation, there are energy losses caused by heat generation.
Generated heat, emphasized as losses, is having a negative impact on the
electric machine, batteries and transmission and, therefore affects the global propulsion system efficiency. Apart from the functional behavior of the
electric machine, which is the production of torque/rotational speed, it also Keywords: hybrid vehicle, electric motor, SRM, CVT, Van Doorne, Lithium
has a thermal behavior due to internal losses, which needs to be taken into batteries, thermal modeling, simulation, losses, real-time, test rig, integratiaccount. The transmission also has both a functional and thermal behavior, on, HIL, energy management
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25
Challenge KART LOW COST
A result of the cooperation between University of Piteşti, Automotive and Transports Department,
Romania and Université de Bourgogne, Institut Supérieur de l’Automobile et des Transports de Nevers, France
The event was organized under the patronage of Society of Automotive Engineers from
Romania (www.siar.ro), and was supported by
the Group Renault Romania.
The event was part of a series of festivities organized during this year at the University of
Pitesti, in order to celebrate its 50 years of existence.
The 2012 KLC edition was hosted on one of
Renault-Dacia’s test tracks near city of Pitesti,
Romania and was deployed on 18th of May
2012.
Within this edition, taking into account the current
orientation of the automotive industry, the organizers decided to introduce a new challenge: the
electric propulsion. Thus, two competitions took
place: one with thermal engine powered karts and
the other with electric motor powered karts.
University of Pitesti came with 3 thermal engine
powered karts and 1 electric kart, while ISAT de
Nevers had 2 thermal engine powered karts and 1
electric kart. The „thermal competition” was won
by ISAT de Nevers, while the „electric competition” was won by the University of Pitesti.
On the occasion of this event, the University of
Pitesti organized an exhibition showing its other
operational prototypes on sustainable mobility: a
hybrid Dacia Duster (Diesel propulsion on the front
axle and electric propulsion on rear axle) and a solar
vehicle.
Additional information:
Challenge Kart Low-Cost. What does it mean?
Developing of a kart over one academic year,
whose cost is not to exceed 2000 € (for thermal
26
ones) or 3000 € (for electric ones), aiming to
participating in May to a motor-sport academic
competition.
This project underlines the basic competences of
an engineer, such as:
Teamwork/organization of a team in such
way that deadlines are to be respected,
Capability to select engineering solutions,
having constraints of budget and time,
Ingeniousness, etc.
Therefore, it’s not just a simple go-karting race.
Equally, it’s a technological, educational and human challenge and the winner is not necessarily
the fastest!
Challenge Kart Low-Cost. For whom?
This competition, whose aim is to develop a socalled “low-cost” by multidisciplinary student
teams, is opened to anyone concerned by the automotive engineering
The students are gathered in teams and over one
academic year, they follow the development stages of a product, so that in the end the motor-sport
competition to be possible.
In 2011, the competition took place on a track
of the many presented on the former site of
France’s F1 Grand Prix at Magny-Cours (F-58)
and the competitors were: Institut Supérieur de
l’Automobile et des Transports de Nevers from
the University of Bourgogne (one team) and
University of Pitesti (two teams) - http://www.
upitmedia.ro/index.php/unctr/universitateadin-piteti-la-kart-low-cost-challenge.html
Challenge Kart Low-Cost. Goals
Learning/exercising of all stages of a product’s
development (design, manufacturing, etc)
Understanding the problems that occur from
the need to obtain an optimal operational product,
as a result of a coherent compromise, corresponding to precise technical specifications,
Encouraging the innovation by imposing of
a permissive technical regulation, leaving a great
freedom of design, thus allowing students the development and application of their ideas,
Development of a product, respecting the
constraints of budget and time,
Development of competing spirit amongst
students,
Encouraging students to seek out for complementary competences, allowing them to open
their minds, which is indispensable for the future
professional life,
Introduction of students in a frame which encourages reflection toward what the automotive
engineering really means and which allows opinions exchanges with people from different nationalities aiming also to create a cultural exchange.
Briefly, the goal of this competition is to prepare
future engineers for project management by developing the teamwork spirit, sharing responsibilities,
respecting deadlines and allocated budget; finally, it
aims to develop the synthesis and compromise capabilities in respect to the initial imposed constrains.
Challenge Kart Low-Cost. Project evaluation
Analysis of the expenses (≤ 2000 € - thermal
karts / 3000 € - electric karts),
Analysis of the kart’s body design,
Dynamic tests, allowing to evaluate the kart’s
dynamics as well as its acceleration,
Endurance test (60 laps) in order to analyze
the kart’s reliability.
Challenge Kart Low-Cost. 2013 edition
Following the discussions we had so far, the next
edition will be hosted by Universidad Politecnica
de Madrid, certainly with the support of STA.
It will be the third engineering school joining this
project: ISAT de Nevers, Université de Bourgogne,
France (SIA), Universitatea din Pitesti, Romania
(SIAR), Universidad Politecnica de Madrid,
Spain (STA).
More details at [email protected] and ernest.
[email protected]
Adrian CLENCI, Assoc. Prof. , Head of the Automotive
and Transports Department, University of Pitesti,
Romania, President of Society of Automotive
Engineers from Romania (SIAR)
auto test 3

Ingineria Automobilului Society of

Transcription

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