© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Digital Object Identifier (DOI): 10.1109/JESTPE.2013.2290282 IEEE Journal of Emerging and Selected Topics in Power Electronics, accepted on 01 November 2013 Transitioning to Physics-of-Failure as a Reliability Driver in Power Electronics Huai Wang Marco Liserre Frede Blaabjerg Peter de Place Rimmen John B. Jacobsen Thorkild Kvisgaard Jørn Landkildehus Suggested Citation

H. Wang, M. Liserre, F. Blaabjerg, P. P. Rimmen, J. B. Jacobsen, T. Kvisgaard and J. Landkildehus, "Tran-sitioning to physics-of-failure as a reliability driver in power electronics,” IEEE Journal of Emerging and Selected Topics in Power Electronics, accepted.

1

Abstract— Power electronics has progressively gained import-

ant status in power generation, distribution and consumption.

With more than 70% of electricity processed through power elec-

tronics, recent research endeavors to improve the reliability of

power electronic systems to comply with more stringent constra-

ints on cost, safety and availability in various applications. This

paper serves to give an overview of the major aspects of reliability

in power electronics and to address the future trends in this

multidisciplinary research direction. The ongoing paradigm shift

in reliability research is presented first. Then the three major

aspects of power electronics reliability are discussed, respectively,

which cover from physics-of-failure analysis of critical power

electronic components, state-of-the-art design for reliability pro-

cess and robustness validation, and intelligent control and condi-

tion monitoring to achieve improved reliability under operation.

Finally, the challenges and opportunities for achieving more reli-

able power electronic systems in the future are discussed.

Index Terms— Power electronics, design for reliability,

physics-of-failure, robustness validation, IGBT modules, capaci-

tors.

I. INTRODUCTION

OWER electronics enables efficient conversion and flexible

control of electric energy by taking advantage of the

innovative solutions in active and passive components, circuit

topologies, control strategies, sensors, digital signal processors

and system integrations. While targets concerning efficiency of

power electronic systems are within reach, the increasing

reliability requirements create new challenges due to the

following factors:

Mission profiles critical applications (e.g. aerospace, mi-

litary, more electrical aircrafts, railway tractions, automo-

Manuscript received April 22, 2013; revised July 25, 2013 and October 9,

2013; accepted November 1, 2013.

H. Wang and F. Blaabjerg are with the Department of Energy Technology, Aalborg University, DK-9220 Aalborg, Denmark (e-mail: hwa@et.aau.dk;

fbl@et.aau.dk).

M. Liserre is with the Faculty of Engineering, Christian-Albrechts-Univer-sity of Kiel, 24143 Kiel, Germany (e-mail: ml@ tf.uni-kiel.de).

P. P. Rimmen and J. Landkildehus are with Danfoss Power Electronics A/S,

R&D Design Center, DK-6300 Gråsten, Denmark (e-mail: pr@danfoss.com; jla@danfoss.com).

J. B. Jacobsen and T. Kvisgaard are with GRUNDFOS Holding A/S,

DK-8850 Bjerringbro, Denmark (e-mail: jbjacobsen@grundfos.com; tkvisga-ard@grundfos.com).

Color versions of one or more of the figures in this paper are available online

at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JESTPE.2013.2290282

tive, data center, medical electronics).

Emerging applications under harsh environment and long

operation hours (e.g. onshore and offshore wind turbines,

photovoltaic systems, air conditions and pump systems).

More stringent cost constraints, reliability requirements

and safety compliances, e.g. demand for parts per million

(ppm) level failure rates in future products.

Continuous need for higher power density in power con-

verters and higher level integration of power electronic

systems, which may invoke new failure mechanisms and

thermal issues.

Uncertainty of reliability performance for new materials

and packaging technologies (e.g. SiC and GaN devices).

Increasing complexity of electronic systems in terms of

functions, number of components and control algorithms.

Resource constraints (e.g. time, cost) for reliability testing

and robustness validation due to time-to-market pressure

and financial pressure.

Table I illustrates the industrial challenges in a reliability

perspective of yesterday, today and tomorrow. To meet the

future application trends and customer expectations for ppm

level failure rate per year, it is essential to have better under-

standing of failure mechanisms of power electronic compo-

nents and to explore innovative R&D approaches to build

reliability in power electronic circuits and systems.

From this perspective, opportunities exist for power elec-

tronics to expand its role in dealing with efficient and reliable

power processing in different kinds of applications. Nearly four

decades ago, the scope of power electronics was defined by

William E. Newell as three of the major disciplines of electrical

engineering shown in Fig. 1(a) [1]. Likewise, the future reliabi-

lity research in power electronics involves multidisciplinary

knowledge as defined here shown in Fig. 1(b). It covers the

following three major aspects: analytical analysis to understand

the nature of why and how power electronic products fail;

design for reliability and robustness validation process to build

in reliability and sufficient robustness in power electronic

products during each development process; intelligent control

and condition monitoring to ensure reliable field operation

under specific mission profiles. Robustness validation is a

process that is widely accepted and implemented in the automo-

tive sector, which is to demonstrate that a product performs its

intended functions with sufficient margin under a defined

mission profile within its specified lifetime [2]. Mission profile

Transitioning to Physics-of-Failure as a

Reliability Driver in Power Electronics

Huai Wang, Member, IEEE, Marco Liserre, Fellow, IEEE, Frede Blaabjerg, Fellow, IEEE,

Peter de Place Rimmen, John B. Jacobsen, Thorkild Kvisgaard, and Jørn Landkildehus

P

2

TABLE I

THE RELIABILITY CHALLENGE IN INDUSTRY SEEN BEFORE, TODAY AND IN THE FUTURE

Customer

expectations

Replacement if failure

Years of warranty

Low risk of failure

Request for maintenance

Peace of mind

Predictive maintenance

Reliability target Affordable market returns (%) Low market return rates ppm market return rates

R&D approach Reliability test

Avoid catastrophes

Robustness tests

Improve weakest components

Design for reliability

Balance with field load / mission profile

R&D key tools

Product operating and

function tests

Testing at the limits Understanding failure mechanisms, field load, root cause

Multi-domain simulation

…

(a) (b)

Fig. 1. Defined scope in (a) power electronics by William E. Newell in 1970’s

[1] and (b) power electronic reliability research needs seen from today.

is a representation of all of the relevant operation and environ-

mental conditions throughout the full life cycle [2] through

production process, test, shipping, service to end of life. The

robustness validation process involves the activities of verifi-

cation, legal validation, and producer risk margin validation.

This paper gives an overview of power electronics reliability

from the three respective aspects defined in Fig. 1(b) and add-

resses the future trends in this multidisciplinary research direc-

tion. § II illustrates the ongoing paradigm shift in reliability

research in power electronics. § III presents the Physics-of

-Failure (PoF) analysis of reliability-critical components to

provide a basis for system level design. § IV discusses the

state-of-the-art Design for Reliability (DFR) and robustness

validation process to build-in reliability through design. § V

presents the control and monitoring (including fault-tolerant

strategies) methods to improve reliability of power electronic

systems under field operation. Finally, the future challenges

and opportunities in reliability of power electronics are dis-

cussed.

II. ONGOING PARADIGM SHIFT IN RELIABILITY RESEARCH IN

POWER ELECTRONICS

Reliability is defined as the ability of an item to perform the

required function under stated conditions for a certain period of

time [3], which is often measured by probability of survival and

failure rate. It is relevant to the durability (i.e. lifetime) and

availability of the item. The essence of reliability engineering is

to prevent the creation of failures. The deficiencies in the

design phase have effect on all produced items and the cost to

correct them is progressively increased as the development

proceeds.

TABLE II

TYPICAL LIFETIME TARGET IN DIFFERENT POWER ELECTRONIC APPLICATIONS

Applications Typical design target of Lifetime

Aircraft 24 years (100,000 hours flight operation)

Automotive 15 years (10,000 operating hours, 300,000 km)

Industry motor drives 5-20 years (60,000 hours in at full load)

Railway 20-30 years (10 hours operation per day)

Wind turbines 20 years (24 hours operation per day)

Photovoltaic plants 5-30 years (12 hours per day)

A. Reliability in Typical Power Electronic Applications

The performance requirements of power electronic products

are increasingly demanding in terms of cost, efficiency, relia-

bility, environmental sustainable materials, size, and power

density. Of which, the reliability performance has influences on

the safety, service quality, lifetime, availability and life cycle

cost of the specific applications. Table II summarizes the

typical design target of lifetime in different applications. To

meet those requirements, paradigm shift is going on in the area

of automotive electronics, more electrical aircrafts, and railway

tractions by introducing new reliability design tools and

robustness validation methods [2], [4]-[5].

With the increasing penetration of renewable energy sources

and the increasing adoption of more efficient variable-speed

motor drives [6]-[8], the failure of power electronic converters

in Wind Turbines (WTs), Photovoltaic (PV) systems and motor

drives are becoming an issue. Field experiences in renewables

reveal that power electronic converters are usually one of the

most critical assemblies in terms of failure level, lifetime and

maintenance cost [9]. For example, it shows that frequency

converters cause 13% of the failure level and 18.4% of the

downtime of 350 onshore wind turbines in a recent study asso-

ciated with 35,000 downtime events [10]. Another representa-

tive survey in [11] concludes that PV inverters are responsible

for 37% of the unscheduled maintenance and 59% of the asso-

ciated cost during five years of operation of a 3.5 MW PV plant.

It should be noted that such statistics always look backwards as

those designs are more than 10 years old. The present techno-

logy could have different figures.

B. Ongoing Paradigm Shift in Reliability Research

The reliability engineering has emerged as an identified dis-

cipline since 1950s with the demands to address the reliability

Yesterday Today Tomorrow

3

issues in electronic products for military applications [12].

Since then, much pioneer work has been devoted to various

reliability topics. One of the main streams is the quantitative

reliability prediction based on empirical data and various

handbooks released by military and industry [13]. Another

stream of the discipline focuses on identifying and modeling of

the physical causes of component failures, which was the initial

concept of PoF presented in 1962 [14]. However, until the

1980s, the handbook based constant failure rate models (e.g.

Military-Handbook-217 series [15]) have been dominantly

applied for describing the useful life of electronic components.

Since 1990s, with the increased complexity of electronic

systems and especially the application of integrated circuits

(ICs), more and more evidences were suggesting that constant

failure rate models are inadequate [16]. The Military-Hand-

book-217F is therefore officially cancelled in 1995. PoF app-

roach has started to gain its more and more important role in

reliability engineering.

In recent years, the initiatives to update the Military-Hand-

book-217F have turned to a hybrid approach, which is proposed

for the planned version of Military-Handbook-217H [17].

During the stage of program’s acquisition-supplier selection

activities, updated empirical models will be used for comparing

different solutions. During the actual system design and deve-

lopment stage, scientific based reliability modeling together

with probabilistic methods will be applied. Intensive PoF

research has been continuously conducted since 1990s in

microelectronics and the state-of-the-art results are presented in

[16] and [18]. With the transition from pure empirical based

methods to more scientific based approaches, the paradigm

shift in reliability research is going on from the following

aspects:

1) From Components to Failure Mechanisms

PoF approach is a methodology based on root-cause failure

mechanism analysis and the impact of materials, defects and

stresses on product reliability [19]. It changes the analysis of

system from a box of components to a box of failure mecha-

nisms. The traditional handbook based reliability prediction

provides failure rate models for various components. PoF app-

roach analyzes and models each failure mechanism induced by

environmental and usage stresses. For a given component, there

could be multiple failure mechanisms which should be identi-

fied individually. Moreover, failure mechanisms are not limited

to the component level. As discussed in the standard ANSI/-

VITA 51.2 [18], there are various failure mechanisms in com-

ponent level (i.e. single transistor level), package level, and

Printed Circuit Board (PCB) level. From this prospective, it is

challengeable to apply PoF to a complex system of which

limited number of models and their associated parameters are

available [18]. Therefore, it is important to identify and to focus

on the critical failure mechanisms in specific applications.

2) From Constant Failure Rate to Mean Cumulative Function

(MCF) Curve

The conventional reliability metrics constant failure rate

(defined as λ) and the corresponding Mean-Time-Between-

-Failures (MTBF) (defined as 1/λ) are found to be inappropriate

to most practical cases as discussed in [9], [13] and [20].

Therefore, it is discouraged the indiscriminate use of these

metrics.

The failure rate over operational time is not constant. An

alternate technique to present the failure level and time is the

MCF curve [21]. When analyzing repairable systems, it graphs

the number of failures versus time (i.e. since installation). It is

also possible to represent the behavior of the group of systems

by an average number of failures versus time, which is known

as MCF. As shown in Fig. 2, it can be broken down to the main

functions which can be described as following parameters:

Zero time failures occur from lack of robustness to transporta-

tion or installation, indicated by the red line. Early failures

come from lack of production capabilities. Some few products

are slipped through the control parameters in the production,

which are marked as the green Weibull curve (β << 1, where β

is defined as the shape parameter in Weibull distribution [22]).

If the product is not robust to “Catastrophic” stress, the product

might fail. This weakness is designed in and the time when

failure occurs has nothing to do with the age of the product. The

only way such accident can be shoved as random in the

operation time (β = 1), marked in orange curve. This has

nothing with fate rate-values or MTBF to do. The last dominant

curve (i.e. the blue one) is the “Lack of lifetime”. This is the

accumulated degradation for all parameters which are able to

degrade as a function of operational time. The customer will be

the person who sees the accumulated failure level of all these

“weaknesses” in the purple curve in Fig. 2. This figure is also

an integration of the bathtub model, but here it is possible to

operate with quantitative figures, which can be broken down in

budgets (e.g. the degradation budget).

3) From Reliability Prediction to Robustness Validation

Conventional empirical methodologies mainly attempt to

determine the feasibility in fulfilling certain reliability goals

and to predict the warranty-costs and maintenance-support

requirements [12]. They provide limited insights in the design

of the systems themselves to eliminate failures within targeted

service life. Compared to them, the concept of PoF is to identify

the root causes of different types of failure under environmental

and operation stress conditions. Therefore, it helps locate the

weak-links and formulate the corresponding guidelines on

robustness design, process control, validation testing and filed

operation. Take the design as an example, Fig. 3 describes how

Fig. 2. Example of MCF or M (t) curve for explaining and measuring relia-

bility.

4

Fig. 3. Concept for robustness design.

the designer shall understand degradation. Products should be

designed by considering the degraded parameters at the

end-of-life with certain level of design margins. It is also show

that it makes only sense to measure performance inside the

design specifications. The optimal situation is that the design is

so good that no weakness can be found inside the customer or

design specifications. All validations to reliability, lifetime and

robustness have to be demonstrated outside or at design

specifications under relative high stress levels.

4) From Microelectronics to also Power Electronics

The PoF approach has been extensively applied to micro-

electronic systems in the last two decades. Different failure

mechanisms, lifetime models, and equivalent damaged circuit

simulation models of electron devices are well presented in

[16]. More and more new models are under development.

Several PoF based industry standards or guidelines have been

released (e.g. [2] and [18]). One of the common driven factors

from industry, academia and military behind this is the

demanding for more reliable commercial-of-the-shell devices

and systems.

In power electronic applications, reliability has been and will

continue to be one of the important performance aspects in

many applications as discussed in § II Part A. To address the

challenges discussed in § I, power electronic engineers and

scientists have started to apply various reliability tools for

reliability prediction and reliability-oriented design of power

electronic converters or systems. Several literature reviews on

field experiences [23], strategies to improve reliability of power

electronic systems [24] and DFR for power electronic systems

[9] have been presented in the last two years. Respective

research in different applications is also discussed in various

literatures, such as three-phase converters for aircrafts [25],

power inverters for railway tractions [26], inverters for hybrid

electric vehicles [27], high power variable-speed motor drives

[28], and pulsed power converters for industrial process control

[29]. Besides these applications, last decade also saw much

pioneering work on the reliability of power converters for WTs

[30] – [32] and inverters for PV systems [33] – [50]. It reveals

that, unlike the case in microelectronics, conventional hand-

book methods are still dominantly applied nowadays for the

reliability prediction in those studies.

While the pace of power electronics toward PoF approach is

relatively slower than that of microelectronics, the need for this

paradigm shift has been well recognized in automotive industry

[2] and then in other sectors. Especially, much interesting work

from the semiconductor side investigates the failure mechani-

sms of IGBT modules [51] and physical based lifetime models

[52]. More realistic thermal stress analysis of Si and SiC based

devices under long term mission profile are also studied in [49]

and [50], respectively. The level of technology and scientific

understanding are still highly evolving. The research in micro-

electronics could provide a very important foundation for the

ongoing and future work in power electronics, especially from

the methodologies point of view. Nevertheless, it should be

noted that most of the physical based models are not scalable

for power electronic components. System level reliability

problems (e.g. active thermal stresses, interconnections among

components, interaction of different components) are still of

interest to be investigated. Therefore, the following three

sections intend to provide a basic framework of the future

reliability research in power electronics relevant to the ongoing

paradigm shift.

III. POF ANALYSIS OF RELIABILITY CRITICAL COMPONENTS IN

POWER ELECTRONICS

As shown in Fig. 1(b), understanding of the reliability phy-

sics of components applied in power electronics is the most

fundamental aspect. The PoF approach is based on analyzing

and modeling each failure mechanism under various environ-

mental and usage stresses. In practice, the PoF analysis focuses

5

TABLE III

FOCUS POINTS MATRIX (FPM) IN RELIABILITY OF POWER ELECTRONIC COMPONENTS

Load Focus points

Climate + Design => Stressor Active power components

Passive power components

Control circuitry, IC, PCB, connectors…

Ambient Product

design

Stressors Die LASJ Wire-

bond

Cap. Ind. Solder

Joint

MLCC IC PCB Connectors

Relative

humidity

-RH(t) Temperature

-T(t)

-thermal system

-operation

point -ON/OFF

-power

P(t)

Temperature swing ΔT X X X X

Average

Temperature T X X X X

X X x x x

dT/dt x x x x

Water X X x

Relative

Humidity x x x X x x x X X x

Pollution Tightness Pollution

x

x

Mains Circuit Voltage x x x X X

x x x x

Cosmic Circuit Voltage x

Mounting Mechanical Chock

/vibration x

x x x x

x

LASJ - Large Area Solder Joint, MLCC - Multi-Layer Ceramic Capacitor, IC- Integrated Circuit, PCB – Printed Circuit Board, Cap. - Capacitor,

Ind. - Inductor, Level of importance (from high to low): X-X-X-x.

on critical components under critical stress conditions. Among

other components, switching devices and capacitors are two of

the most vulnerable components in terms of failure level and

time as analyzed in [23], [34], [35] and [53]. They are consider-

ed as the reliability critical components in power electronic

converters, especially the IGBT modules in medium to high

power applications and capacitors for DC-link applications.

Therefore, in the following parts, the critical stressors for

different power electronic components is firstly discussed.

Then, the PoF analysis of IGBT modules and DC-link capaci-

tors is given.

A. Critical Stressors for Different Power Electronic Compo-

nents

Focus Point Matrix (FPM), as suggested in [2], is a useful

way to analyze the critical stressors that will kill the compo-

nents. Based on the accumulated industrial experiences and

future research needs, Table III shows the critical stressors for

different components in power electronic systems. It can be

noted that steady-state temperature, temperature swings, humi-

dity, voltage and vibrations have different level of impact on

semiconductor devices, capacitors, inductors and low power

control boards. It provides the information on determining the

critical failure mechanisms. The interactions among different

stressors are also of interest to be explored.

B. PoF Analysis of IGBT Modules

Fig. 4 shows a typical structure of IGBT modules [54]. There

are three dominant wear out failure mechanisms for IGBT

modules due to cyclic thermal stress: baseplate solder joints

cracking, chip solder joint cracking, and the wire bonds lift-off.

The cyclic thermal stress is a response to the converter line and

loading variations as well as periodically commutation of

power switching devices. It will induce thermal cycling on

different layers of materials used for fabrication of power

electronic components.

Fig. 4. Structural details of an IGBT module (connections that are relevant to

module lifetime are marked red) [54].

Fig. 5. A typical stress-strain (σ-ε) curve for a material [55].

6

Fig. 6. Typical catastrophic failure of IGBT modules [60].

Thermal cycling is found to be one of the main drivers for

failure of IGBT modules. The effect of the temperature cycling

can be explained by the typical stress-strain curve [55] shown

in Fig. 5. σ is defined as the cyclic stress (e.g. temperature

cycling) and ε is defined as the deformation. With a low cyclic

stress below σyield, no damage occurs and the material is in the

elastic region. When the stress is increased above σyield, an

irreversible deformation is induced and the material enters into

the plastic region. The coefficients of thermal expansion of

different materials in the IGBT modules are different, leading

to stress formation in the packaging and continuous degrada-

tion with each cycle until the material fails. As derived in [9],

the number of cycles to failure under thermal cycling can be

obtained as

0 - m

N k T T

(1)

where k and m are empirically-determined constants and N is

the number of cycles to failure. ∆T is the thermal cycling range

and ∆T0 is the portion of ∆T that in the elastic strain range. If

∆T0 is negligible compared to ∆T, it can be dropped out from

the above equation, which then becomes the Coffin-Manson

model discussed in [56]-[58].

The model shown in (1) considers the influence of thermal

cycling only. It does not take into account the effect of steady-

-state temperature, thermal cycle time, and geometry. In [59],

an empirical model is developed for bond wire fatigue of IGBT

modules, which tends to treat all the above factors as well as

failure of the diodes in parallel with the IGBT switches. In [52],

a physical based model for wire bond fatigue has been

developed which could analyze the cycle-to-failure under

different steady-state temperature and thermal cycle time.

Although it may be difficult to obtain some of the parameters

required by the model, it is a promising model in its kind for the

PoF analysis.

Besides wear out failure discussed above, different types of

catastrophic failure could also occur triggered by single-event

overstress. Unlike the wear out failure, the catastrophic failure

is difficult to be predicted and thus may lead to serious conse-

quence to the power electronic converters. Fig. 6 classifies the

IGBT catastrophic failure into open-circuit mode and short-

-circuit mode induced by different failure mechanisms. It

should be noted that both wear out failure and catastrophic

failure may have the same failure mechanisms (e.g. bond wire

lift-off) but the former one is due to long term degradation (see

the blue curve in Fig. 2) and the latter one is due to single-event

overstress within short time duration (see the orange curve in

Fig. 2).

C. PoF Analysis of DC-Link Capacitors

DC-link capacitors contribute to cost, size and failure of

power electronic converters on a considerable scale. To address

the issue, research efforts can be divided into two directions: a)

advance the capacitor technology with improved and pre-

determined reliability built in and b) a proper and optimal

DC-link design based on the commercially available capacitors

to ensure reliable field operation. The latter one is more

relevant from the perspective of power electronic designers,

which is discussed here.

Three main types of capacitors are available for DC-link

applications, which are the Aluminum Electrolytic Capacitors

(Al-Caps), Metallized Polypropylene Film Capacitors (MPPF-

-Caps) and high capacitance Multi-Layer Ceramic Capacitors

(MLC-Caps). The DC-link design requires the matching of

available capacitor characteristics and parameters to the parti-

cular application needs under specific environmental, electrical

and mechanical stresses. Table IV summarizes the failure

modes, critical failure mechanisms and corresponding stress-

ors. More detailed discussions on them have been given in [61].

Table V gives the wear out failure criterion and typical electri-

cal parameters for the condition monitoring of capacitors.

Lifetime prediction of capacitors is mainly based on empiri-

cal models as physical based models are still not available. The

most widely used empirical model for capacitors is shown in

(2) which describes the influence of temperature and voltage

stress.

0

0 0

1 1exp

n

a

B

EVL L

V K T T

(2)

where L and L0 are the lifetime under the use condition and

testing condition, respectively. V and V0 are the voltage at use

condition and test condition, respectively. T and T0 are the

temperature in Kelvin at use condition and test condition,

respectively. Ea is the activation energy, KB is Boltzmann’s

constant (8.62×10−5 eV/K), and n is the voltage stress exponent.

Therefore, the values of Ea and n are the key parameters to be

determined in the above model.

7

TABLE IV

OVERVIEW OF FAILURE MODES, CRITICAL FAILURE MECHANISMS AND CRITICAL STRESSORS OF THE THREE MAIN TYPES OF DC-LINK CAPACITORS (WITH

EMPHASIS ON THE ONES RELEVANT TO DESIGN AND OPERATION OF POWER CONVERTERS)

Cap. type Failure modes Critical failure mechanisms Critical stressors

Al-Caps

Open circuit Self-healing dielectric breakdown VC, Ta, iC

Disconnection of terminals Vibration

Short circuit Dielectric breakdown of oxide layer VC, Ta, iC

Wear out: electrical parameter drift

(C, ESR, tanδ, ILC, Rp)

Electrolyte vaporization Ta, iC

Electrochemical reaction (e.g. degradation of oxide

layer, anode foil capacitance drop) VC

MPPF-Caps

Open circuit (typical)

Self-healing dielectric breakdown VC, Ta, dVC/dt

Connection instability by heat contraction

of a dielectric film Ta, iC

Reduction in electrode area caused by oxidation of

evaporated metal due to moisture absorption Humidity

Short circuit (with resistance)

Dielectric film breakdown VC, dVC/dt

Self-healing due to overcurrent Ta, iC

Moisture absorption by film Humidity

Wear out: electrical parameter drift

(C, ESR, tanδ, ILC, Rp) Dielectric loss VC, Ta, iC, humidity

MLC-Caps

Short circuit (typical) Dielectric breakdown VC, Ta, iC

Cracking; damage to capacitor body Vibration

Wear out: electrical parameter drift

(C, ESR, tanδ, ILC, Rp)

Oxide vacancy migration; dielectric puncture; insulation

degradation; micro-crack within ceramic VC, Ta, iC, vibration

C -capacitance, ESR-equivalent series resistance, tanδ -dissipation factor, Rp -insulation resistance, VC -capacitor voltage stress, iC -capacitor

ripple current stress, iLC -leakage current, Ta -ambient temperature.

TABLE V

WEAR OUT FAILURE CRITERION AND PARAMETERS FOR CONDITION

MONITORING OF CAPACITORS

Al-Caps MPPF-Caps MLC-Caps

Wear out

failure

criterion

(typical)

Condition

monitoring

parameters

C and ESR C Rp, C and tanδ

C0 -initial capacitance, ESR0 –initial equivalent series resistance, tanδ0 -initial

dissipation factor, Rp0 -initial insulation resistance.

However, the voltage dependency of lifetime for Al-Caps

quite depends on the voltage stress level. In [62], instead of a

power law relationship, a linear equation is found to be more

suitable to model the impact of voltage stress. In order to obtain

the physical explanations of the lifetime model variants from

different capacitor manufacturers, a generic model is derived in

[9] as shown in (3). Where a0 and a1 are constants describing the

voltage and temperature dependency of Ea. Ea0 is the activation

energy under test. It can be noted that the influence of voltage

stress is modeled as linear, power law, and exponential rela-

tionship, respectively for low-voltage stress, medium-voltage

stress and high-voltage stress. Another important observation is

that the activation energy Ea is varying with voltage and

temperature, especially under high-voltage stress condition. It is

still a challenge to determine the value of the parameters and the

boundaries of low-voltage stress, medium-voltage stress and

high-voltage stress in (3).

D. Cases Studies on the Application of IGBTs and Capacitors

in Power Converters

1) IGBT Modules in a 2.3 MW Grid-Side Wind Power Con-

verter

0

0

0 0 0

0 0 0 0 0

1 0

0

1 1exp (low voltage stress)

1 1exp ( medium voltage stress)

exp exp (high voltage stress)

a

B

n

a

B

a a

B B

V E

V K T T

EL V

L V K T T

E a V E a Va V V

K T K T

(3)

0 80%C C

0 200%ESR ESR

0 95%C C

0tan tan 3

0 1.5%p pR R

710pR

0 90%C C

0tan tan 2

8

Fig. 7. Two-level back-to-back converter for a 2.3 MW wind turbine using a

Permanent Magnet Synchronous Generator (PMSG) [9].

TABLE VI

CONVERTER PARAMETERS FOR THE CASE STUDY [9]

Topology 2L-BTB as shown in Fig. 7

Rated output active power 2.3 MW

DC bus voltage 1.1 kV DC

*Rated primary side voltage 690 V rms

Rated load current 1.93 kA rms

Switching frequency 1950 Hz

Filter inductance 132 µH

IGBT Selection I (grid side) 1.6 kA/1.7kV/125ºC, two in parallel

IGBT Selection II (grid side) 2.4 kA /1.7kV/ 150ºC, single switch

* Line-to-line voltage in the primary windings of transformer.

TABLE VII

LIFETIME PREDICTION RESULTS OF THE SELECTED IGBT MODULES

Failure mechanisms B10 lifetime (year)

Selection I Section II

Baseplate solder joints 358 24

IGBT chip solder joints 438 22

Wire bonds 2633 74

Overall (determined by the shortest one) 358 22

A case study on the lifetime prediction of IGBT modules in a

2.3 MW wind power converter has been studied in [9]. A

Two-Level Back-to-Back (2L-BTB) converter is applied in the

study as shown in Fig. 7. The technical advantage of the

2L-BTB topology is the relatively simple structure and few

components, which contributes to a well-proven robust and

reliable performance. Table VI gives the specifications and

selections of the IGBT modules. By following the prediction

procedure from wind speed profile analysis, case temperature

and junction temperature estimation, cycling counting of tem-

perature swings to parameter estimation of lifetime models, the

lifetime of two condidates of IGBT modules for the grid-side

converter is predicted in [9]. The lifetime prediction is based on

each of the three critical failure mechanisms related to thermal

cycling discussed in § III Part A. The results are shown in Table

VII. It should be noted that other failure mechanisms induced

by thermal stress or other types of stresses need also to be con-

sidered, besides those listed in Table VII.

2) DC-Link Capacitors in a 1 kW PV Inverter

Electrolytic capacitors that widely used in PV inverters are

considered as the weakest link with respect to the semiconduc-

tor devices [34] – [35]. Therefore, the case study for DC-link

capacitors is performed on a 1 kW 400 V DC-link PV inverter.

Fig. 8(a) presents a simplified structure of the inverter. The

input power of the PV inverter is assumed constant within one

cycle of the grid voltage. Fig. 8(b) shows the instantaneous

power balancing function of the input capacitor C. The nominal

input voltage of the inverter is 400 V with a maximum voltage

ripple of 5% and a maximum input voltage of 600 V. The

calculated minimum required capacitance is 398 µF and ripple

current stress is 1.8 A. A reliability-oriented design guideline

proposed in [63] is applied for the selection of the input

capacitor to fulfill 20 years of lifetime. According to the

electrical stress analysis, preliminary choices of the capacitors

are determined as shown in Table VIII. Then the thermal

stresses of those capacitors are estimated based on their specific

thermal models. The lifetime of the selected capacitors is

therefore can be estimated based on the mission profile,

operation mode and specific lifetime model. The applied

empirical lifetime models from the respective capacitor

manufacturers are consistent with the generic lifetime model

shown in (3). Finally, the optimal capacitors can be chosen by

comparing different options.

TABLE VIII

THREE KINDS OF CAPACITORS FROM DIFFERENT MANUFACTURES CONSIDERED FOR THE PV INVERTER DESIGN

Case No.

Capacitor bank Rated lifetime

(85℃)

ESR at 100 Hz (mΩ) Natural cooling thermal

resistance Rth (℃/W) 25 ℃ 45 ℃ 65 ℃ 85 ℃

1 four 350 V/470 µF /1.9A 1,000 hours 440 308 264 264 15.62

2 two 315 V/1000 µF /3.63A 2,000 hours 207 145 124 124 15.19

3 two 350 V/1000 µF/ 5.5A 24,000 hours 85 50.3 38 32.5 3.6

(a) Simplified structure.

(b) Instantaneous power flow.

Fig. 8. Single-phase grid-connected PV inverter.

9

(a) Capacitor power losses.

(b) Capacitor hotspot temperatures.

(c) Capacitor predicted lifetime.

(d) Output power de-rating curves.

Fig. 9. Simulation results of different capacitors under various ambient temper-

atures ((a)-(c) are with 1 kW output power and (d) is with minimum lifetime of

20 years).

Figs. 9(a)-(c) compare the power loss, hotspot temperature,

lifetime prediction with 1 kW output power. Fig. 9(d) plots the

power de-rating curve to fulfill the lifetime requirement. If

100,000 hours of lifetime (equivalent to 12 hours/day operation

in 20 years with a design margin of 12.4%) is required, it can be

noted from Fig. 9 (c) and Fig. 9 (d) that only the Case 3 can ful-

fill the requirement in a wide ambient temperature range. The

selection of Case 2 can only have 20 years of lifetime when the

ambient temperature is below 20℃. Therefore, the proposed

method allows the optimal selection of the input capacitors in

terms of both electrical and reliability performance.

According to Fig. 9(d), for applications when output power

de-rating is allowed, the required 100,000 hours of lifetime

could still be fulfilled for selection of Case 1 and Case 2 by load

management according to the de-rating curves.

IV. DESIGN FOR RELIABILITY AND ROBUSTNESS VALIDATION

OF POWER ELECTRONICS

The second aspect of power electronics reliability is to build

in reliability and sufficient robustness into system design thro-

ugh DFR process. Industries have advanced the development of

reliability engineering from traditional testing for reliability to

DFR [64]. DFR is the process conducted during the design

phase of a component or system that ensures them to be able to

achieve required level of reliability. It aims to understand and

fix the reliability problems up-front in the design process.

In [65], a structured approach to DFR was recommended

which include an interactive progression of key design acti-

vities by using appropriate analysis tools. Due to the difference

in chosen reliability tools and specified requirements of

products, DFR process varies with industry sectors, however,

the generic form usually covers the process of identify, design,

analyze, verify, validate and control [64]. In [66], a DFR

process is presented for aerospace systems starting from the

concept, planning and requirement, development, test and

evaluation, release and evaluate the field operation perfor-

mance.

Statistics is a necessary basis to deal with the effects of un-

certainty and variability on reliability, which is also true for

PoF based DFR process. Both empirical models and physical

based models are subjected to various kinds of uncertainty in

material properties, stress conditions, manufacture process and

accuracy of the available models [67]. For example, if the

variances of material-dependent parameters k, m and ∆T0, and

operational-stress-dependent parameter ∆T are taken into acc-

ount in (1), the predicted lifetime of the IGBT modules will be

distributed with time rather than the single fixed values as

shown in Table VII. The 2-parameter Weibull distribution is

widely applied to present the cumulative failure distribution

function [64] due to its flexibility to model different trends of

the failure level with time. In [68], the probabilistic based PoF

models have been developed for plastic package corrosion.

Moreover, Monte-Carlo simulation is another important statis-

tics tool to handle uncertainties to analyze the robustness mar-

gin, confidence level, and so on [69]. However, as the variation

is often a function of time and operating condition, statistics

itself is not sufficient to interpret the reliability data without

judgment of the assumptions and non-statistical factors (e.g.

modification of designs, new components, etc.).

A systematic DFR procedure specifically applicable to the

design of power electronic products is presented in [9] and

shown in Fig. 10. By implementing the procedure, reliability is

well considered and treated in each development phase (i.e.

concept, design, validation, production and release), especially

in the design phase. The design of power electronic converters

10

Fig. 10. State-of-the-art reliability design procedure for power electronics.

is mission profile based by taking into account large parametric

variations (e.g. temperature swings, solar irradiance level

changes, wind speed fluctuations, load changes, manufacturing

process, etc.). Important concepts (except for PoF approach

which has been discussed in § III) and design tools shown in

Fig. 10 are discussed as follows. More detailed discussions are

given in [9].

A. Load-Strength Analysis

Load-strength analysis is an important method in the first step

of the design phase shown in Fig. 10. A component fails when

the applied load exceeds the design strength. The load refers to

a kind of stress (e.g. voltage, cyclic load, temperature, etc.) and

the strength refer to any resisting physical property (e.g.

harness, melting point, adhesion, etc.) [64]. Load and strength

of power electronic components are allocated within a certain

interval which can be described by a specific probability den-

sity function (e.g. normal distribution). Moreover, the strength

of a material or device could be degraded with time. Theoreti-

cally, the probability of failure can be obtained by analyzing the

overlap area between the load distribution and the strength

distribution. From another prospective, it implies that failure

could be reduced or eliminated within service life by either

design with an increased strength (i.e. an increased design

margin), or with a reduced load by control (i.e. stress control or

load management), or both. Practically, the exact distributions

of load and strength are very often not available, Monte Carlo

simulation [64] can be applied to randomly select samples from

each distribution, compare them and thus roughly estimate the

probability of failure.

B. Reliability Prediction Toolbox

Reliability prediction (not based on constant failure rate λ) is

an important tool to quantify the lifetime, failure level and

design robustness based on various source of data and

prediction models. Fig. 11 presents a generic prediction toolbox

based on the PoF approach. The toolbox includes statistical

models and lifetime models and various sources of available

data (e.g. manufacturer testing data, simulation data and field

data, etc.) for the reliability prediction of individual com-

ponents and the overall system. The statistical models are well

presented in [64], while the number of physical based lifetime

models available for power electronic components is still

limited. Research efforts to both accelerated testing and

advanced multidisciplinary simulations will be beneficial to

obtaining those lifetime models. A more detailed step-by-step

procedure for lifetime prediction is presented in [70].

11

Fig. 11. Reliability prediction toolbox for power electronic systems.

TABLE IX

SUMMARY OF SYSTEM LEVEL RELIABILITY PREDICTION METHODS

Reliability Block Diagram (RBD) Fault Tree Analysis (FTA) Markov Analysis (MA)

Concepts RBD is an analytical technique graphically

representing the system components and their reliability-wise connections (from

simple series-parallel to complex) by a logic

diagram based on the system characteristics.

FTA is an analytical technique using a

top-down approach to analyze various system combinations of hardware, software

and human failures (i.e. sub events) that

could cause the system failure (i.e. top event).

MA is a dynamic state-space analytical

technique presenting all possible system states (i.e. functioning or failed) and the

existing transitions between these states.

Elements Rectangle blocks

Direction lines

Failure level and time of the

component/subsystem represented by each blocks

Events (i.e. initiating fault events,

intermediate events and top event)

Logic gates (e.g. AND, OR and more

complex ones)

Probability of each event

States (i.e. functioning or failed)

Transitions between states

Transition rates based on failure rates

and repair rates of components/ subsystems

Outcome System level reliability System level reliability

Identified all possible faults (similar to the results from FMEA)

System level reliability

System availability

Applications For non-repairable systems

Without redundancy

With redundancy

For non-repairable systems

Without redundancy

With redundancy

Mainly for repairable systems

Without redundancy

With redundancy

Advantages Simplicity and ease of application All factors including human factors

could be taken into account

Useful also for identifying failure causes

and design problems

Dynamic (i.e. represent state of every

component at any time and the

dependences among them)

Applicable for repairable systems

Disadvantages/

Limitations

Limitation in considering external events (e.g. human factor) and priority of events

Dependencies among components or

subsystems are not well treated

Dependencies among components/sub-systems are not well treated

State-based models easily get large (e.g. maximum 2n states with n components)

Primarily applicable for constant failure

rate and constant repair rate (which

works in theory only)

To map the reliability from component level to the system

level [3], Reliability Block Diagram (RBD), Fault-Tree Analy-

sis (FTA) and state-space analysis (e.g. Markov analysis) are

widely applied as summarized in Table IX.

It should be noted that the tabulated three methods are

conventionally applicable to constant failure rate cases, which

are corresponding to the handbook based reliability prediction

methods. The PoF based system level reliability prediction is

12

still an open research topic even in microelectronics [16] and

[18]. Interactions among different failure mechanisms will

bring additional complexity for the analysis. Therefore, it was

argued that the PoF approach is not practical for assessing an

entire system in [12]. Moreover, it should be noted that the

system reliability depends not only on components, but also on

packaging, interconnects, manufacturing process, and human

errors. The latters need also to be treated properly for a more

accurate reliability assessment.

V. INTELLIGENT CONTROL AND MONITORING OF POWER

ELECTRONIC SYSTEMS

After power electronic systems have been designed, their

reliability could be further improved through control and

condition monitoring. This is the third important aspect shown

in Fig. 1(b). Among many options, three main actions can be

taken to increase the reliability of power electronic systems:

prognostics and health management, active thermal control for

reducing temperature and temperature swing that are the main

killing factors of power device modules and fault tolerant

operation to continue operate the system even in case of fail-

ures. The last can be considered as an alternative measure with

respect to the first two or like the last attempt to make the

system operating if it was not possible to predict failures or to

avoid them. Of course all these actions entail important invest-

ments in terms of devices, sensors and control actions and even

request redundancies. All of them shall be evaluated in terms of

cost respect to the specific application.

A. Prognostics and Health Management

The Electronic Prognostics and Health Management Re-

search Center at the University of Maryland has categorized the

main approaches as: use of fuses and canary devices, built-in-

-test (BIT), monitoring and reasoning of failure precursors, and

modeling accumulated damage based on measured life-cycle

loads [71].

Apart from the first category that relies on the presence of

devices that fail before the main one (like the canary in a mine

full of hazardous gas), the three other categories need: 1) sen-

sors to check the functionality of a device or circuit, like in case

of BIT, to monitor precursors of the failure or to measure cycles

whose number can be correlated to failure and 2) data-logging

to store the data coming from sensors. Accordingly, Fig. 12

shows the configurations for the prognostics and health

management. The last three categories can in part overlap with

the concept of condition monitoring that refers to on-line

monitoring of the device. In case of power semiconductor this

can be done by modifying the gate driver circuit.

Different sensors can be employed and can be classified in

two categories: ambient sensors (temperature, humidity and

pollution) and internal sensors (module temperature, vibration,

electrical parameters). Since the main failure cause for power

module is the junction temperature swing, measuring it or esti-

mating by means of Thermo-Sensitive Electrical Parameters

(TSEPs) is one of the most interesting challenges [72]. In fact

sensing the junction temperature during converter operation is

notoriously difficult - direct access to chips is prevented by mo-

dule packaging and dielectric gel, which therefore limits the

optical and physical contact methods such as the use of infrared

cameras or optical fibers.

Electrical methods allow the measurement of temperature

without any physical alteration to a device. However, one

disadvantage compared to optical or physical contact methods

is that the latter can be used to measure the temperature at

specific points in the die or in the module. Electrical methods

generally give an average temperature across the die. For

instance, the voltage drop across a PN-junction is known to

vary with temperature - a measurement of this voltage can

therefore be used to derive a temperature solely for the junction.

However, this perhaps does not give a reliable enough estima-

tion of temperature elsewhere in the devices, such as in bond

wires, solder joints, etc.

Data acquisition is very important since once determined the

important quantities to be sensed or estimated, there are issues

related to the amount of data that is possible to store and how to

use those data. Hence developing a data-acquisition system

taking into account both the ambient and the internal quantities

can be a challenge [73].

The goal is to have the real-time operating characteristics and

the health conditions of the components (particularly of the

power modules and of the capacitors) and of the overall power

converter [74].

This information can be used for two main goals: implement

a proactive maintenance plan (i.e. prognostic maintenance) and

provide information for proactive control schemes that can be a

simple load management (i.e. reduction or sharing of the load

among different units) or the more advanced active thermal

control, briefly introduced in the following.

B. Active Thermal Control

The thermal analysis of power converters, especially in case

of more complex structures like multilevel or multi-cell ones,

reveals that some of the power semiconductor devices can be

more stressed with respect to others and this difference can be

even more evident in some particular conditions like those

caused by system faults [75]. Hence the possibility to modify

Fig. 12. Prognostics and health management of power electronic systems.

13

the modulation and control of the power converter using as a

feedback the junction temperature of the most stressed device is

an appealing possibility. The more straightforward approach is

manipulating the switching frequency and the current limit to

regulate the losses and prevent over-temperature or to reduce

temperature swing [76]. In view of controlling the junction

temperature, estimating it by means of TSEP, as already men-

tioned, or using an observer based on FEM modeling of the

device [76] are two interesting alternatives to the more expen-

sive ones by using of integrated sensors in the chip [77].

Fig. 13 gives the general block diagram for active thermal

control of the power semiconductors once the junction temper-

ature is measured or estimated. The easiest way is to change the

switching frequency [78]-[79] to control the junction temper-

ature. In case of parallel power converters that present some

redundancies it is also possible to share the load among the

different units also in view of controlling the temperature swing

[80]. Another alternative is to circulate reactive power among

the different power converters connected in parallel in a high

power converter or in a wind or photovoltaic park to reduce the

temperature swing in the most stressed power semiconductor

devices [81]. The idea can be applied only in case of power

converters like the neutral-point-clamped inverters where there

is an uneven distribution of power losses and as a consequence

of the temperature of the power semiconductor devices, being

this difference even bigger in some particular stressing cir-

cumstances like in the case of sudden power changes (e.g. for a

wind gust), grid faults or variable atmospheric conditions. The

main drawbacks are: higher losses and higher mean tempera-

ture of the most stressed device but also of the other devices.

However, one risk is to move the stress from bond wires to

solder joints.

C. Fault Tolerant Operation

Working outside the Safe Operating Area (SOA) leads power

semiconductors to damage. The main failure causes are: fault

currents either over-current, short-circuit current or earth fault

current, over-voltages, over-temperature and cosmic radiation

[54]. Other problems may arise because of the driver of the

power semiconductor: malfunctioning of the driver board,

Fig. 13. Active thermal control of the power semiconductor junction tempera-

ture Tj by means of y (switching frequency, reactive power or any other

quantity that can modify the power semiconductor losses). Tj is obtained by using an estimator based on TSEP (Thermo-Sensitive Electrical Parameter) or

an observer using measured voltages and currents.

Fig. 14. Inverter faults considered: (a) single switch short-circuit, (b) phase--leg short-circuit, (c) single switch open-circuit, and (d) single-phase open-

-circuit [83].

Fig. 15. Switch redundant topology for fault tolerant control [83].

Fig. 16. Redundancies by connecting IGBTs in parallel or in series [84].

Fig. 17. Fault-tolerant voltage source inverter by adding extra leg for more electrical aircraft application [86].

14

auxiliary power supply failure or dv/dt disturbance. As a con-

sequence five main types of faults can be identified: single

switch short-circuit (power semiconductor is de-saturated

working as current source or it is a physical short-circuit),

phase-leg short-circuit, single switch open-circuit, single-phase

open-circuit, intermittent gate-misfiring [82]. Fig. 14 describes

the first four types of faults.

Three levels of protections can prevent failures or limit their

effects: fast (in the switch, 10 ns), slow (outside the switch) and

very slow (system level). Several diagnostic methods can be

used to detect failures and they can be mainly classified in those

used for open-switch failure or closed-switch failure and in

software one or hardware one. Generally software methods are

more suitable in case of open-switch failure while closed-

-switch failures need a fast detection because they can lead to

destructive failure of the overall system, the desaturation one is

the most famous [82]. Once a fault is detected and isolated or

on-line repair is implemented, the system can continue to

operate safely and fault tolerant operation can be implemented.

There are already several simple solutions implemented in

industry also without any redundancy if operation with high

harmonic content and lower power level can be accepted [83]

as shown in Fig. 15. Otherwise redundancies based on para-

lleling or connecting in series power semiconductor devices

[84] as shown in Fig. 16 is the simplest and most adopted

solution in industry and use of devices that can continue to

operate in short-circuit like press-pack IGCT can help. The next

step in using redundancy to improve fault-tolerant operation is

in adding extra legs to the power converter. The procedure

consists of the following steps: 1) detection of the faulty leg, 2)

stop the control signal for the two switching drivers of the

faulty leg, 3) trigger the bidirectional switch connecting the

new leg, 4) use the control signals of the faulty leg for the

redundant one. The use of fast digital computational devices

[85] and the integration in the power module of the extra leg

and of a thyristor that can survive high energy pulses [86] are

the enabling technologies to isolate a faulty leg and on-line

substitute it with a healthy one. The latter has been developed

within an EU project for more electric aircraft as shown in Fig.

17, and this is an interesting sign of the importance of fault

operation capability solutions that should be designed to

guarantee high reliability in safety critical applications.

The last two solutions to guarantee fault-tolerant operation

entail larger investments at system level and in general a signi-

ficant shift in the power converter design: multiphase power

converters and machines [87]-[88] and use of parallel or series

connection of power converters [89]-[90]. Fig. 18 and Fig. 19

show the redundancy achieved by connecting converters in

parallel and in input-series output-parallel, respectively. Both

of the solutions have been proposed and in some cases imple-

mented in the aforementioned more electric aircraft [88]-[89].

Particularly connection in series and/or in parallel power con-

verters is already widely adopted in dc/dc converters and

requires the power modules to be identical and capable of

working independently as the case shown in Fig. 19. Moreover

the faulted module(s) must be quickly isolated from the system,

which is not always easy during operation of the power

converter especially taking into account the associated

transients that should be minimized to avoid damage of the

healthy modules while replacing the faulty ones.

VI. CONCLUSION AND OUTLOOK

Reliability is an important performance index of power

electronic systems. The status and future trends of design for

reliability in power electronics are presented in this paper. A

paradigm shift in reliability research on power electronics has

left simple handbook based on constant failure rate for the PoF

approach and DFR process. Accordingly, three major aspects

of power electronics reliability are discussed: the PoF analysis

of reliability critical components (e.g. IGBT modules and

DC-link capacitors) and two associated study cases; the

state-of-the-art DFR process and robustness validation for

power electronic systems; the prognostics and health

management, active thermal control and fault-tolerant stra-

tegies for reliable field operation.

Joint efforts from engineers and scientists in the multiple

Fig. 18. Redundancy achieved by connecting converters in parallel [89].

Fig. 19. Common duty ratio, automatic master-slave control scheme with

identical and independent modules for input-series, output-parallel connection

[90].

15

disciplines are required to fulfill the research needs and pro-

mote the paradigm shift in reliability research. The major

challenges and opportunities in the research on reliability for

power electronic systems are addressed as follows:

A. Challenges

Pervasive and fast implementation of power electronics in

a large variation of applications with all kind of environ-

mental exposures.

Outdated paradigms and lack of understanding in the de-

sign for reliability process in power electronics.

Uncertainties in mission profiles and variations in strength

of components.

Increasing electrical/electronic content and complexity.

Lack of understanding in failure mechanisms and failure

modes of reliability critical components.

Traditional system level reliability prediction methods are

based on constant failure rates. However, physics-of-

failure based component level reliability prediction results

in varying failure level with time.

Resource-consuming testing for reliability prediction and

robustness validation from components to entire systems.

End up with ppm level return rates for mass-manufactured

power electronic products.

Higher operating temperature (e.g. with wide band-gap

devices) which challenges the overall reliability and life-

time.

Software reliability becomes an issue with more and more

digital controllers are introduced in power electronic sys-

tems, which should be treated adequately.

B. Opportunities

The research in microelectronics provides an important

foundation for the ongoing and future work in power

electronics, especially from the methodologies point of

view.

More and more mission profiles and on-line monitoring

data from the field are available and accessible.

Physics-of-failure approach provides insights to avoid

failures in power electronic components, circuits and sys-

tems.

Active thermal control by controlling the power flow in

power electronic circuits.

Component level and system level smart de-rating opera-

tion.

Condition monitoring and fault tolerant design which

allow extended lifetime and reduced failure rate.

Emerging semiconductor and capacitor technologies en-

able more reliable power electronic components and sys-

tems.

Computer-aided automated design software to save time

and cost in the development process.

Trends for modular design of power converters and stan-

dardized power electronic components and packaging

technologies.

With better understanding of failure mechanisms in power

electronics, more failure mechanism specific accelerated

testing could be designed, leading to improved reliability

predictions for targeted applications.

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Huai Wang (S’07–M’12) received the

B.Eng. degree in Electrical and Electronic

Engineering from Huazhong University of

Science and Technology, Wuhan, China, in

2007, and the Ph.D. degree in Electronic

Engineering from City University of Hong

Kong, Kowloon, Hong Kong, in 2012.

Since 2012, he has been with Aalborg

University, Denmark, where he is currently an Assistant

Professor in the Department of Energy Technology. He was a

Visiting Scientist at Massachusetts Institute of Technology

(MIT), USA, during September to November, 2013. His

industry experience in power electronics includes 6 months’

work at the ABB Corporate Research Center, Baden,

Switzerland, in 2009. His research interests include the

reliability of DC-link capacitors, reliability of power electronic

systems, high-voltage DC-DC power converters, time-domain

control of converters, and passive components reduction

technologies. On the above research topics, he has contributed

over 40 journal and conference papers and filed 3 patents.

Dr. Wang is the recipient of 5 paper awards and project

awards from industry, IEEE and the Hong Kong Institution of

Engineers (HKIE). He serves the guest Associated Editor of

IEEE Transactions on Power Electronics Special Issue on

Robust Design and Reliability in Power Electronics, and

session chair of various conferences in power electronics.

Marco Liserre (S’00-M’02-SM’07-F’13)

received the MSc and PhD degree in

Electrical Engineering from the Bari

Polytechnic, respectively in 1998 and

2002. He has been Associate Professor at

Bari Polytechnic and Professor in reliable

power electronics at Aalborg University

(Denmark). He is currently Full Professor

and Chair of Power Electronics at

Christian-Albrechts-University of Kiel (Germany). He has

published 168 technical papers (44 of them in international

peer-reviewed journals), 3 chapters of a book and a book (Grid

Converters for Photovoltaic and Wind Power Systems,

ISBN-10: 0-470-05751-3 – IEEE-Wiley, also translated in

Chinese). These works have received more than 6000 citations.

He has been visiting Professor at Alcala de Henares University

(Spain).

He is member of IAS, PELS, PES and IES. He is Associate

Editor of the IEEE Transactions on Industrial Electronics, IEEE

Industrial Electronics Magazine, IEEE Transactions on

Industrial Informatics, where he is currently Co-EIC, IEEE

Transactions on power electronics and IEEE Journal of

Emerging and Selected Topics in Power Electronics. He has

been Founder and Editor-in-Chief of the IEEE Industrial

Electronics Magazine, Founder and the Chairman of the

Technical Committee on Renewable Energy Systems,

Co-Chairman of the International Symposium on Industrial

Electronics (ISIE 2010), IES Vice-President responsible of the

publications. He has received the IES 2009 Early Career

Award, the IES 2011 Anthony J. Hornfeck Service Award, the

2011 Industrial Electronics Magazine best paper award and the

Third Prize paper award by the Industrial Power Converter

18

Committee at ECCE 2012, 2012. He is senior member of IES

AdCom. He has been elevated to the IEEE fellow grade with

the following citation “for contributions to grid connection of

renewable energy systems and industrial drives”.

Frede Blaabjerg (S’86–M’88–SM’97–

F’03) was with ABB-Scandia, Randers,

Denmark, from 1987 to 1988. From 1988

to 1992, he was a Ph.D. Student with

Aalborg University, Aalborg, Denmark.

He became an Assistant Professor in 1992,

an Associate Professor in 1996, and a Full

Professor of power electronics and drives

in 1998. He has been a part time Research Leader with the

Research Center Risoe in wind turbines. From 2006 to 2010, he

was the Dean of the Faculty of Engineering, Science, and

Medicine and became a Visiting Professor with Zhejiang

University, Hangzhou, China, in 2009. His current research

interests include power electronics and its applications such as

in wind turbines, PV systems, reliability, harmonics and

adjustable speed drives.

He received the 1995 Angelos Award for his contribution in

modulation technique and the Annual Teacher Prize at Aalborg

University. In 1998, he received the Outstanding Young Power

Electronics Engineer Award by the IEEE Power Electronics

Society. He has received 15 IEEE Prize Paper Awards and

another Prize Paper Award at PELINCEC Poland in 2005. He

received the IEEE PELS Distinguished Service Award in 2009,

the EPE-PEMC Council Award in 2010 and the IEEE William

E. Newell Power Electronics Award 2014. He has received a

number of major research awards in Denmark. He was an

Editor-in-Chief of the IEEE TRANSACTIONS ON POWER

ELECTRONICS from 2006 to 2012. He was a Distinguished

Lecturer for the IEEE Power Electronics Society from 2005 to

2007 and for the IEEE Industry Applications Society from 2010

to 2011. He was a Chairman of EPE in 2007 and PEDG,

Aalborg, in 2012.

Peter de Place Rimmen is today

Reliability Advisor at Danfoss Power

Electronics A/S in Denmark since 2009.

Peter has worked with practical approach

implementing Reliability during the last 25

years in followed companies: Vestas Wind

System R&D from 2004 to 2009, Grundfos

Management R&D from 1997 to 2004 and

Bang & Olufsen R&D form 1988 to 1997.

Before that he had careers (14 years) at B&O as Constructor,

Test engineer, Plant manager and Project manager. Peter had

for some time participated in IEC dependability group. Peter

has together with Nokia trained Nokia R&D and Vestas R&D

people around the world in “Design for Quality and Reliability”.

Today Peter is participating in CORPE Centre of Reliable

Power Electronics at Aalborg University, participating in ZVEI

“facts sheets group” for Robustness Validation, ECPE Course

instructor, board member FAST (Danish Society for Applied

Statistics) and initiated in 2001 and member of the Danish Six

Sigma ERFA-group, subgroup of FAST.

Peter holds 1½ patent for Vestas concern Lifetime

improvement by thermal control improvements, and for

Danfoss he hold 2 patents concern Dehumidifier for enclosures

and one 1 patent for Monitoring device usage for stress in the

field.

John B. Jacobsen was born in Hørning,

Denmark, in 1960. After practical educa-

tion to electrician he received B.Sc. El.Eng

from Aarhus Teknikum, Aarhus in 1985.

Main work experience is from Grundfos,

Denmark; 7 years in hybrid technology

development, 7 years in hybrid production

& more than 10 years as chief specialist in

integration of power electronics into products, i.e. mechatronic

disciplines including thermal management, interconnection,

fixation, protection from environment (impact, humidity, ....),

reliability & cost. Optimization criterion being needed perfor-

mance & reliability at lowest possible cost. Generalist in

understanding value chain and all the disciplines that meet in

the physical mechatronic reality, i.e. function trade-offs in

design and produce ability in production.

Thorkild Kvisgaard was born in Fabjerg

Denmark in 1958. After the practical

education as electrician he received a

B.Sc.E.E from Aarhus Teknikum in 1984.

In addition he received an e-MBA in

Innovation and Technology Management

from Aalborg University in 2006. Main

work experience is from Scanvaegt Inter-

national where he in 10 years was Manager of Electronics

Development creating solutions for the food industry as well as

electronics for offshore applications.

In 1994 he joined Grundfos and served as a Product

Development Manager in 11 years. After this Thorkild

Kvisgaard changed position in Grundfos to Global Technology

Manager. In addition he became a Member of the Board in

“Center for Electrical Energy Systems (CEES)” in 2006 and he

act as Chairman of the Center for ”Intelligent and Efficient

Power Electronics” (IEPE). In the “Center Of Reliable Power

Electronics” (CORPE) Thorkild Kvisgaard has the role as Vice

Chairman. He had several patents granted and was nominated

for the best Danish patent granted 1992.

Jørn Landkildehus was born in Ebeltoft,

Denmark, in 1969. He received the M.Sc.-

E.E. from Aalborg University, Aalborg,

Denmark, in 1995. Since 1995 he is with

Danfoss Power Electronics engaged with

development of variable speed drives and

research in power topologies. He has been

specializing in the design for EMC and in

recent years been leading reliability engin-

eering department at Danfoss Power Electronics. His technical

interest include development processes, multi-disciplinary

design techniques and Design for Reliability.