Mission profile on Power Electronics Reliability
Transcription
Mission profile on Power Electronics Reliability
Mission profile on Power Electronics Reliability - importance, analysis & testing Peter de Place Rimmen, Ke Ma, Huai Wang Center of Reliable Power Electronics (CORPE), Aalborg University, Denmark Danfoss Power Electronics, Denmark [email protected], [email protected], [email protected] www.corpe.et.aau.dk CORPE Schedule of the Tutorial ■ Importance of missions profiles on reliability – industry perspective (approx. 20-25 min) - Overview of the involved parameters for specifying reliability. - The role of mission profiles in product development. - Variation in the user profiles from automotive to solar. - Paradigm shift in reliability research in power electronics. ■ Reliability analysis based on mission profiles (approx. 25 min) - Flows and structure for reliability analysis considering mission profiles - Mission profiles translation and mapping under multi-time-scales - Case study on lifetime prediction in wind power application ■ Testing of power electronic components and design for parameter variations (approx. 25 min) - Thermal cycling and power cycling testing of IGBT modules - Degradation testing of film capacitors under humidity conditions - Design for parameter variations of IGBT modules in Photovoltaic inverters CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 2 Part 1 Importance of missions profiles on reliability – industry perspective Peter de Place Rimmen Overview of the involved parameters for specifying reliability. The role of mission profiles in product development. Variation in the user profiles from automotive to solar. Paradigm shift in reliability research in power electronics. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 3 Mission profiles Why Mission Profile is important! 4 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Source: SAE, J1879 Robustness Validation Standard ZVEI, Handbook for Robustness Validation of Automotive Electrical/electronic Modules The Mission Profile is a representation of all all relevant relevant conditions a product will be exposed to in all all of of its its conditions intendedapplications applications throughout its entire entirelife lifecycle. cycle intended Design for Robustness and Lifetime Customer Wishes [CRS] Product-Performance Specification [PRS] Link Application Mission Profile [PRS] Link Q Customer & Brand Safety Quality Target [PRS] Link Next Existing knowledge / Design for Reliability “Tool box” Link Design for Robustness and Life Integrated Product Development Design for Safety will in the future consider degradation “End of Life Risk”. Weakness Ref: Larry Edson Validations for Standards Approval / Safety Demands Risk evaluations: 5 | Reliability Engineering 07/10/2015 Robustness, lifetime & degradation has impact on Safety Quality monitoring & Risk mining in project Tutorial ESREF 2015 Link Link Integrated Product Development Process shall secure the designed functions are unaffected to the environment and user-profile in the whole expected lifetime. Together with the Mechanicaland Electronics-Designers Reliability Eng. makes guidelines for how to implement needed immunity to secure sufficient Robustness and Lifetime. Weakness Analysis Phase • What technology fit to the PRS • • • • • (Product Requirement Specification)? Ref: Larry Edson What’s new in the Requirements? Lesson learned from previous product Establish the knowledge to achieve targets Establish design budgets High level simulation on system Development Phase [Qualitative test] • Simulate or test for robustness at degraded Validation Phase [Quantitative test] components to the Mission profiles. • Accelerated lifetime test • Highly Accelerated Limit Testing (HALT) • 3th part approval test philosophy used. • Calibrated Accelerates Life Test (CALT) Other related activities: • Detailed simulations on • Logistics PPAP closed (Production Part Approval Process) functions/subsystems/system • Produce ability proved 6 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Customer Wishes [*CRS] Product-Performance Specification [PRS] Such parameter will describe what kind of functions the product can do examples like: • Km/Liter • Interfaces • Speed • In-/Out-puts • Efficiency • Resolution • Noise level • Storage • Voltage in or output • Control functions • Frequencies • Friction • Load • Power • Capacity • • Sensitivity • • Color • • Surface *CRS = Customer Requirement Specification. 7 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Application Mission Profile [*PRS] Such parameter will describe the stresses the product/component will experience from production, operation to end of life examples like: Environmental: User profiles: • Temperature Max/Min • On/Off periods • Thermal stress • Load profiles • Vibration • Relocations • Shock/Bump • Grid used • Humidity • Load used • Chemicals • Stop and go • Sun • Maintenance • Lightning • Hot plug • EMC/Spikes • Altitude 8 | Reliability Engineering 07/10/2015 *PRS = Product Requirement Specification. Tutorial ESREF 2015 Q Customer & Brand Quality Target [*PRS] Such parameter will describe the availability with confidence for the product during the whole life as overall targets like: Product: • First pass yield Q Product Target breakdown to Availability at: • Functions • Delivery • Modules • Warranty 2 - ? years • Components • Lifetime ? – 20 years • Safety The operational way will in many cases be focusing on why the product is outside specification and failing to operate! *PRS = Product Requirement Specification. 9 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Explain “end of life” performance target on Robustness and Life focus Examples: Component Robustness to Lifetime iaw Degradation budget Fan with focus on performance capacity. Failure criteria defined. Variation to: • power • Temperature • Humidity • Dirt • Vibration • ice 2000 meters above sea level 25% degradation of heat sink surface 30% degradation of fans Electronics, bearing, Gaskets with focus on tightness. Failure criteria defined. Can it be mounted without being damaged? Robust to: • Chemicals • Tools • Handlings Sufficient tight at end of life. • Flexibility /stiffness • Pressure to surfaces • Water tight iaw specification Electrolyte Capacitor with focus on: • capacity • ESR • leakage current Failure criteria defined. Component or circuit are Robust to: • Initial Volt • I leak variation • Temperature • Shock & Vibration Based on vendor specs and variation we will simulate when failure criteria are reached for the component or circuit. 10 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Validate Robustness to interaction in life time Interaction focus Such validations test shall prove that the product are able to survive the specified lifetime in the specified different environments. “More than 10 units are going through the same test-legs without failing in accelerated test. This is called Quantitative tests”. In the shown example 36 units used in 6 different test-sequence. Such test will be important in the future to make sure that the customer not will be the first to see unexpected failure mechanism. Ref: Larry Edson 11 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Existing knowledge / Design for Reliability “The Tool box” The Tool box consist of a lot of different tools. Tool boxes • Reactive tools. • Field analysis (*MCF) • Root Course Analysis Source: Reliasoft. Proactive tools • Kinematics • Simulation • Derating • FMEA • DoE (Design of Experience) • Gauge R&R / MSA • Target setting (*MCF-model) • Budgeting Design For Six Sigma is a basis for Design for Reliability but do not in itself guarantee compliance to reliability targets. *MCF = Mean Cumulative Function 12 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Design for Reliability approach Customer Requirements Specification Customer Requirements Specification ”Performance shall be specified as end of lifetime” Product “Design” Requirements Specification The Rimmen model 13 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Design for Reliability approach Identifying The Severe User (GM‐term) Some applications have small load variations (PR) Usage of a product varies because people or environments vary Some people/environments will be “easy” on the product, and some will be “hard” on the product We statistically quantify the severe user by statistically extrapolating the usage pattern from a sample of people Six to twenty “users” are monitored for a period of time and then extrapolated out to “one life”. A Weibull analysis is performed on the points of intersection at “one life.” Derived Requirement (typically 99.8%) Sampling period 14 | Reliability Engineering 07/10/2015 Time Tutorial ESREF 2015 One Design Life Extrapolation To One Life 10 Yrs. Most Severe User Observed In Our Small Sample Larry G. Edson / GM / 2006 Number Of Times A Product Is Used Or The Level Of Force Applied “Severe User” Design for Reliability Mission Profile Stress Italian 15 | Reliability Engineering 07/10/2015 Example for small variation: • Solar/Turbine • Site, Same location • Optimized • All severe users • Continued monitoring Density Density Example for big variation: • Car drivers/customers • Young/old (Users) • New/practiced • Alone/together • Stressed/relaxed • Busy/Sunday Strength North Sea Sweden Tutorial ESREF 2015 Stress Strength Mid. Europe Design for Reliability approach The Rimmen model Performance Customer Requirement Specification Product “Design” Requirements Specification 16 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Design for Reliability approach The Rimmen model Performance Customer Requirement Specification Product “Design” Requirements Specification This is the areas which can be used for Accelerated Reliability Validating Testing 17 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Development Phase [Qualitative test] Failure intensity: h(t)/year The “Bath tube curve” is: F I T F I T F I T F I T F I T Product age in service [years] Linear scale) If FIT is the speed of failures, then all the FIT’s values are correct. But what does it tell you? 18 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 The “Bath tube curve” is: Intuitively good FIT-values from supplier are usually an result from quantitative tests. (No failure observed) You can use the models to calculate a failure level, but is the result realistic? Automotive can produce component with a failure free period. It does not fit to FIT. Handbooks do not reflect the component quality we see today. Handbooks are based on field failures and in many time not root course analysed Handbooks cannot be up to date with the newest technology The components might be much much better than described in the handbooks. Risk information/indicator Physics of Failures are not considered “FIT” does not support Robust Design FIT or MTBF says nothing of the components limitations (Robustness or Lifetime) only that there were no failure found during the test conditions. FIT is not an “excuse” for the failures 19 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 F I T F I T F I T F I T You should ask your component manufacture for the expected lifetime (η, β & Confidence) under the stresses (Mission Profile) as the component will be exposed to Failure intensity: h(t)/year [%] Failed product = f(Warranty Period) [Statically without replacement] Failure intensity [h(t)/year] "not very useful" Product age in service [years] Linear scale) 20 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? From “Bath tub” (Failure intensity curve) Failure intensity: h(t)/year [%] Failed product = f(Warranty Period) [Statically without replacement] Failure intensity [h(t)/year] "not very useful" Product age in service [years] Linear scale) 21 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? From “Bath tub” (Failure intensity curve) via integration to Failed product = f(Warranty Period) [Statically without replacement] Mean Cumulative Functions [%] Lack of Customer Satisfaction Product age in service [years] Linear scale) Goal: “Failure Free Period” 22 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? We must work for a “failure free period” We must control the degradation, the wear out. Failed product = f(Warranty Period) [Statically without replacement] Mean Cumulative Functions [%] Lack of Installation‐ & Transport‐robustness [0‐Time failure level] Lack of Customer Satisfaction Some of the tools that influence “Dead on Arrival”: • Design for transport • Design for installation • Instructions etc. Product age in service [years] Linear scale) 23 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? Dead on Arrival or Zero times failures: Mean Cumulative Functions [%] Failed product = f(Warranty Period) [Statically without replacement] Lack of Installation‐ & Transport‐robustness [0‐Time failure level] Some of the tools and parameters that influence Process & Component Failures: Lack of Production Capabilities [Early failures] • Design For Manufacturing • Capability (Six Sigma-philosophy) Lack of Customer Satisfaction • Statistic Process Control • Tolerance Chain Analysis (statistic) • Contaminants • Poka Yoke • Taguchi / DoE • Etc. Product age in service [years] Linear scale) 24 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? Early failures due to low Cpk or Cpp in the whole supply chain Mean Cumulative Functions [%] Failed product = f(Warranty Period) [Statically without replacement] Some of the Lack of Installation‐ & Transport‐robustness [0‐Time failure level] tools and parameters that influence Robustness: Lack of design robustness [statistically constant] • Load/Strength, Derating & Margin • Robustness Lack of Production Capabilities [Early failures] • Thermal design Lack of Customer Satisfaction • Design Maturity • DFMEA • Reviews • Six Sigma • Etc. Product age in service [years] Linear scale) 25 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? Lack of design Robustness against “hard” and unforeseen load. Failed product = f(Warranty Period) [Statically without replacement] Lack of Installation‐ & Transport‐robustness [0‐Time failure level] Mean Cumulative Functions [%] Lack of design robustness [statistically constant] Lack of Production Capabilities [Early failures] Lack of Lifetime [wear out] Lack of Customer Satisfaction Product age in service [years] Linear scale) 26 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? Lack of design Lifetime. Degradations and wear out. Mean Cumulative Functions [%] Failed product = f(Warranty Period) [ Statically without replacement] Some of the tools and parameters that influence the designed Lack of Installation‐ & Transport‐robustness [0‐Time failure level] lifetime: Lack of design robustness [statistically constant] • Thermal stress • Thermal design Lack of Production Capabilities [Early failures] • Corrosion Lack of Lifetime [wear out] • Load/Strength, De-rating & Margin Lack of Customer Satisfaction • DFMEA • Six Sigma • Robustness • Etc. Product age in service [years] Linear scale) Goal: “Failure Free Period” One Design Life 27 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Which kind of failures do you not want? Lack of design Lifetime. Degradations and wear out. Which kind of failures do you not want? Early failures Lack of Robustness failures Wear out [lin] M(t) • Noise • Overload • … Lifetime 28 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 [lin] Mission profiles – Outdoor environment Climatic data has been downloaded from 560 weather stations in Europe. Data is analysed and provides input to design specification. STN ==== EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW EBAW Similar data is available from specific locations in US and Asia. Station code Place EBAW EBAW Antwerp/Deurne TIME TMP DEW DD/HHMM C C ======= === === 01-01-2008 00:20 4 3 01-01-2008 01:20 3 3 01-01-2008 02:20 4 3 01-01-2008 03:20 4 3 01-01-2008 04:20 4 3 01-01-2008 05:20 5 4 01-01-2008 06:20 4 4 01-01-2008 07:20 4 3 01-01-2008 08:20 4 4 01-01-2008 09:20 4 4 01-01-2008 10:20 5 4 01-01-2008 11:20 5 3 01-01-2008 12:20 5 3 01-01-2008 13:20 5 3 Arrhenius Average Average Accumulated temp Total humidity Coffin-Manson Total Hours Max Min temp temp Max MIN Average humidity Average Total operating hours Hours hours Parameter Hum dew temp temp 2008 2009 humidity humidity 2008 humidity 2009 17.543,5 5.697,7 49.747,1 40.598,0 876,6 33,0 -14,0 11,1 11,3 100,0 21,0 77,5 75,7 RH Total Acum % #### #### === hourstemp 93 1 1 100 1 0,1 93 1 0,1 93 1 0,1 93 1 0,1 93 1 0,1 100 1 0,1 93 1 0,1 100 1 0,1 100 1 0,1 93 1 0,1 87 1 0,1 87 1 0,1 87 1 0,1 NPL= Dark Green Contry Belgium Delta t stress pr day 7,452463 EBBE EBBE Beauvechain 17.544,0 5.501,2 49.964,3 31.982,5 4,3 34,0 -14,0 10,7 10,8 100,0 25,0 78,4 76,6 Belgium EBBL EBBL Kleine-Brogel 17.543,5 5.620,2 52.105,7 64.860,5 380,1 37,0 -19,0 10,4 11,3 100,0 19,0 79,7 78,7 Belgium 9,419712 EBBR EBBR Brussels National 17.543,5 5.431,6 49.751,6 38.676,5 804,2 34,0 -14,0 10,6 10,9 100,0 24,0 77,5 76,5 Belgium 7,273963 6,614508 EBCI EBCI Charleroi/Gosselies 17.543,5 5.261,9 49.707,7 36.224,5 571,6 34,0 -15,0 10,2 10,6 100,0 19,0 79,0 75,8 Belgium 7,039612 EBCV EBCV Chievres Ab 17.543,0 5.272,2 57.181,1 32.701,5 0,0 32,0 -14,0 10,4 8,6 100,0 23,0 79,5 82,4 Belgium 6,688635 7,209031 EBDT EBDT Schaffen 17.543,0 5.637,0 49.990,1 37.988,0 0,0 36,0 -14,0 10,8 11,1 100,0 11,0 77,7 76,5 Belgium EBFN EBFN Koksijde 17.542,5 5.229,0 54.914,6 33.688,0 317,8 32,0 -10,0 10,5 11,4 100,0 28,0 79,2 81,0 Belgium 6,78887 EBFS EBFS Florennes 17.543,5 4.932,0 51.889,8 31.434,5 176,9 33,0 -14,0 9,5 10,5 100,0 17,0 80,2 79,5 Belgium 6,557688 7,991307 EBLB EBLB Elsenborn 17.523,0 4.060,4 51.463,4 46.626,5 0,0 30,0 -21,0 7,3 7,6 100,0 12,0 83,5 84,0 Belgium EBLG EBLG Bierset/Liege 17.543,5 5.366,6 49.261,4 31.681,0 467,1 34,0 -15,0 10,3 10,8 100,0 22,0 78,2 75,5 Belgium 6,58335 EBOS EBOS Oostende 17.543,5 5.067,1 53.345,5 32.160,5 1.220,9 31,0 -10,0 10,4 10,4 100,0 17,0 79,7 79,2 Belgium 6,632983 EDAH EDAH Heringsdorf 10.185,0 2.709,4 26.921,2 8.104,5 60,5 29,0 -13,0 11,3 4,7 100,0 25,0 74,9 91,9 Germany 4,370068 Ref. Peter de Place Rimmen patent: Monitoring device usage and stress EP 2631598 A1 and Ref. EPE 2015 ECCE :S. K. Chaudhary, P. Ghimire, F. Blaabjerg, P. B. Thøgersen, P. de P. Rimmen Development of Field Data Logger for Recording Mission Profile of Power Converters 29 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Temperature Temperature Temperature / RH Measured Parameters time time Arrhenius Parameter: measure of Accumulated Temperature Stress Coffin-Manson Parameter: Measure of Plastic strain based thermal fatigue. time Extreme Temperatures (& humidity): Max. & min. temperature (& humidity)values in the specified periodic intervals are recorded. 1 1 2 2 Every 10°C rise in temperature (above the 25° C reference) halves the device life-time. 30 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 RH parameter: Measure of Accumulated weighted humidity hours. 0 if % 50% 50 1 10 if % 50% Environmental data needed for outdoor products. Examples: •Highest temperature •Lowest temperature •Highest thermal stress •Lowest thermal stress •Lowest RH •Highest RH •Lightning •Storms •Snow •Rain •Salt •Other Chemical •Cleaning the product •etc The product must be robust against all relevant stressors and possible combinations! 31 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Backup slides Reliability Eng. interact with project & organization Product Performance Project and Line Managements Reliability Eng. task Designers task Understand the end of life performance specification target. Help establish performance specification at end of life. Define and accept end of life performance specifications: PRS defined and accepted Assist how to design Performance to end of life time Design to specified Performance at end of life time Assist how to design with Design with sufficient margin and confidence margin and confidence Specify Validation Specify and Executing process criteria's to meet functional setup end of life performance specification 33 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Reliability Eng. interact with project & organization Mission profile Project and Line Managements Reliability Eng. task Designers task Align & accept Assist Mission Profiles Define and own Mission Profiles Explain the statistics and the understanding of accumulated stress in the mission profiles Gathering data from applications Assist translating component stress and how to avoid component breakdowns before the life time budget allow this. Translate from product to component mission profiles Part of PRS Gathering data from applications 34 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Reliability Eng. interact with project & organization Robustness and Lifetime Goals Project and Line Managements Reliability Eng. task Designers task Align & accept Define Reliability Goals Part of PRS Breakdown in budgets to estimate availability and track lifetime Part of budget breakdown and estimate lifetime Functions levels Define functions Design function Assist f Robustness level Design f Robustness Components level Special component are known for low Technology Strength Focus on design components Part of Project Business Case Calculate Warranty Cost Assist in Cost optimization Optimize design Align & accept Confidence in achieving the Qlevel 35 | Reliability Engineering 07/10/2015 Tutorial ESREF 2015 Part 2 Reliability analysis based on mission profiles Ke Ma Flows and structure for reliability analysis Mission profiles translation and mapping under multi-time-scales Case study on lifetime prediction in wind power application CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 36 Enabling Part of “Design for Reliability” Typical development cycle of power electronics products Specified lifetime Mission Specifications Design & Development Production Market × Unexpected Failures High cost ! $$$ Products development considering “Design for reliability” Specified lifetime Mission Specifications Design & Development Production × Expected Failures + Reliability Specifications Market + - $ Much lower cost ! Reliability Evaluation Tools CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 37 Concept of the reliability prediction Cost Operation improvement “Reliability Metrics” Mission Profiles Reliability Tools ? 1.1 kVDC IGBT Generator Filter Wind turbine 2L converter Converter Designs 690 Vrms Grid · reliability · lifecycle · margin · weakness · cost · wear-out · …… 2L converter Design improvement Quality ► Mission-profile dependent ► Physics-of-failure based ► Applications compatible CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 38 Road Map to Access Reliability Metrics Identification · Critical components · Failure mehanisms · Major stress & strength Critical components in Power electronics Stress Analysis Strength Modeling · Mission profile translation · Multi-physics stress · Multi-time scales stress · Component-based · Accelerated/Limit test · Degradation model Translate mission profile to device loading Frequency of occurance Accelerated test of IGBT Reliability Mapping Stress variation · Stress organization · Variation & statistics · Multi-components system Strength variation Failures ! Designed Stress Designed Strength Relation of stress, strength, failures Rain flow counting of thermal cycles Reliability Metrics Indirect · Thermal loading · Voltage/current stress · Stress margin Direct · Bx lifetime · Robustness · Reliability/unreliability Thermal loading of IGBT chips Reliability/unreliability vs. time CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 39 Mission Profiles of Wind Power Converter Voltage(%) 100 Germany 90 Spain Denmark 75 US 25 Limited space Keep connected above the curves Time (ms) 0 150 500 Generator side Wind speed (m/s) 1000 1500 Grid faults Harsh environment Vw 750 P P Q Q Wind Power Conversion System Grid side P/Prated (p.u.) 1.0 Underexcited Boundary 0.8 Overexcited Boundary 0.6 Ambient Temp. (ºC) 0.4 Ta 0.2 Time (hour) All have impacts to thermal cycling and reliability ! Q/Prated (p.u.) -0.3 Underexcited Overexcited 0.4 Q support Variable wind and temp. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 40 Main Disturbances for Thermal Cycles Time scale day hour min sec ms µs Temp. / Wind Enviromental Wind Turbine Generator Mechanical Electrical Control Grid Switching Main disturber Ambient temperature, Wind variation, Wind speed variation MPPT Control, Grid Device switching ► Wide spread of time scales ! ► Hard to model and predict. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 41 Concept of Multi-Time Scales converter Modelling Enviroment level (day-year) · · · · Converter System Enviromental variance Steady state Analytical model No thermal dynamics Converter environment MPPT Control System level (s-h) · · · · Mechanical variance Control dynamics Ts averaged model Slow thermal dynamics Inverter Control LCL Filter dinverter Wind Mechanics Grid + - + - Zg Control and mechanics 1.1 kVDC Circuit level (ms - s) IGBT Generator · · · · Electrical variance Switching dynamics Detail circuit model Fast thermal dynamics 690 Vrms Filter Wind turbine 2L converter Grid 2L converter Circuit and control CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 42 General Structure for Thermal Analysis of PE System vdc DC link vabc iabc Control PWM ► Mismatched time constants. Filter ► Thermal modelling instead of monitoring. Grid idc ► Multi-domains models need to be accurate. Zg ► Multi-disturbances related to mission profiles. Typical grid-connected converter system Idc Q* Electr. param. Duty ratio Vdc* Control Tambient Converter feedback Control & Electrical models pLoss Loss Thermal impedance ΔT + + Device Temp. feedback Loss & Thermal models Signal flow for the thermal information of device CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 43 Circuit Level Thermal Modelling Controls (switching cycle averaged) vdc Vdc* vdc* - ed id - + iin idq dq abc Cdc id* ωLF dq abc -ωLF Q* vdc + PI PI Q* 2 Ed 3 i q* ► Suitable for control and switching dynamics. ► Device switching is included ► Heat sink dynamics is not included ► Thermal information from µs to a few seconds. Electrical behaviors (switching dynamics) θ vabc* Grid iabc Lf PWM Eabc + PI Converter - iq PLL abc dq θ edq eq Pin Electrical & control Tj TA IGBT module Thermal model (device dynamics) Loss model (instanenous) dabc TC Tj dabc pcon@Tj R jc1 jc1 s 1 ... iabc pdevice ... + + R jcn jcn s ∑ ΔTjc Tj + 1 Moudule psw@Tj Case temperature vdc fs Tj Tc Loss & thermal 200 ms, 1 µs step CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 44 System Level Thermal Modelling Controls (switching cycle averaged) Electrical behaviors (switching cycle averaged) ed vdc Vdc* vdc* - ed id - + PI PI ed PWM + id* 2 Ed 3 i q* PI - id 1 s LF + × RF dd -ωLF + ÷ PWM × dq + iq - + 1 s Cdc icap vdc × RF eq eq 3/2 dq 1 s LF - + + ωLF vdc - iq × iin id vdc -ωLF Q* dd ÷ ωLF Q* iin ► Suitable for control and mechanical dynamics ► Device switching is not included ► Heat sink dynamics is included ► Thermal information above switching cycle to hours. Pin iq Tj TA eq IGBT module Foster Model (Gain from Pin to Tjc) Pout other devices Electrical & control TC LPF Pout Rch Thermal Grease Heat sink Ch Gain from Pin to Pout Thermal model (device + heat sink dynamics) Loss model (switching cycle averaged) dabc dabc jc1 pcon@TH Conduction loss function pcon@TL Temp. depedent function iabc pcon@Tj pdevice1 jcn s iabc psw@TL psw@Tj pdevice2 + Thermal grease ∑ … … fs LPF ΔTch Rch Gpin_to_pout pdeviceN vdc Tj1 1 LPF psw@TH Temp. depedent function + Moudule + Switching loss function ΔTjc ∑ R jcn + Esw@TH Esw@TL 1 ... Vcon@TL s ... Vcon@TH idq R jc1 Tj ha Rha s 1 + Tc1 Th Heat sink Ta Tj Loss & thermal 3 hours, 1 second step CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 45 Environment Level Thermal Modelling Electrical behaviors (steady state) iin ed ► Suitable for environmental dynamics ► Control and electrical part is considered as steady state. ► Thermal information above fundamental cycle to years. eq Controls (steady state) Vdc* id vdc vdc* RF id RF iq Q* Q* iq 2 Ed 3 iin LF iq vdc d d LF id 1.5 (id d d ed vdc d q dd eq iq d q ) dq Pin Tj TA IGBT module Electrical & control Pout other devices TC Rch Thermal Grease Thermal model (heat sink/No dynamics) Loss model (fundemental cycle averaged) dabc Tj M Pcon@TH Conduction loss function Pcon@TL Temp. depedent function idq Pcon@Tj Pdevice1 Temp. depedent function Psw@Tj ∑ Pdevice2 … … fs + Thermal grease PdeviceN vdc ΔTch Rch Psw@TH Psw@TL Tj1 Rjcn + Switching loss function + Moudule + Imax ΔTjc ∑ ... φ Ch Rjc1 ... Imax Heat sink Tj ha Rha s 1 + Tc1 Th Heat sink Ta Loss & thermal 1 year, 5 mins step CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 46 Incompatibility of Thermal Stress and Lifetime Model Temperature ΔT Tm time Thermal stress with constant ΔT and Tm Typical lifetime model Only constant ΔT and Tm can be mapped to cycles to failure in this figure ! Thermal stress in real world - Variable ΔT and Tm CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 47 Stress Organization by Rainflow Counting Method Source: M. Matsuishi, T. Endo, “Fatigue of metals subjected to varying stress”, Japan Soc. Mech. Engineering, 1968. Thermal stress vs. time Typical lifetime model Rainflow counting Cycle number vs. ΔT and Tm ΔT and Tm at each cycle CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 48 Miner Rules and Accumulated Damage Stress level 1 Stress level K Stress Stress level 2 N1 Miner rules: N2 … Stress level K-1 NK-1 NK N1 N N 2 ... K 1 N F1 N F 2 N FK Nk – number of counted cycles at stress level k; NFk – number of cycles to failure at stress level k – acquired from life time model; Accumulated damage: ADn N N1 N 2 ... n N F1 N F 2 N Fn (for 1 n K ) Dn: Accumulated damage caused by N1+N2+…Nn counted cycles CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 49 An Example from Wind Speeds to B10 Lifetime Source: K. Ma, M. Liserre, F. Blaabjerg, T. Kerekes, “Thermal Loading and Lifetime Estimation for Power Device Considering Mission Profiles in Wind Power Converter,” IEEE Trans. on Power Electronics, 2014. IGBT Generator 690 Vrms Filter Wind turbine 2L converter Consumed B10 life time / year (%) 1.1 kVDC Grid 2L converter Converter design (Loss curve) Loading Translation Po(t) Loss Ploss Calculation Thermal analysis Thermal Rainflow Impedance Count N Lifetime Mapping Reliability Metrics Reliability mapping Consumed B10 lifetime (%) Mission profile (solar, wind, grid) Converter design (Cooling and device) Wind speed (m/s) CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 50 A Matlab Tool for Lifetime Evaluation Key features ► User specified mission profiles inputs ► Wind power, solar PV and motor drive applications ► Outputs: accumulated damage as function of time, B10 lifetime CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 51 Examples by using the tools – mission profiles 1 year Wind speed recorded at Thyboron wind farm Damage built in 1 year A typical ClassIA wind speed variation in 60 hours Damage built in 60 hours CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 52 Examples by using the tools – cooling strategy Cooling behavior of heat sink during the shut down of wind turbines Reduce to ambient temperature. Maintain to constant temperature. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 53 Critical issues of reliability prediction Identification · Critical components · Failure mehanisms · Major stress & strength ► Accurate but fast-simulated thermal model Stress Analysis Strength Modeling · Mission profile translation · Multi-physics stress · Multi-time scales stress · Component-based · Accelerated/Limit test · Degradation model ► Correct mission profiles in the real filed operation. ► Variation of parameter/stress/strength in components ► Impacts of multi-components and redundancy design Reliability Mapping · Stress organization · Variation & statistics · Multi-components system ► Other failure mechanisms and components ► Validating the prediction results Reliability Metrics Indirect · Thermal loading · Voltage/current stress · Stress margin Direct · Bx lifetime · Robustness · Reliability/unreliability CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 54 More Advanced Thermal Modelling – FEM Simulation Structure modeling of IGBT module mounted on water cooling system Structure modelling of cooling system ► Suitable for thermal distribution analysis ► Only for very short term or steady-state ► Thermal information below a few seconds Thermal distribution inside module CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 55 From FEM to Circuit Simulation – Extended Time Ranges Ploss ( diode ) Temperature monitoring points T detail distribution P [W] Step Ploss (IGBT) Trial1: to IGBT chip P [W] Step Ploss (diode) t [s] i9 i8 i7 i6 i5 i4 i3 i2 i1 d3 d2 d1 Trial2: to diode chip d6 d5 d4 T d9 d8 j T d7 j j T d6 T d5 j d2 d1 j d4 j j j T T T Diode Chip T jd 3 ) ) Z th( d( 2j coupl Z th(i(j2coupl s1) s1) Z thd (2 j s1) Tsd1 9 Tsd1 8 Temp [°C] Tsd1 7 T d3 T d6 d 5 s2 Tj Ts1 Ts2 Z thi 2( j s1) i2 s1 i8 s1 T T Tsi19 Tsi17 Tsi14 IGBT Chip Solder i2 Tsi21 ) ) Z th(i(2s1coupl Z th( d(s22coupl s 2) c) Z thd (2s 2c ) Tsi16 i5 s1 Ploss ( diode ) Z th ( s1 s 2) Ploss ( IGBT ) T d3 d 2 s2 Baseplate Solder Tsi13 T Tsi11 Ts 2 Tsd28 Ts 2 Tsd27 Tsd1 4 Tsd21 critical layers IGBT Chip ) ) Z th( d(s12coupl Z th(i(2s1coupl s 2) s 2) Z thd (2s1 s 2) Tsd29 Ploss ( diode ) d 2 s1 d 1 s1 Tsd1 5 T Ts1 Tsd1 4 t [s] t [s] Ploss ( IGBT ) Diode Chip Solder Temperature responses d9 d8 d7 Tsd1 6 T ji1 Ploss ( IGBT ) T ji 9 T ji 3 T ji 6 i2 i5 i8 Tj Tj Tj T ji 7 T ji 4 Ploss ( diode ) Ploss ( IGBT ) i2 s2 T Tsi23 Tsi24 i5 s2 T Tsi26 Tsi27 i8 s2 T Tsi29 Baseplate Solder Z thi 2( s 2c ) Tc Z th ( c a ) Temperature responses at critical points (Extraction of thermal impedance curves) Ta 3D thermal network based on FEM simulation ► Only critical points and layers are focused ► Thermal coupling & boundary conditions are considered and modeled. ► New 3-dimensional thermal impedance geometry CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 56 Results Comparison Between FEM and 3D Thermal Impedance i2_s1 i5_s1 i8_s1 i2_s2 i5_s2 i8_s2 D2 Tj T1 Tji2 Tji1 D1 T2 (FEM simulation, 15 min by work station) i3 Temperature measured by infrared camera (Extracted thermal network, 15 sec by laptop) 97 Model FEM Experiment 96 95 ► Much fast simulation speed - enable longer term stress analysis and integration with other models 94 Temperature (C) ► Thermal cycling information are accurately remained in critical points. 93 92 91 90 89 88 87 0 0.2 0.4 0.6 0.8 Time (s) 1 1.2 1.4 Temperature comparison on i2 point CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 57 1.6 Part 3 Testing of Power Electronic Components and Design for Parameter Variations Huai Wang ■ Power cycling testing of IGBT modules ■ Degradation testing of film capacitors under humidity conditions ■ Design for parameter variations of IGBT modules CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 58 Reliability Critical Components in Power Electronics An example of capacitors (Photo courtesy of CDE). An example of IGBT module (Photo courtesy of Infineon). Percentage of the response to the most frangible components in power electronic systems from an industry survey (% may vary for different applications and designs) Data sources: S. Yang, A. Bryant, P. Mawby, D. Xiang, R. Li, and P. Tavner, "An Industry-Based Survey of Reliability in Power Electronic Converters," IEEE Transactions on Industry Applications, vol. 47, pp. 1441-1451, 2011. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 59 IGBT Power Cycling Testing TC-thermal cycling; PC-power cycling CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 60 LESIT Project Power Cycling Testing (1993-1995) (LESIT – Leistung Elektronik Systemtechnik Informations Technologie) Figure source: U. Scheuermann and U. Hecht, “Power cycling lifetime of advanced power modules for different temperature swings,” in Proc. PCIM Europe 2002, pp. 59-64. Data source: M. Held, P. Jacob, G. Nicoletti, P. Scacco, M. H. Poech, “Fast power cycling test for IGBT modules in traction application,” in Proc. Power Electronics and Drive Systems 1997, 425-430. Number of cycles to failure as function of ΔTj with Tm (mean temperature). Testing focus: bond wire reliability of IGBT modules in traction application Testing samples: 300A/1200V single switch IGBT modules from different suppliers Testing conditions: ΔTj : 30°C to 80°C, VGE: 15V, current load : 240 to 300A, ton :0.6 to 4.8s, and toff : 0.4 to 5s Failure criterion: 5% increase of VCE Measurement method: periodical static measurement of VCE CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 61 RAPSDRA Project Power/Thermal Cycling Testing (RAPSDRA – Reliability of Advanced High Power Semiconductor Devices for Railway Traction Application) Source: H. Berg and E. Wolfgang, "Advanced IGBT modules for railway traction applications: Reliability testing," Microelectronics Reliability 38(6-8): 1319-1323, 1998. Proposed reliability tests in RAPSDRA project Reliability test Proposed testing conditions Standards Estimated testing time Testing focus Power cycling 1 (active) Tmin = 55°C, ΔT=50°C, 70°C Ic = Icnom, tcycle=3 sec Non-standard 3 million cycles (104 days) Bond wire reliability Traction application Power cycling 2 (active) Tmin = 55°C, ΔT=50°C, 70°C Ic = Icnom, tcycle=1 min Non-standard 100 k cycles (70 days) Solder reliability Traction application Thermal cycling (passive) Tmin = 25°C, Tmax = 105°C, 125°C, tcycle=4 min Non-standard 10 k cycles (28 days) Solder reliability Traction application RAPSDRA project extends the testing focus to the solder joint reliability CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 62 PWM Switching Based Power Cycling Testing Source: V. Smet, V., F. Forest, et al., "Ageing and failure modes of IGBT modules in high-temperature power cycling," IEEE Transactions on Industrial Electronics, 58(10): 4931-4941. DC pulse PWM pulse More realistic testing (i.e. switching, high voltage, dynamic loss) under PWM switching conditions Testing with inverter legs in a back-to-back configuration 600V/200A IGBT modules for automobile traction application CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 63 Power Cycling Testing at Aalborg University For wind power converter applications CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 64 Power Cycling Testing at Aalborg University PWM switching currents with online on-state voltage monitoring Source: Pramod Ghimire, Stig Munk-Nielsen, et. al Testing setup Designed gate driver with integrated on-state voltage measurement circuits and CONCEPT driver core ■ More realistic testing (i.e. switching, high voltage, dynamic loss) under switching conditions ■ Testing with inverter legs of 1700V/1000A IGBT modules for wind power application ■ Online measurement of VCE CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 65 Wear Out Testing Results Source: Pramod Ghimire, Stig Munk-Nielsen, et. al Stressed parameter for ageing test of power module DC link voltage 1000V Load current 650Arms Output frequency 6 Hz Switching frequency 2.5kHz Cooling temperature 80oC Cooling Water mixed with glycol On-state voltage increase of the lower side switches of the power modules CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 66 Power Cycling Testing at Aalborg University DC currents (10 modules simultaneously) Source: Stig Munk-Nielsen, et. al Specifications of the testing setup Type of DUT 1000V Max. No. of DUTs 10 power modules DC currents < 2000A Duty cycle ton=2s , toff=8s (adjustable) ΔTjunction <150°C Cooling water temp. 25°C - 80°C CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 67 Power Cycling Testing at Aalborg University PWM switching currents (for 600 V/30 A low power modules) Source: Uimin Choi, et. al Testing conditions: ∆Tj = 80 °C, Th = 48 °C, 30 A current RMS, 400 V DC link, cycle period = 1 s) CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 68 A Widely Used Lifetime Model for Capacitors A simplified model derived from the above equation The information of humidity impact is usually not available! Lx – expected operating lifetime; L0 – expected lifetime for full rated voltage and temperature; Vx – actual applied voltage; Vo – rated voltage; T0 – maximum rated ambient temperature; Tx – actual ambient temperature; Ea is the activation energy, KB is Boltzmann’s constant (8.62×10−5 eV/K) CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 69 Capacitor Testing System System configuration ■ Climatic chamber ■ 2000 V (DC) / 100 A (AC) / 50 Hz to 1 kHz ripple current tester ■ 2000 V (DC) / 50 A (AC) / 20 kHz to 100 kHz (discrete) ripple current tester ■ 500 V (DC) / 30A (AC) / 100 Hz to 1 kHz (discrete) ripple current tester ■ LCR meter ■ IR / leakage current meter ■ Computer System capability ■ ■ ■ ■ Temp. range -70 °C to +180 °C Humidity range (for a certain range of temp.): 10 % RH to 95 % RH DC voltage stress up to 2000 V and ripple current stress up to 100 A and 100 kHz Measurement of capacitance, ESR, inductance, insulation resistance, leakage current and hotspot temperature CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 70 Testing Results MPPF-Caps Capacitance (normalized) 85°C, 85%RH 2,160 hours 85°C, 70%RH 2,700 hours Testing of 1100 V/40 μF MPPF-Caps 85°C, 55%RH 3,850 hours (Metalized Polypropylene Film) Sample size: 10 pcs for each group of testing CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 71 Testing Results Weibull Plots 85°C, 85%RH 85°C, 70%RH Testing of 1100 V/40 μF MPPF-Caps 85°C, 55%RH (Metalized Polypropylene Film) Sample size: 10 pcs for each group of testing CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 72 Humidity-Dependent Lifetime CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 73 An Example of Photovoltaic (PV) Inverter An electrical energy conditioning system to convert the DC power from PV panels to AC power to the electric grid. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 74 Translation of Mission Profile into Power Tamb – ambient temperature; SI – Solar Irradiances; Pin – input power of the PV inverter CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 75 Translation Thermal Stress Profiles into Lifetime Distribution Source of lifetime model: R. Bayerer, T. Hermann, T. Licht, J. Lutz, and M. Feller, “Model for power cycling lifetime of IGBT modules - Various factors influencing lifetime,” in Proc. International Conference on Integrated Power Systems (CIPS), pp. 1–6, 2008. Tj – junction temperature; Ploss – power loss; Rth – thermal resistance; ∆Tj – junction temperature variation; N- number of cycle to failure; Tj, min – minimum junction temperature; ton- heating time of the power cycling; V- blocking voltage of the IGBT chips; I- current per bond wire; A, β1 to β6 are constants; CI – Confidence Interval CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 76 Parameter Variations in IGBTs and the Lifetime Model Vce,on – on-state voltage drop of IGBTs. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 77 Annual Mission Profile of Solar Irradiance and Ambient Temperature (1s/data) CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 78 Annual Accumulated Damage Distribution with Respect to Each Parameter Variation CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 79 Predicted Lifetime Distribution of Bond-Wires of the IGBT Module CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 80 References 1. H. Wang, M. Liserre, F. Blaabjerg, P. P. Rimmen, J. B. Jacobsen, T. Kvisgaard, J. Landkildehus, "Transitioning to physics-of-failure as a reliability driver in power electronics," IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 2, no. 1, pp. 97-114, Mar. 2014. (Open Access) 2. H. Wang, M. Liserre, and F. Blaabjerg, “Toward reliable power electronics - challenges, design tools and opportunities,” IEEE Industrial Electronics Magazine, vol.7, no. 2, pp. 17-26, Jun. 2013. 3. H. Wang, F. Blaabjerg, and K. Ma, “Design for reliability of power electronic systems,” in Proceedings of the Annual Conference of the IEEE Industrial Electronics Society (IECON), 2012, pp. 33-44. 4. S. Yang, A. T. Bryant, P. A. Mawby, D. Xiang, L. Ran, and P. Tavner, “An industry-based survey of reliability in power electronic converters,” IEEE Trans. Ind. Appl., vol. 47, no. 3, pp. 1441-1451, May/Jun. 2011. 5. Y. Yang, H. Wang, F. Blaabjerg, and K. Ma, "Mission profile based multi-disciplinary analysis of power modules in single-phase transformerless photovoltaic inverters," in Proceedings of European Conference on Power Electronics and Applications, 2013, pp. P.1P.10. 7. S. Beczkowski, P. Ghimire, A. R. de Vega, S. Munk-Nielsen, B. Rannestad, P. Thøgersen, “Online Vce measurement method for wear-out monitoring of high power IGBT modules”, in Proc. EPE 2013, pages 1-7. 8. P. Ghimire, A. R. de Vega, S. Beczkowski, B. Rannestad, S. Munk-Nielsen, P. Thøgersen, “Improving reliability of power converter using an online monitoring of IGBT modules”, IEEE Industrial Electronics Magazine, Vol. 8, No. 3, 09.2014, p. 40-50. 9. Ghimire, Pramod; Pedersen, Kristian Bonderup; de Vega, Angel Ruiz; Rannestad, Bjørn; Munk-Nielsen, Stig; Thøgersen, Paul Bach, “ A real time measurement of junction temperature variation in high power IGBT modules for wind power converter application”, Integrated Power Systems (CIPS), 2014 8th International Conference on. VDE Verlag GMBH, 2014. p. 1-6 6776812. 10. Ghimire, Pramod; Pedersen, Kristian Bonderup; Rannestad, Bjørn; Munk-Nielsen, Stig; Thøgersen, Paul; Rimmen, Peter de Place., ”Real time wear-out monitoring test setup for high power IGBT modules”, Submitted in Transaction on Power electronics. 11. R. Bayerer, T. Hermann, T. Licht, J. Lutz, and M. Feller, “Model for power cycling lifetime of IGBT modules - Various factors influencing lifetime,” in Proc. International Conference on Integrated Power Systems (CIPS), pp. 1–6, 2008. 12. H. Wang and F. Blaabjerg, “Reliability of capacitors for DC-link applications in power electronic converters – an overview,” IEEE Transactions on Industry Applications, vol. 50, no. 5, pp. 3569-3578, Sep./Oct. 2014. (Open access) 13. H. Wang, D. A. Nielsen, and F. Blaabjerg, “Degradation testing and failure analysis of DC film capacitors under high humidity conditions,” Microelectronics Reliability, in press, doi:10.1016/j.microrel.2015.06.011. 14. P. D. Reigosa, H. Wang, Y. Yang, and F. Blaabjerg, “Prediction of bond wire fatigue of IGBTs in a PV inverter under long-term operation,” in Proc. APEC, pp. 3052-3059, 2015. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 81 References 14. M. Matsuishi, T. Endo, “Fatigue of metals subjected to varying stress”, Japan Soc. Mech. Engineering, 1968. 15. K. Ma, D. Zhou, F. Blaabjerg, “Evaluation and Design Tools for the Reliability of Wind Power Converter System,” Journal of Power Electronics, in press, 2015. 16. L. Popova, K. Ma, F. Blaabjerg, J. Pyrhonen, “Device Loading of Modular Multilevel Converter in Wind Power”, IEEJ Journal of Industry Applications, Vol. 4, No. 4, 2015. 17. K. Ma, A. S. Bahman, S. M. Beczkowski, F. Blaabjerg, “Complete Loss and Thermal Model of Power Semiconductors Including Device Rating Information,” IEEE Trans. on Power Electronics, Vol. 30, No. 5, pp. 2556-2569, May 2015. 18. K. Ma, M. Liserre, F. Blaabjerg, T. Kerekes, “Thermal Loading and Lifetime Estimation for Power Device Considering Mission Profiles in Wind Power Converter,” IEEE Trans. on Power Electronics, Vol. 30, No. 2, pp. 590-602, 2015. 19. A. Sajjad, K. Ma, F. Blaabjerg, “A Novel 3D Thermal Impedance Model for High Power Modules Considering Multi-layer Thermal Coupling and Different Heating/Cooling Conditions. “ in Proc APEC 2015. 20. K. Ma, F. Blaabjerg, “Multi-timescale Modelling for the Loading Behaviours of Power Electronics Converter” in Proc. ECCE 2015. 21. K. Ma, N. He, F. Blaabjerg, M. Andresen, M. Liserre, “Frequency-Domain Thermal Modelling of Power Semiconductor Devices” in Proc. ECCE 2015. CENTER OF RELIABLE POWER ELECTRONICS, AALBORG UNIVERSITY | 0 7 . 1 0 . 2 0 1 5 | S L I D E 82 Thank you for your attention! Center of Reliable Power Electronics (CORPE), University, Denmark Danfoss Power Electronics, Denmark For presentation slides download: www.corpe.et.aau.dk CORPE