Ingineria Automobilului Society of

Ingineria
Automobilului
Romanian
Automobile
Register
Society of
Automotive
Engineers
of Romania
DISTR IBU TED WITH AU TOTEST MAG A ZINE
Vol. 7, no. 4 (29) / 2013
International Congress of the Society
of Automotive Engineers of Romania
Grand Hamster E4WD
DACIA Hybrid Concept Car
l Experimental Study of the Energy Efficiency of Cars l Simulations of a Compression
Ignition Engine Engine Powered by Different Fuel Blends when Changing Injection Parameters
SIAR IS AFFILIATED TO
INTERNATIONAL
FEDERATION OF
AUTOMOTIVE
ENGINEERING
SOCIETIES
EUROPEAN
AUTOMOBILE
ENGINEERS
COOPERATION
AUTOMOTIVE TRANSMISSIONS FUNDAMENTALS.
SELECTION DESIGN AND APPLICATION.
SECOND EDITION
Authors: Harald Naunheimer, Bernd Bertsche, Joachim Ryborz,
Wolfgang Novak
Publisher : Springer-Verlag Berlin Heidelberg
Published: 2004
ISBN: 978-3-642-16213-8
This book gives a full account of the development process for automotive
transmissions.
Main topics:
• Overview of the traffic-vehicle-transmission system
• Mediating the power flow in vehicles
• Selecting the ratios
• Vehicle transmission systems, basic design principles
• Typical designs of vehicle transmissions
• Layout and design of important components, e.g. gearshifting
mechanisms, moving-off elements, pumps, retarders
• Transmission control units
• Product development process
• Manufacturing technology of vehicle transmissions
• Reliability and testing
The book covers manual, automated manual and automatic transmissions as well as continuously variable transmissions
and hybrid drives for passenger cars and commercial vehicles. Furthermore, final drives, power take-offs and transfer
gearboxes for 4-WD-vehicles are considered.
ALTERNATIVE CARS IN THE 21ST CENTURY.
A NEW PERSONAL TRANSPORTATION PARADIGM.
SECOND EDITION
Author: Robert Q. Riley
Author: Robert Q. Riley
Publisher : SAE International
Published: 2004
ISBN: 0-7680-0874-3
Contents:
• Personal Mobility in Crisis
• Personal Mobility Vehicles for the 21st century
• The Technology of Fuel Economy
• Alternative Fuels
• Electric and Hybrid Vehicles
• Three-Wheel Cars with Tilting Three-Wheel Vehicle
Information
• Safety and Low-Mass Vehicles
• Intelligent Transportation Systems
• Alternative Cars in Europe
Ingineria Automobilului
Automobile Engineering versus Automotive Engineering
Ingineria Automobilelor versus Ingineria Autovehiculelor
C
ould be the Automobile Engineering one
of the open windows for the Romanian Automotive Engineering scientific research?
A sharper glance slices like a diamond shatters of
the inert, dusty window of the Romanian industry
and reveals a rather discouraging picture.
At the very foundation of the scientific research,
no matter the field, resides the specific social demand to innovating, up-to-dating, competing and
performing.
But for years, the Romanian Automotive Industry focuses almost exclusively on passenger cars. There is a good reason for it: former famous
factories (i.e. ROMAN, Tractorul, ARO) had diminished or ceased their
activities; next to them, powerful research and design institutions were
developing their activities.
Within this context, from the heights built-up by media, the Automobile Engineering looks downwards to its “poorer”, less spotlighted relatives. The scientific research developed by the decreased number of the university professors
and researcher that could provide some innovation for the truck, tractors, buses and special vehicles industry seems to be pointless. As a result, the interest in
developing / innovating / manufacturing this kind of vehicles or components
for these vehicles continuously decreased. Nevertheless, I believe that the scientific research within the Automotive Engineering field should pay attention
to the whole lifecycle (designing, manufacturing, using, maintaining, decommissioning and disassembling) to all the automotive categories.
I led the Military Vehicles and Transportation Department of the Military Technical Academy more than 10 years. During all this time I have
developed, along with my colleagues, a new concept, which we called
mobile terrestrial bearing platform for technical systems (PMT-PST). According to a systemic approach, it consists of a basic module, wheeled or
tracked propelled, on which different systems were mounted: weapon
systems (cannons, mortars, rocket launchers etc.), command and control
systems, radar installations, day-and-night surveillance systems, medical
evacuation systems (MEDEVAC), recovery and technical maintenance
systems, communication systems, assault vehicles and so on. These vehicles became, consequently, combat vehicles, mobile command nodes,
surveillance stations or different special vehicles. Moreover, they could be
armored or not and they could be fitted with personnel or goods transportation modules, able to perform within a modern warfare environment.
The activity of research-development-testing consisted of both the classic
approach of the wheeled or tracked vehicles’ designing, manufacturing
and maintenance, and the specific elements of the particular type of installed equipment (such as the weapon system’s stabilization, protection
against enemy fire, mobility and progression capacity in difficult conditions, unique fuel refueling, vehicle’s buoyancy, etc.).
The good results achieved in time were due, among others, to the excellent
co-operation with the remaining specialist of the former specialized industrial branches as well as with the other Technical Universities in Romania.
The previous given examples testify the fact that by reuniting the technical
capacities and the human resources, the Romanian research in this branch
of activity could significantly get involved in developing and innovating
various special vehicles or their components.
The existence of high level competencies in this filed within the Automotive
Departments of various Universities provides an important, but not enough
known and used resource by the Romanian specialized companies.
So, who takes the first step?
Professor Minu MTREA, Eng., PhD
Secretary General of SIAR
Former Head of the Military Vehicles and Transportation Department
of the Military Technical Academy
Summary „Ingineria Automobilului“ No. 29 (vol. 7, no. 4)
3
Automobile Engineering versus Automotive Engineer
Simularea funcţionării unui motor cu aprindere
Ingineria Automobilelor versus Ingineria Autovehiculelor
prin comprimare alimentat cu biocombustibili
5
International Congress of the Society of Automotive
Engineers of Romania – SIAR
în cazul modificării parametrilor de injecţie
Automotive Motor Mobility Ambient – AMMA 2013
15
High Order Spectral Analysis of a Measured Automotive Parameter
Congresul Internaţional al Societăţii Inginerilor de Automobile
Analiza spectrală de ordin superior a semnalului unei mărimi
din România – SIAR
mecanice măsurate în transmisia unui automobil. Modele
8
Experimental Study of the Energy Efficiency of Cars
Studiul experimental al eficienţei energetice
matematice obţinute prin identificare
a automobilelor
20
University Research: Symposium „EV&HV 2013 – Innovation in
12
Simulations of a Compression Ignition Engine Powered
Electric and Hybrid Mobility” Automotive Engineering
by Different Fuel Blends when Changing Injection Parameters
Research Centre, University of Piteşti. 1 november 2013
3
Ingineria Automobilului
ROMANIAN
AUTOMOBILE
REGISTER
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George-Adrian DINCĂ
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SIAR
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SOCIETY OF AUTOMOTIVE ENGINEERS OF ROMANIA
President: Conf. dr. ing. Adrian CLENCI, University of Piteşti
Honorary President: Prof. dr. ing. Eugen NEGRUŞ, University Politehnica of Bucharest
Vice-president: Prof. dr. ing. Cristian ANDREESCU, University Politehnica of Bucharest
Vice-president: Prof. dr. ing. Nicolae BURNETE, Technical University of Cluj-Napoca
Vice-president: Prof. dr. ing. Anghel CHIRU, University „Transilvania” of Braşov
Vice-president: Prof. dr. ing. Victor OŢĂT, University of Craiova
Vice-president: Prof. dr. ing. Ioan TABACU, University of Piteşti
General Secretary of SIAR: Prof. dr. ing. Minu MITREA, Military Technical Academy of Bucharest
SCIENTIFIC AND ADVISORY EDITORIAL BOARD
Prof. Dennis ASSANIS
University of Michigan, Michigan, USA
Prof. Rodica A. BĂRĂNESCU
University of Iilinois, Chicago College of
Engineering, USA
Eng. Eduard GOLOVATAI-SCHMIDT
Schaeffler AG & Co. KG Herzogenaurach,
Germany
Prof. Peter KUCHAR
University for Applied Sciences, Konstanz, Germany
Prof. Nicolae BURNETE
Technical University of Cluj-Napoca, Romania
Prof. Mircea OPREAN
University Politehnica of Bucharest, Romania
Prof. Giovanni CIPOLLA
Politecnico di Torino, Italy
Prof. Nicolae V. ORLANDEA
Retired Professor, University of Michigan Ann
Arbor, USA
Dr. Felice E. CORCIONE
Engines Institute, Naples, Italy
Prof. Georges DESCOMBES
Conservatoire National des Arts et Metiers de Paris,
France
Prof. Cedomir DUBOKA
University of Belgrade, Serbia
Prof. Pedro ESTEBAN
Institute for Applied Automotive Research,
Tarragona, Spain
Prof. Radu GAIGINSCHI
Technical University „Gheorghe Asachi” of Iaşi,
Romania
Prof. Berthold GRÜNWALD
Technical University of Darmstadt, Germany
Prof. Victor OŢĂT
University of Craiova, Romania
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. Cornel STAN
West Saxon University of Zwickau, Germany
Prof. Dinu TARAZA
Wayne State University, USA
HONORARY COMMITTEE OF SIAR
AVL List Romania – Werner MOSER
Romanian Automobile Register – RAR – George-Adrian DINCĂ
The National Union of Road Hauliers from Romania – UNTRR – Florian MIHUŢ
EDITORIAL BOARD
Editor in chief: Prof. Dr. -Ing. habil. Prof. E. h. Dr. h.c. Cornel STAN
Executive editor: Prof. dr. ing. Mircea OPREAN, University Politehnica of Bucharest
Deputy chief editor:
Prof. dr. ing. Gheorghe-Alexandru RADU, University „Transilvania” of Braşov
Prof. dr. ing. Ion COPAE, Military Technical Academy of Bucharest
Conf. dr. ing. Ştefan TABACU, University of Piteşti
Redactors:
Conf. dr. ing. Adrian SACHELARIE, University „Gheorghe Asachi” of Iaşi
Conf. dr. ing. Ilie DUMITRU, University of Craiova
S.l. dr. ing. Cristian COLDEA, Technical University of Cluj-Napoca
S.l. dr. ing. Marius BĂŢĂUŞ, University Politehnica of Bucharest
S.l. dr. ing. Gheorghe DRAGOMIR, University of Oradea
Editorial secretary: Prof. dr. ing. Minu MITREA, General Secretary of SIAR
Automotive Engineering: print edition publication, 2006 (ISSN 1842-4074), electronic edition, 2007 (ISSN 2284-5690).
New Series of the Journal of Automotive Engineers (RIA), printed in 1992-2000
4
Ingineria Automobilului
AUTOMOTIVE MOTOR MOBILITY AMBIENT – AMMA 2013
International Congress of the Society of Automotive
Engineers of Romania – SIAR
Congresul Internaţional al Societăţii Inginerilor de Automobile din
România – SIAR
Professor Eng.
Nicolae BURNETE
Ph. D., Congress President
Technical University of Cluj-Napoca
[email protected]
D
uring 17 to 19 October
2013, Alma Mater Napocensis, Technical University of Cluj-Napoca organized “Automotive Motor Mobility Ambient
– AMMA 2013” - International
Congress of Society of Automotive
Engineers of Romania – SIAR, under the high patronage of FISITA
(International Federation of Automotive Engineering Societies), accompanied by a suite of events that
focused the attention of Romanian
and foreign specialists in the field of
automotive engineering and road
transport.
The host of SIAR Congress was
for the third time Automotive and
Transport Department of the Technical University of Cluj-Napoca,
one of the poles of excellence in applied and fundamental research in
the automotive industry, with wide
recognition nationally and internationally.
All events centered around AMMA
International Congress in 2013
made ​​the city of Cluj-Napoca to
become, for a few days, an international center for automotive engineering, providing opportunities
for useful contacts and information
to date on the major issues of vehicle development and environment.
Mobility of ideas, goods and people characterize contemporary society, one of the main elements of
the future development of human
society and the automotive indus-
The opening festivity
try is an important factor in this
direction. Aware of the importance
of addressing current and future
issues that face the automotive engineering, the participants in the
International Congress AMMA
2013 and aims to address them,
discuss and formulate solutions
in an appropriate scientific framework, confirmed the presence of
a number of specialists academic,
economic and social, both in the
country and abroad.
Departments of interest AMMA
International Congress 2013 were
directly related to scientific research in the field of automotive
engineering, ideas, inventions and
new and emerging technologies
related to the following topics: hybrid and electric vehicles, advanced
propulsion systems, vehicle design,
advanced engineering and computer simulation, road safety and
traffic control, materials and innovative technologies, green vehicles
and pollution caused by internal
combustion engines.
The Congress provided an opportunity for all professionals in the
automotive and environmental en-
gineering (researchers, designers,
users and producers) to achieve a
fruitful exchange of views and to
contribute to the growth of education in these areas.
More than 275 participants at the
congress had the opportunity to be
actively involved in the scientific
papers presented in plenary and in
sections, workshops, exhibitions,
leisure.
AMMA 2013 opening of the
Congress brought in front of participants: Günter Hohl - FISITA
representative, former President
of the EAEC (European Coopera-
tion Automotive Engineers) Gigel
Paraschiv - Secretary of State, Ministry of National Education, Aurel
Vlaicu - Rector of the Technical
University of Cluj-Napoca, Horia Dorin Uioreanu - Cluj County
Council President Mihnea Ioraş
- Subprefect of Cluj Adrian Clenci
- President SIAR, Gheorghe-Alexandru Radu - Academy of Technical Sciences of Romania, Stefan
Kanya - regional Director Europe
- AVL List GmbH.
After the official opening of the
congress plenary session presentation took place.
Mr. Günter Hohl – presentation of the paper-work
5
Ingineria Automobilului
The first paper, presented in plenary
by Günter Hohl, entitled „FISITA
and the Automotive World“ started with an overview of FISITA,
putting into evidence the fact that
it represents more than 170,000
engineers worldwide, having an
important role innovation in the
automotive engineering, development of various industry standards
and the scientific support organization. SIAR members in that SIAR
is part of FISITA participate in the
global effort to develop engineering and road transport vehicles. Evolution of the autovehicle global production
FISITA and EAEC Congresses are
opportunities to show unity and
efforts of Automotive Engineers. It
was further shown an evolution of
vehicles, both international inventors and Romanian, remembering
the Belu Barbu, Dimitrie Leonida,
Aurel Persu and others, along with
changes in automotive production
in Romania.
It was stressed the important role
that the car industry has both the
European economy and the world
is said that this is the „engine of
Europe „. Also mentioned the fact
that although the number of com- Industrial orizontal areas with development induced by the evolution
of the romanian automobile industry
panies producing vehicles fell from
36 in 1970 to 15 in 2000 , increased
diversity of models (sedan, sports
car, SUV ... the pick -up, MPV,
hatchback, SW, coupe, roadster)
from 3-15, then recalled the target
in terms of environmental protection, namely a better air quality and
reduce vehicle noise. Automotive
future involving new technologies:
environmentally friendly electric
cars and interconnected and autonomous vehicles. In conclusion,
cars, buses and trucks will remain
the main option for the transport
of people and goods, will increase
environmental protection requirements, and educating the public on
the importance of environmentally
friendly transport will increase.
The opening of the exhibition
A second paper, presented in Parliament by George Druţă adviser ments and prospects for devel- industry is shaken marked „migraACAROM, entitled „The auto opment” said the comprehensive tions” Inter-zonal and hierarchy
industry in Romania, develop- development of the automotive changes. He was presented the evo6
lution of automobile production
worldwide, continuing with the
main pillars of the automotive industry in Romania: Dacia - Renault
and Ford Romania. After describing the evolution of sales of new
motor vehicles presented exports
of cars and vans and emphasized
that it supports both domestic
production and the entire national
economy. There was an overview
of the major automotive suppliers in Romania, emphasizing that
the top 20 suppliers/manufacturers globally, 13 produce auto parts
in Romania. Components sector
remains attractive and relatively
competitive in the Central -Eastern Europe. It highlighted the role
ACAROM programs to increase
competitiveness and opportunities
of a regional cluster, the work ending by presenting perspectives of
automotive industry in ACAROM
vision.
From AVL GmbH, Stefan Kania
presented „The connected powertrain TM”. After stressing that AVL
is the largest development, simulation and testing technology of
powetrain in the world (with 6,200
employees and a 12.5% investment in research and innovation)
were presented aims to develop
transmission and new concepts in
automotive engineering. Based on
a hybrid vehicle demonstration in
2004, with emissions of only 9098 g/km of CO, with a 1.2l engine
with 3 cylinders, developing 60
kW, since 2006 an optimized turbo-hybrid has been presented, also
the „connected vehicle” equipped
with the system of driving direction keeper, „smart cruise control”
and the concept of CONNECTED
POWERTRAIN TM. Also was presented control architecture and
changes to this system and AVL
system RANGE EXTENDER.
Cristian Nevzoreanu, Public Affairs
Director of Renault Technologie
Roumanie, presented the paper”
ROMANIA – A Competences
Center for Renault”.
Ingineria Automobilului
From the outset it was noted that
in the 14 years since is in Romania,
Renault has invested here 2 billion, has reached a total of 18,000
employees and performed 5.5 million hours of training, after who
pointed out that Romania is the
second country of „Renault Planet”.
It was emphasized that Renault is
present in Romania on long term,
with a full branch self development: design, engineering, testing,
industrialization, manufacturing,
international logistics, marketing,
after-sales.
Among the latest models that have
been launched are both new Logan
MCV - launched in May 2013 and
the new Duster - launched in September 2013.
It insisted on the presence of Renault Technologie Roumanie the
only automotive development
center in Eastern Europe and the
largest such center outside France’s
Renault. Also was presented the
Titu Technical Center, the various
types of possible tests, and testbeds of network equipment along
with test tracks and talked about
the production of the new Energy
TCe90 engine - codenamed H4Bt.
Finally, they were presented and
possible areas of youth development programs master engineers
dedicated <Automotive Projects
Engineering (IPA)>, conducted by
RTR in partnership with technical
universities in the country.
Simultaneously with the implementation and presentation of the
congress, companies and organizations with activities in the field of
automotive engineering, motor,
mobility and environment organized exhibition stands with specific
themes. Among the exhibitors were
found companies design and computer simulation in the automotive industry, turbochargers repair
specific components, importers
and distributors of automotive oils,
aerosols and specialty products, automotive repair, automotive maintenance products, fasteners, power
Images from the exhibition
tools and pneumatic, chemical,
hand tools specialized manufacturers of diesel injection systems,
automotive battery manufacturers,
suppliers of solutions for auto damage assessment etc.
Simultaneously with the implementation and presentation of the
congress, companies and organizations with activities in the field of
automotive engineering, motor,
mobility and environment organized exhibition stands with specific
themes. Among the exhibitors were
found companies design and computer simulation in the automotive industry, turbochargers repair
specific components, importers
and distributors of automotive oils,
aerosols and specialty products, au-
tomotive repair, automotive maintenance products, fasteners, power
tools and pneumatic, chemical,
hand tools specialized manufacturers of diesel injection systems,
automotive battery manufacturers,
suppliers of solutions for auto damage assessment etc.
The congress took place in 2013
AMMA while remaining specific
activities a number of themed
workshops to the students, young
researchers and professionals with
experience in the automotive and
maintenance products. Workshops
conducted during the congress had
the following main topics: Determining fuel consumption in real
operating conditions (Karl Kock
- AVL Graz Austria), Introducing
the application aided design Catia V6 (CENIT), Modern service
technologies (Autodiga).
In these workshops have explained
some basic concepts and specific
equipment used in the measurements, i.e. stands for experimental
tests.
Some of the equipment related to
determining fuel consumption in
real terms are installed directly on
the vehicle, being relatively easy
to install on motorcycles, cars and
trucks, allowing precise monitoring
of the operation of fuel supply and
exhaust gas systems. Were also recorded characteristic values of other auxiliary systems of the engine,
among which may be mentioned
cooling, lubrication, ignition and
starter. The whole process of doing
experimental research have specific
equipment installed on vehicles so
that they can be subjected to a test
protocol on the circuit characteristic, everyday traffic conditions,
respectively. Equipment this way
installed facilitated the fuel consumption determination both in
traffic and circuit.
Paper presentation within sections
of the AMMA 2013 was of great interest and assistance proved so numerous and the discussions continued after completion of exposure.
7
Ingineria Automobilului
Ingineria Automobilului
Experimental Study of the Energy Efficiency of Cars
Studiul experimental al eficienţei energetice a automobilelor
Eng.
Mihail IACOB
[email protected]
Eng.
George ENE
email: [email protected]
Eng.
Marian-Eduard
RĂDULESCU
email: [email protected]
Professor Eng.
Ion COPAE, Ph.D.
Military Technical Academy of
Bucharest,
email: [email protected]
ABSTRACT
The article presents the problem
of establishing energy efficiency of
cars, which considers both power
performance and fuel consumption
of their. Study is based on experimental data obtained from tests of
cars equipped with on-board computer and embedded transducers.
Nowadays, the car is one of representative mechatronic products,
an excellent example of integrating
software of mechanical, electronic
and informatics components. From
the beginning until today, the car
revolutionized transportation and
it concentrated the most significant
engineering effort to improve continuously its performance.
Among the main requirements,
which are imposed on cars, are also
those relating to their dynamics
and fuel saving; usually, these two
requirements can not be satisfied
simultaneously to the desired maximum level. In the specialty literature, the study of dynamics and fuel
saving is performed separately from
each other, without resorting to the
8
interconnections between them.
In the classic sense of the literature,
the references of dynamics belong
only start-up, typically the accelerator start-up time and space. Broadly
speaking, dynamics refers to the
whole movement, it only for the
fact that the dynamics represents
any variation in time.
Similarly, in the classic sense of the
literature, the references of fuel saving refer only to fuel consumption,
expressed in various forms. Broadly
speaking, we should question and
about other issues, for example
those relating to the use of fuel energy input for the engine efficiency,
for propulsion etc.
Lately, it puts more and more the
problem that refers at increasing
energy efficiency of a car, which
aims dynamics and fuel saving
interrelated each other [1, 2, 3].
In other words, it does not want a
high dynamic energy without con- ERFC criteria value is determined
sider the effort to get it; for this rea- by the relationship:
son, the main efforts are directed
towards improving economic effiCc − C r
ciency more than towards improv- ERFC =
(1)
Cc − C p
ing dynamics, obviously because
of the limited oil resources. This
effort is understandable, given that where: Cc - current fuel consumpthe car is a means of transport with tion, Cr – achieved fuel consumpvery low efficiency, wasting a lot of tion, Cp - potential fuel consumpenergy introduced with the fuel.
tion (possibly reduced).
Efforts aimed at improving energy For example, if we want to reduce
efficiency targets simultaneously fuel consumption in 2035 to 62.5%
fuel saving and dynamics, but in of the current value by sacrificing
one sense: lower fuel consumption dynamic performance by 50%, of
by affecting dynamics limits im- equation (1) is made of
​​ a relatively
posed. In this regard, recent stud- fuel consumption:
ies and research in this area operCr =
Cc − ERFC( Cc − C p ) =
1 − 0, 5(1 − 0, 6
ate with the concept called ERFC
(2)
(Emphasis on Reducing Fuel
Cr =
Cc − ERFC( Cc − C p ) =
1 − 0, 5(1 − 0, 625) =
0, 8125
Consumption)
with quantitative
expression that signifies what per- as can be noticed in figure 1 [1].
centage of dynamic performance As stated, the size ERFC is actuis sacrificed for fuel economy [1]. ally a criterion of energy efficiency
Fig.1. Consumption calculation by implementing criteria ERFC
8
Ingineria Automobilului
Fig.2. Forecast for 2035 to dynamic and fuel saving
Fig.3. Criterion for energy efficiency kc for operation with gasoline
because fuel economy is based primarily on reducing the dynamics of
the car.
In order not to affect drastically the
dynamics, the building companies
will have to improve manufacturing
technologies and to adopt new constructive measures. The experts in
the field believe that it will have a big
impact the weight of the car, meaning significantly reducing it. For
example, if it aims to achieve ERFC
value of 50% (Figure 1), the current
car must weigh with 10% less.
As a consequence to the above, in
Figure 2 presents the forecast for
the year 2035 on the dynamics
and fuel saving of a middle class
car based on the degree of implementation ERFC compared to the
current situation was targeted for
dynamic time starting from zero
speed to 100 km/h, and for economical fuel consumption per 100
km traveled by car [1].
Figure 2 shows that in 2035 the
dynamics decreases and fuel saving increases with increasing value
ERFC. If it will be not implemented ERFC 2035, the fuel saving of
the current remains the same and
the dynamics will be improved
mainly due to decreasing vehicle
mass.
In order to emphasize energy efficiency, some experimental researches were carried out with
a Skoda Octavia fitted with fuel
injection engine and with power
plant liquefied petroleum gas
(LPG), which covered most functional regimes encountered in nor-
mal operation with a movement
with a normal driving style. The
analyze of energy efficiency of the
car was based on experimental data
by defining and setting the criteria
for assessing the energy efficiency
by comparing it to the two fuels using the concept of equivalent energy efficiency; these criteria should
evaluate the use of quantitative
energy introduced with the fuel,
which are the consequences of this
use in terms of energetic plan and
which are the factors that influence
9
Ingineria Automobilului
the most energy efficiency.
The first criterion for calculation
the energy efficiency is the ratio of
Wcinenergy of the car and the
the kinetic
(3)
=
k
⋅ 100
c
energy
introduced with the fuel [3]:
Wi
where the two energies are determined by the following relations:
ma v
2
Wcin =
Ch Q2i S p
W
=
respectively:
i
V
Fig.4. Mean of tests energy efficiency criterion kc for operation with LPG
Fig.5. Fuel consumption per 100 kilometers on petrol and LPG operation
Fig.6. Average values/tests of energy efficiency criterion kws
10
(4)
(5)
In these expressions were noted:
ma – vehicle weight, Ch - hourly
fuel consumption of the engine,
Qi - lower heating value of the fuel,
Sp - space map, v [m/s], V [km/h] vehicle speed.
Figure 3a shows the results which
were obtained for 50 tests when
engine is running with gasoline. As
will be noted from Figure 3c, for
these all tests, 34.86% of the energy
input with the fuel is actually used
for driving the vehicle. The values​​
of this ratio vary in the range 25.33
÷ 40.73%.
Since equation (3) calls from the
kinetic energy of the car, which is
the effective displacement energy
consumed and the energy introduced with the fuel that is the most
Ingineria Automobilului
Two other criteria for the calculation of energy efficiency is the ratio
of the volumetric fuel consumption
and torque Me, respectively engine
power Pe:
=
k cm
Fig.7. Average values/tests of energy efficiency criteria kcm and kcp
important criterion in assessing the
energy efficiency; this criterion has
a dynamic component Wcin and a
fuel saving component Wi.
If it uses fuel consumption per 100
km, C100, then the equation (5) becomes:
Wi =
ρQi S p C100
100
(6)
where ρ is fuel density.
The equation (6) is useful when it
is desired that in the study of energy efficiency to consider the fuel
price P [lei/liter], not only the dynamic and fuel saving elements. As
noted, the equation (6) shows two
sizes which depend on fuel type, ρ
and Qi , both lower for LPG.
Figure 4 presents the results which
were obtained for 50 tests when the
engine is running on LPG. As will
be noted from Figure 4a, in all of
these samples 30.15% of the energy
input to the fuel is actually used
for move the vehicle, the value is
of 4.71% less than that of the value
when it is used the gasoline. Sample
values ​​of this ratio vary in the range
19.28 ÷ 37.87%.
Taking into account the price P,
density ρ and lower calorific power
Qi for these two fuels, then it gets an
average equivalent relation in the
case of LPG, as shown in Fig. 4b
and calculated with the formula:
Pb ρ g Qig
it. Under these conditions, fig.5a
(7) shows average values of
​​ equivalent
Pg ρ b Qib
consumption of LPG/tests and,
As shown, this time the car equiva- compared, in fig.5b gasoline conlent energy efficiency increases, sumption per 100 km driven.
meaning that the average value of As noted in figure 5a, equivalent to
all tests increased to 44.13%, ex- LPG consumption for the all tests
ceeding the 9.27% amount of gaso- is 7.7 litres/100 km, compared to
line (34.86%).
the value of consumption of 11.3
In equation (7) the index „b“ refers litres/100km during the experiat gasoline and subscript „g“ refers ments. In addition, it is noted that
at liquefied petroleum gas. This the two graphs equivalent to LPG
equation shows that LPG is favored consumption value is close to that
if we speak about price (Pb = 6.01 of gasoline consumption (7.4 lilei/liter; Pg = 2.85 lei/liter - on ex- tres/100 km), is only 4.1% higher.
periments) but it is disfavored if we The second criterion for calculaspeak about density (rb = 0.74 kg/ tion of energy efficiency is the ratio
liter; rg = 0.54 kg/liter) and lower of energy introduced with fuel and
calorific value (Qib = 47300 kJ/ space traveled by car:
kg; Qig = 45000 kJ/kg): as a result,
W
the first factor equivalent ratio ink ws = i
(9)
creases the ratio and the other two
Sp
decrease it.
In this regard, it should be noted the numerator resorting to the fuel
that if there is a LPG equivalent saving, and the denominator the
consumption, so consumption dynamics.
compared to gasoline. Equivalent Figure 6 presents kws ratio values ​​for
fuel consumption per 100 km is both fuels, from which it appears
calculated from an expression of that in the case of LPG to scroll
type (7):
through one kilometer is required
a fuel energy of 2.04 times higher
Pg ρ b Qib
C100 e = C100
(8) than gasoline for the all tests, in
Pb ρ g Qig
average. If in this case it is defined
which shows that the price of gas is a ratio kwse equivalent with gasoline
a factor that reduces the equivalent (Figure 6b), the energy requireconsumption, and the density and ments per unit distance is about 1.4
the lower calorific value increases higher than LPG.
k ce = k c
Cv
Cv
(10)
; k cp
=
Me
Pe
where Cv is the fuel consumption in milliliters (ml).
In Figure 7 are shown the average values ​​of the last two samples
for the calculation the energy efficiency criteria for both fuels.
The graphs on the left show that
the time to achieve a torque of 1
Nm is necessary a fuel volumetric
consumption for all tests volume
increased by 74.7% in the case of
LPG; if is relates to the gasoline,
the equivalent consumption is increased by 19.7% for LPG.
Similarly, the graphs on the right
show that in order to obtain a
power of 1 kW is necessary a fuel
volumetric consumption for all
tests increased by 58.4% in the case
of LPG; if it relates to the gasoline,
the equivalent consumption is increased by 46,4 % for LPG.
Similarly, other criteria which refer
at energy efficiency of the vehicle
were defined and it was examined
the influence of factors on them by
using the information theory.
The studies have shown that the
high equivalent energy efficiency
for LPG and the price which it is
much lower represent two arguments which lead to the conclusion
that it is more advantageous to use
LPG as fuel compared to gasoline.
BIBLIOGRAPHY
1. Bandivadekar A. and others. On
the Road in 2035. Report, Laboratory for Energy and the Environment,
Massachusetts Institute of Technology, 2008
2. Cheah H., Heywood J. Meeting
US passenger vehicle fuel economy
standards in 2016 and beyond. Energy Policy 39, 2011, pg. 454-466
3. Copae I., Lespezeanu I., Cazacu C.
Dinamica autovehiculelor. Publisher
ERICOM, Bucharest, 2006
11
Ingineria Automobilului
Ingineria Automobilului
Simulations of a Compression Ignition Engine Powered by
Different Fuel Blends when Changing Injection Parameters
Simularea funcţionării unui motor cu aprindere
prin comprimare alimentat cu biocombustibili în cazul
modificării parametrilor de injecţie
Eng.
Călin ICLODEAN
Technical University of
Cluj-Napoca
[email protected]
Professor Eng.
Nicolae BURNETE
Ph. D., Technical University
of Cluj-Napoca
[email protected]
ABSTRACT
This paper studied using computer
simulation the influence of parameters in the electronic control unit
ECU on the functional optimization of a compression ignited
engine Renault K9K fuelled with
bio fuels B10 and B20. To obtain
this objective a model in the AVL
Boost software has been made
for a compression ignited engine
that was implemented an element
ECU with fuel injection control
by loading the input maps on each
drive channel.
Following the computer simulations the optimization of fuel
injection was studied by ECU
parameters to obtain the same results from the combustion process
for each type of bio fuel.
Engine performance was evaluated based on the quantity of heat
released obtained from the combustion process in the cylinder to
compare with the properties of
mixtures of fuels used in the simulation. To increase the quantity
of heat released from the burning process was commissioned
by ECU parameters increasing
the quantity of fuel injected with
12
increasing the bio component by
enlarging the injection time.
INTRODUCTION
Studies and researches on the
operation of the compression
ignition engine in the optimum
economic pole provides opportunities to optimize energy parameters and therefore to achieve
aspirations about current fuel
consumption, pollutant emissions
and specific power in the process
of burning. Computer simulation
allows for optimal economic zone,
thereby constituting a fundamental step for the development of
simulation models underlying
data provision and strategies to
calibrate the motors perform best.
AVL Boost application is a suite
of simulation software tools with
which you can design, create, develop and study a large variety of
internal combustion engine. Preprocessing program used for
initial input data and the characteristics of the motor which will
be designed as a model for the
simulation. After assembling the
elements for the engine, mathematical equations and algorithms
of the model behind the Graphical
User Interface GUI analyze and
calculate the processes required
during the simulations. The pressures, temperatures and flow rates
are obtained from gas dynamics
equations and solutions are averages of the pipe cross-section [1].
THE MODEL USED IN
COMPUTER SIMULATION
PROCESS
Compression ignition engine Renault K9K is a turbocharged with
Common Rail, and the model built
in AVL Boost application is shown
in Figure 1.
The combustion model used in the
computer simulation was selected
Mixing Controlled Combustion
MCC model that determines the
quantity of heat release and pollutant emissions based on the
quantity of fuel in the cylinder and
the turbulent kinetic energy introduced of fuel injection. The implemented injection law was iRate, a
law that defines the injection by an
approximation based on the pul-
Fig. 1. The compression ignition engine Renault K9K in AVL Boost.
12
Ingineria Automobilului
Start of Injection
[°RAC]
Fuelling [mg]
Parameters
Flow Time
[kg/h]
Speed
[rot/min]
Minimum
Correction
Baseline
Map
Maximum
Correction
Minimum
Correction
Baseline
Map
Maximum
Correction
Minimum
Correction
Baseline
Map
Maximum
Correction
800
3.22
3.54
3.89
-5.00
-2.00
1.00
0.31
0.34
0.37
1000
3.25
3.58
3.94
-6.00
-3.00
0.00
0.39
0.43
0.47
1500
2.98
3.28
3.61
-9.00
-6.00
-3.00
0.54
0.59
0.65
2000
2.99
3.29
3.62
-9.50
-6.50
-3.50
0.72
0.79
0.87
2500
3000
3.12
2.95
3.43
3.25
3.77
3.58
-8.25
-6.25
-5.25
-3.25
-2.25
2.25
0.94
1.06
1.03
1.17
1.13
1.29
3500
2.99
3.29
3.62
-7.00
-4.00
-1.00
1.25
1.38
1.52
4000
3.07
3.38
3.72
-5.25
-2.25
1.47
1.62
1.78
4500
2.95
3.24
3.56
-8.25
-8.75
-5.75
-2.75
1.59
1.75
1.93
Table 1. Baseline Map and Correction Map of the Electronic Control Unit [4]
verized fuel flow through the injector per unit time slots. To do this,
in the equations for the calculation
of the law of injection the density
data, fuel injection time expressed
in crankshaft rotation angle at the
beginning and at the end of the
injection, and data on the amount
of fuel injected during the entire
duration of the injection has been
introduced [2].
The electronic control units ECU
introduced in the model used in
the computer simulation process
management aims injection on the
Baseline Map containing benchmarks for engine operation at
steady state values compared with
the signals provided the sensor and
the actuator output. Injection maps
for the building model are designed
to optimize injection parameters
controlled by the ECU to obtain
maximum power with low fuel
consumption and low emissions.
When these conditions are not
complied the ECU intervenes, and
corrects the required parameters
using correction maps to achieve
the results (Table 1).
THE RESULTS OF THE
SIMULATION PROCESS
To determine defining values for
the engine cycle computer simulations were made using diesel fuel
for the model built in AVL Boost
Fig. 3. Rate of Heat Released from the computer simulations.
Fig. 4. NOx emissions from the computer simulations.
13
Ingineria Automobilului
From the performed simulations
with mixtures of biofuel the heat
released from burning was decreased between 1.5% and 2% for
B10 biofuel blends, and between
2% and 2.5% for B20 biofuel
blends, because of the low calorific
value of the biofuel [4].
NOx emissions resulting from
computer simulations, increased in
proportion with the percentage of
oxygen in biofuel blends. Biofuel
used in computer simulations in the
engine generates an increase of NOx
emissions of up to 1.5% for B10 biofuel blends and 2.5% for B20 biofuel
blends. By increasing the quantity of
the injected fuel to change the injection parameters in order to increase
the quantity of heat released from
burning process the NOx emissions
increase in up to a value of 2% for
B10 biofuel blends, and up to 3% for
B20 biofuel blends.
CO emissions have decreased
by 2.5% when using B10 biofuel
blend, or 5% when using B20 biofuel blend due to oxygen content
and cetane number blend which
rises with the increasing concentration of biofuel in the blend. Research has shown a decrease of CO
emissions by up to 3.7% for B10
biofuel blends and up to the value
of 6.8% for B20 biofuel blends.
Fig. 5. CO emissions from the computer simulations.
Fig. 6. The Rate of Heat Released by changes of injection parameters.
Fig. 7. The NOx emissions by changes of injection parameters.
REFERENCES
Fig. 8. The CO emissions by changes of injection parameters.
application, and the simulations
were repeated using B10 biofuel,
respective B20 biofuel [3].
The engine performance was
evaluated based on the amount
of heat release obtained from the
combustion process in the cylinder to compare the properties of
mixtures of fuels used in the simulation. The conclusion was that
a bigger quantity of heat release
was obtained from the combustion process under conditions of
low concentration of biofuel in the
blend increased, because it has a
14
lower calorific value and a density
greater than diesel fuel. The evolution of maximum heat released by
the combustion process is shown in
Figure 3, NOx emissions in Figure
4 and CO emissions in Figure 5.
CHANGE OF INJECTION
PARAMETERS
The computer simulations followed the following logic: increasing the quantity of heat released
from burning. For this purpose, the
ECU simulation parameters have
been modified to inject a higher
quantity of fuel for greater percent-
age of biofuel concentration of the
mixture [2].
The simulation results during the
combustion for the maximum heat
release in the cylinder and emissions of NOx and CO generated
from the change of the injection
parameters are shown in Figures 6,
7 and 8.
CONCLUSIONS
Following the computer simulations it was found that B10 and
B20 biofuel blends with up to 98%
and 95% of the energy potential of
diesel fuel.
[1] AVL BOOST version 2011, Users Guide, AVL List GmbH, Graz,
Austria, Document no. 01.0104,
Edition 07.2011;
[2] Iclodean, C., Burnete, N., Computer Simulation of CI Engines
Fuelled with Biofuels by Modelling
Injection iRate Law, Research Journal of Agricultural Science, CNCSIS Clasa B+, No. 44 (1), 2012,
ISSN: 2066-1843;
[3] Burnete, N., ș.a., Motoare Diesel
și Biocombustibili pentru transportul urban, Editura Mediamira, ClujNapoca, 2008, ISBN: 978-973-713217-8;
[4] Iclodean, C., Burnete, N., Influence of the Electronic Control
Unit on Optimization Function of
the Compression Ignition Engines
Powered with Biofuels, IJE, CNCSIS Clasa B+, Tome XI, Fascicule 3,
2013, ISSN: 1584-2665.
Ingineria Automobilului
Ingineria Automobilului
High Order Spectral Analysis of a Measured
Automotive Parameter
Analiza spectrală de ordin superior a semnalului unei mărimi
mecanice măsurate în transmisia unui automobil.
Modele matematice obţinute prin identificare
Assoc. prof. Eng.
Marin MARINESCU
marin_s_marinescu @yahoo.com
Eng.
Marian TRUŢĂ
Military Technical Academy
of Bucharest
1. INTRODUCTION
The classic theory of a measured
mechanical amount generally
deals with fundamental statistic
amounts, such as average, dispersion, median value and so on. This
won’t lead to an intimate analysis
of the real phenomenon, since the
measured amount is considered
somehow to be rather quasi-constant. Although the spectral analysis, based on the Fourier Transform
provides some information about
the signal’s spectrum, it has been
proven to have a serious lack: it
considers the spectrum to be timesteady and the Fourier Transform
takes into account all the frequencies as being developed in the same
time. But in the real life, the spectra
are time-variable; they change from
one moment to another. Moreover,
the classic analysis can’t separate
the linear part of the signal from the
non-linear one.
Hence, along with the time-analysis, should be also applied a multispectral analysis, which is able to
separate the linear part from the
non-linear one and a time-frequency analysis that is able to offer valuable information about the time
variation of the signal’s spectra. In
15
this respect, fig. 1 depicts a normal
signal that has been achieved from
a tested vehicle. It represents the
torque acting on a transmission
shaft of a military vehicle. The signal was achieved as given in fig. 2.
2. DATA SELFCORRELATION IN THE
TIME ANALYSIS
To establish the confidence level Fig. 1. Test signal and classically modeled Fig. 2. Transducer mounting
of the measured data, a self-correlation analysis should be applied 3. SPECTRAL (FREQUENCY)
before anything else. Thus, if the ANALYSIS
self-correlation is poor, the signal The spectral analysis can be pershould be abandoned, since it is formed in a mono-spectral way or
not trustful. To perform this kind in a multi-spectral way as well. The
of analysis, the signal is previously first type is also called a Fourier
“cut into pieces”. Usually, the sig- analysis and it assigns the whole
nal is divided into two equal parts spectrum of frequencies to a single
Fig. 3. Self-correlation function
that are reciprocally compared us- moment of time. So, the spectrum of the signal
ing the self-correlation function as contains both the linear compogiven by:
nent and the non-linear one on the
same graphic. The multi-spectral
(4)
(1)
analysis is able to separate the non- is the amplitude of the signal that
where n is the number of the one linear part from the linear one and gives the amplitude of the spectra.
half of the data, xi is a certain val- the most used one is the bi-spectral In these equations x(t) is the signal
ue, h is the time-gap between two analysis.
in continuos time (the Fourier
consecutive values of the data vec- 3.1 Mono-spectral analysis
Transform can be also applied in
tor and m is the maximum allowed The most used spectra in this kind discrete time, as will be used in this
gap. Fig. 3 depicts the graph of the of analysis are the amplitude spec- case), f is the frequency and t is the
self-correlation function for the tra of the signal. To reach these continuos time. Of course, j = − 1
achieved signal. The signal theory spectra, the Fourier Transform is the imaginary number.
states that the two sides of the self- (that decomposes the signal) will Since the amplitude of the speccorrelation are rather symmetric be written, as:
trum depicts the values of the enand they have a slight tendency to
ergy that is dissipated on the cor(2)
zero, than the data are well self-cor
respondent frequencies, it means
related. The poorer the symmetry, that, using the real part and imagi- that on the frequencies that have
the more non-linear behavior. The nary part of the equation, can be high peaks, the system dissipates its
faster trend to zero, the poorer self- also be written as:
highest energies. So, these frequencorrelation. From the presented figcies are, somehow, characteristic
(3) and they will be either filtered (if
ure one can notice the data are well
correlated but the signal isn’t linear. where:
one knows them as coming from a
15
Ingineria Automobilului
Fig. 4. The amplitude spectra of
the signal
Fig. 6. Filtered signal
specific, identifiable noise) or taken
into account (if they are useful).
It is noticeable that the system dissipates energy on some frequencies that have high peaks. They
correspond to 3.2¸3.5 Hz, 7.5¸7.8
Hz and 14.6¸14.9 Hz. The question is: are these bands useful or
they belong to some specific noise?
During the tests, when preparing
the shaft for tests, the balancing
counterweights had to be removed,
so the shaft became unbalanced.
Considering the angular speed of
the engine, which was kept rather
constant, and also considering the
transmission ratios on the driveline
from the engine to the shaft, one
could notice that these frequencies
are noisy. Moreover, the second
and the third bands are integer mul-
tiples of the first one, which should
be considered as the base oscillation, while the others should be its
second and third order harmonics.
Hence, a filter had to be instated.
3.2 Used filter
Since the signal is discrete, a digital
filter is used. Many filters have been
analyzed and a Butterworth Infinite
Impulse Response filter has been
chosen. The filter’s order was stated
at six, value that came into being
starting from both the filter’s stability and computing time. Fig. 5 gives
the main characteristic features of
the mentioned filter.
Since there was no reliable information that the other two frequencies are indeed second order and
third order harmonics of the first
frequency, the same model of filter
was applied to the resulting signal,
after it was processed by the first filter. Nothing happened, the filtered
signal (from the first filter) was
completely overlapping on the genuine signal (the computed filtering
errors were lower than 3.25%);
hence, even filtering on the subsequent frequencies, no improvements occurred. That really means
the other two peaks belong to the
second and third order harmonics
of the first peak’s frequency.
In conclusion, applying the designed filter over the original signal on the stop-band frequency of
3.2¸3.5 Hz, the other two frequencies will be automatically eliminated, since they are nothing but
Fig. 5. IIR, Butterworth, sixth order, 3.2÷3.5 Hz, band-stop filter
16
superior order harmonics of the
mentioned frequency.
Using the coherence function,
the linear part could be separated
from the non-linear one. A view in
this respect is given by fig. 7 that
provides the separation of the linear part from the non-linear one;
both of them overlapped on the
genuine signal.
3.3 Multi-spectral analysis
Multi-spectral analysis assumes
the using of the cummulants. The
higher is the order of the cummulant, the higher will be the order of
the multi-spectral analysis. There
is one step between the order of
the analysis and the used cummulant. Thus, to perform a second order spectral analysis, a third order
cummulant will be used, as this
Fig. 7. Signal separation
paper reveals. So, the third order
cummulant is given in discrete
time, by:
(5)
where
is the averaging opera*
tor, x(n ), x (n ) are the signal and its
complex conjugate while k and r
are the used regressors; hence, the
bi-spectrum will be written as:
M {}
⋅
(6)
where f1 and f2 are the frequencies
of the linear and the non-linear
part respectively.
The images given in fig. 8 represent
the amplitude of the bi-spectrum
of the signal. For a better picturing, and to make the necessary
idea about the influence of the filter upon the non-linear part of the
Ingineria Automobilului
Fig. 8 The bi-spectrum of the signal. a - 2D bi-spectrum, non-filtered signal; b - 3D bi-spectrum, non-filtered signal; c - 2D bi-spectrum, filtered signal;
d - 3D bi-spectrum, filtered signal
signal, the upper part of the figure
contains the images of the bi-spectrum when applied to the genuine
signal. Consequently, the lower
part of the figure gives the images
of the same signal, but previously
filtered. One can notice that the
filtered signal has lost a lot of peaks
around the main one (in the middle of the diagrams). In the graphs,
fl and fn are the frequencies of the
linear and non-linear components,
respectively. So, the “busier” the
field of the 2D representation, the
more the non-linear component
is present in the signal. After filtering, the non-linear component
decreases in importance.
4. SYSTEM’S TIMEIDENTIFICATION
MATHEMATICAL MODEL
After processing the data, a mathematical model should be issued.
A method is to use the time-identification algorithms. The Theory of
Signals provides a wide range of algorithms, depending on a lot of factors. One of the most important is
the number of inputs and outputs.
The considered system has one input and one output, so it is SISO
(Single Input Single Output). To
get the model means to determine
the transfer function. An ARX
(Auto Regressive with eXogene inputs) model was considered in this
situation, given by:
(7)
where A and B are polynomials and
e is the error.
Applying this algorithm according
to its characteristics (given in fig.
9), the transfer function in discrete
time was obtained. Using a Z transform, the transfer function in continuos time was obtained; hence,
the differential equation that duplicates the real signal is given by
(8)
This is the wanted mathematical
model.
For a more suggestive view, fig. 9
gives, on the same diagram (upper left) the genuine signal (blue
curve) and the model’s one (red
curve). In green, there is the modeling error. One can notice that
the blue curve (genuine signal) is
almost completely covered by the
red one, so the model is excellent.
Moreover, the equation is stable,
according to its impulse response.
17
Ingineria Automobilului
Fig. 9. The features of the ARX mathematic model
5. SYSTEM’S FREQUENCYIDENTIFICATION
MATHEMATICAL MODEL
This method assumes the use of
the so-called regressor, of different
orders. A regressor is nothing else
but a history value of the signal.
Assume a discrete-time signal actual value as x(k) . It’s first order
regressor is x(k – 1) and so on. So,
the model is built up by the signal’s historical values and it works
as a prediction of the actual value
starting from its past one(s). So,
for a SISO system, using the first
order regressor, the equation describing the phenomenon, based
18
on the frequency-identification
algorithm, is given by:
(9)
where y(k) is the output and x(k)
is the input, in discrete time. Fig.
10 depicts the graphical representation of the already filtered genuine signal (blue curve), its mathematical model as obtained with
this method, and the modeling
error. As in the time-identification
method, the red curve overlaps
almost completely the blue one,
so the error is quite low. But there
is still a difference. Using only the
first order regressor, the error is
slightly bigger than in the previ-
Fig. 10. Results of the frequency-identification mathematical model
Ingineria Automobilului
Fig. 11. Born-Jordan
Transform
ous case. Of course, the regressor
order can be increased, but the
computing time will also increase
while the error won’t decrease significantly. Applying the algorithm
to the analyzed signal, the mathematical model is given by equation
(10). As expected, this equation
is using the discrete time (the actual value in the time-positioning
vector). Using specific methods,
it can be translated into continuos
time, but it is quite complicate.
Most of the time it is used just the
way it is now, in discrete time.
the spectral-temporal method.
From the very beginning should
be mentioned that this method is
a non-parametric one. Should a
parametric method be used, mathematical models with equations are
obtained. Should a non-parametric
method be used, only graphical
representations are obtained.
The most used transforms are the
bilinear ones. These transforms are
both in continuous time and discrete time. Most of them belong to
the so-called “Cohen class” that has
the general equation given by:
(10)
6. SYSTEM’S TIMEFREQUENCYIDENTIFICATION
MATHEMATICAL MODEL
Eventually, the last method to
achieve a mathematical model is
Fig. 12. Spectrogram
(11)
Of course, all the terms of the
above given general transform can
be explained, but this will take a lot
of room and time in this paper. So,
the representations will be more
suggestive.
Fig. 11 depicts the Born-Jordan,
discrete time transform. For a
better analysis, the signal and the
spectrum of the signal were also attached. The field of the transform
is providing the weight of the nonlinear component. So, the “emptier” the field, the less energy of the
non-linear component, so the less
importance in the signal it has.
Two more representations are used
to reveal the structure of the signal.
One of them is the spectrogram,
as depicted in fig. 12. It provides a
very good information about the
time evolution of the frequency
spectra of the signal. It was obtained by applying second power of
the Short Term Fourier Transform,
as given by equation (12):
(12)
Eventually, the results obtained by
the Stockwell Transform, as given
by equation (13), are depicted in
fig. 13. This transform is a sort of a
phase-corrected wavelet transform
and it is very good to be used whenever comes about revealing the
non-linear component of a signal.
(13)
which is also, very complex in its
expression.
7. CONCLUSIONS
The classic analysis of a signal, which
is eventually the time history of a
mechanical amount, measured by
electrical means, doesn’t provide
intimate information about its be-
havior. Using the new techniques of
time, frequency and time-frequency
analysis, one can get more specific
information about the evolution
of that specific amount. Moreover,
these techniques are able to provide
high-reliable mathematical models
for the measured amount. A new
perspective is therefore open and
the mechanical phenomena can be
better interpreted.
REFERENCES
[1] Bitmead, R. - Modeling and Identification for Control - University of
California, Berkeley, 1999
[2] Ilie, C.O., Marinescu, M., Oloeriu, F. - Getting a mathematical
model of the vehicle’s dynamics using
regressions - Second international
congress automotive, safety and
environment, SMAT 2008, 23-25
October, 2008 Craiova, Romania,
ISBN 978-606-510-253-8, ISBN
978-606-510-245-3
[3] Longin Iacobescu, Ioan Filip,
Marin Marinescu - Rezolvarea unor
probleme care apar in procesarea
datelor experimentale. Filtrarea software a semnalelor - The 32nd International Scientific Conference of
the Military Technical Academy
„Modern Technologies in the 21st
Century”, Bucharest, 1-2 November
2007
[4] Marinescu, M., Vilău, R., Mitrea
M. - Mechanical faults identification
using spectral analysis of a measured
signal - ESFA 2009, November 1214, Bucharest, ISSN 2067-1083
[5] Marinescu, M. - The importance
of filtering the signals of the measured
mechanical amounts - MTA Review
nr. 1/2010, Bucureşti, pp. 7-14,
ISSN 1843-339
[6] Marinescu, M., Vilău, R., Truţă,
M., Fieraru, O. - A method to obtain
a generalized model of the pressure
evolution within the braking system
of a vehicle - International Journal of
Modern Manufacturing Technologies, ISSN 2067-3604
[7] Marinescu, M. - Parametric
(polynomial) method to issue a mathematical model starting from a measured signal of a mechanical amount
- The 6th International Conference
„New challenges in the field of
military sciences 2009” 18 – 19 November, 2009, Budapest, Hungary,
ISBN 978-963-87706-6-0
[8] *** Signal Processing Toolbox,
http://mathworks.com
[9] *** Frequency Selective Filters.
2001
[10] *** Filter Design using MATLAB’s remez. 2001
Fig. 13. Signal (red curve) and Stockwell Transform
19
Ingineria Automobilului
Ingineria Automobilului
University Research
Cercetare Universitară
Symposium „EV&HV 2013 – Innovation in electric and hybrid mobility”
Automotive Engineering Research Centre, University of Piteşti. 1 november 2013
Simpozionul „EV&HV 2013 – Inovare în Mobilitatea Electrică şi Hibridă”
Centrul de cercetare „Ingineria Automobilului”, Universitatea din Piteşti. 1 noiembrie 2013
Assoc. Prof. Ph D. Eng.
Dănuţ Gabriel
Marinescu
Executive Director - Research Center
„Automotive Engineering”
University of Pitesti
The Research Center „ Automotive
Engineering „ within the University
of Pitesti organized on November
1, 2013 the second edition of the
National Symposium „ EV & HV
- Innovation in hybrid and electric
mobility”.
The event was held under the patronage of the Society of Automotive Engineers of Romania - SIAR
and brought together experts from
the economic environment, research institutes and universities,
with interests in electric and hybrid
mobility .
Opening the symposium , the
speakers Prof.PhD.eng. Ion Tabacu - Director of the Research
Center „ Automotive Engineering”, Prof.PhD.eng. Sebastian
Pârlac – Vice-rector of the University of Pitesti and engineer
Cristian Liviu Popescu - Manager
of Innovation Projects within the
Renault Technologie Roumanie
, highlighted the need to develop
the cooperation between the academic and economic environment
in the domain of green vehicles .
Within the symposium there have
addressed both aspects of design
and construction of the electric
and hybrid vehicles and the work
of the research teams in the fields
of electro- mobility and renewable
energies.
This year, the event „EV & HV
2013” has broadened its thematic
20
area by including the domain of
hybrid propulsion of thermal-hydraulic type.
There were presented the following
papers:
• Comparison between a thermal/
electrical vehicle from physical client equirements point of view - Ioan
Teleagă, Cristian Liviu Popescu Renault Technologie Roumanie;
• Schneider Electric solutions for the
electric vehicle charging infrastructure
- Vlad Rovo, Petre Butu - Schneider
Electric Romania;
• Toyota HSD - Hybrid Synergy
Drive - Bogdan Dumitrescu - TOYOTA Pitesti;
• Determination of motion power and of the running efficiency
of an electric vehicle - Aurelian
Crăciunescu , Leonard Melcescu
and Adrian Baltateanu - Polytechnic University of Bucharest;
• Hybrid electric car. Present and
perspectives for the ICSI Râmnicu
Vâlcea - Adrian Enache, Michael
Culcer - National Research & De-
velopment Institute for Cryogenics
and Isotopic Technologies - ICSI
Râmnicu Vâlcea;
• Elastic wave propagation in functionally graded materials - Erol Senocak, collaborator of the Univer20
Ingineria Automobilului
of Pitesti – the EcoLOGIC program
2002-2013 - Danut Gabriel Marinescu - University of Pitesti.
The exhibition organized on this
occasion hosted a series of electric
and hybrid vehicles: Toyota Prius
Plug-in - presented by Toyota Pitesti, the concept of electric vehicle
with autonomy range extension using the fuel cell - presented by ICSI
Râmnicu Vâlcea for the first time
at such events within the academia
environment and the latest Renault
ZE electric vehicles - presented by
sity of Pitesti;
SCHAFFLER
Romania; the Renault engineering center of
• Hydraulic Hybrid System for the auto- • Contribution to the promotion of Romania.
motive propulsion - Horia Abăitancei electromobility within the University University of Pitesti presented two
of the achievements of teachers
and students teams in 2011-2013:
KartEL - the electric propulsion
kart developed with Alseca SRL
funding and SOLARom – the solar
vehicle developed with EFES SRL
funding.
KartEL won the first place in the
„electric drive” section of the international competition Challenge
Kart Low-Cost, held in 2012 on
the Renault - Dacia testing slopes
at Merişani - Arges, and at Nevers
- France in 2013.
They were also exposed to the concepts realized in the „Alternative
Propulsion Systems for Cars - Alternative and Renewable Energies”
laboratory within the ECOLogic
program during 2002-2013: Dacia
ELECTRA - an electric vehicle built
on Dacia Logan platform, Dacia
GRAND SANDERO Hybrid UtilityVehicle – a LPG ​​- Electric hybrid
vehicle built on Dacia Logan MCV
platform, Dacia HAMSTER a diesel-electric hybrid vehicle built on
the Dacia Sandero platform and the
functional model Grand Hamster
Electricway 4WD – a diesel -electric
hybrid vehicle (Plug-in) built on
the Dacia Duster platform.
Starting this year, the symposium
„EV&HV” has a „junior” formula
with an educational role , especially
dedicated to students. The first edition of „EV&HV - Junior” was held
in early June 2013 in collaboration
with Renault Technologie Roumanie .
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