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A design tool to study the impact of mission-profile on the reliability of SiC-based PV-inverter devices
Microelectronics Reliability 54 (2014) 1655–1660
Contents lists available at ScienceDirect
Microelectronics Reliability journal homepage: www.elsevier.com/locate/microrel
A design tool to study the impact of mission-profile on the reliability of SiC-based PV-inverter devices N.C. Sintamarean a,⇑, H. Wang a, F. Blaabjerg a, P.de P. Rimmen b a b
Department of Energy Technology, Center of Reliable Power Electronics, Aalborg University, Pontoppidanstraede 101, 9220 Aalborg, Denmark Danfoss Power Electronics, R&D Design Center Europe, 6300 Graasten, Denmark
a r t i c l e
i n f o
Article history: Received 27 June 2014 Accepted 8 July 2014 Available online 23 August 2014 Keywords: Mission-profile variation Device-degradation feedback Long term simulation Power electronics devices reliability
a b s t r a c t This paper introduces a reliability-oriented design tool for a new generation of grid connected PV-inverters. The proposed design tool consists of a real field mission profile model (for one year operation in USA-Arizona), a PV-panel model, a grid connected PV-inverter model, an electro-thermal model and the lifetime model of the power semiconductor devices. A simulation model able to consider one year real field operation conditions (solar irradiance and ambient temperature) is developed. Thus, one year estimation of the converter devices thermal loading distribution is achieved and is further used as an input to a lifetime model. The proposed reliability oriented design tool is used to study the impact of MP and device degradation (aging) in the PV-inverter lifetime. The obtained results indicate that the MP of the field where the PV-inverter is operating has an important impact in the converter lifetime expectation, and it should be considered in the design stage to better optimize the converter design margin. In order to improve the accuracy of the lifetime estimation it is crucial to consider also the device degradation feedback (in the simulation model) which has an impact of 30% in the precision of the lifetime estimation in the studied case. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The converter availability in PV-system applications is one of the most important aspects and it depends mostly on the component reliability and its maintenance [1,2]. Therefore, highly reliable components are required in order to minimize the downtime during the lifetime of the converter and implicitly also limit the maintenance costs [3,4]. Even if the typical design target of the lifetime for PV-systems is around 20 years, there is a discrepancy between the lifetime of the PV-inverter (typically 5–10 years) and the PV-panel (20–25 years). The system reliability can be improved by replacing devices before their failure [4,5]. Great variations of the PV-inverters lifetime are encountered due to the Mission Profile (MP) variation from one region to another. Therefore, in order to achieve reliability improvement and cost reduction of the PV-technology, it is of major importance to predict the lifetime of the PV-inverter, according to the MP operating conditions. The loading stress (e.g. thermal loading of devices, cyclic load, voltage etc.) of the PV-inverter devices is a
⇑ Corresponding author. Tel.: +45 2392 9795. E-mail address: [email protected] (N.C. Sintamarean). http://dx.doi.org/10.1016/j.microrel.2014.07.055 0026-2714/Ó 2014 Elsevier Ltd. All rights reserved.
consequence of the MP variations. Moreover, the device strength model is a consequence of the any resisting physical properties (e.g. hardness, melting point, adhesion, etc.) which defines how much loading the component can withstand [2]. A component failure occurs when the applied stress exceeds the designed strength. By analysing the overlap area between the stress-strength distributions, the probability of failure can be obtained (Fig. 1). Therefore, stress and strength, are two of the most important factors which have to be considered for lifetime or reliability estimation of PVinverters. Moreover, the MP will have an impact in the device degradation (D) influencing the failure distribution as shown in Fig. 1. The device strength is well known, thus the main factor which influence the failure distribution is the MP, which usually is not taken into consideration by the producers in the design stage of the PV-inverters. This is the main reason why PV-inverter lifetime varies so much. In order to avoid overdesign-underdesign of the product, a proactive measure can be taken from the design phase by selecting an optimum design margin in respect with the stress margin. This paper proposes a reliability oriented design tool for the new generation of SiC-based grid connected PV-inverters in order to study the impact of mission profile and device degradation in the PV-inverter lifetime.
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Load Stress
Device Strength
Occurance
Ideal Case Without Degr.
time of the measured data is one minute. Thus a realistic loading of the converter devices can be achieved, taking into account short time and longer time variations.
Failures
2.2. PV-panel model
(MP) Stress Distribuon (D) Strength Distribuon Design Margin Fig. 1. Stress–strength analysis emphasize the failure due to MP variation and device aging.
The PV-panel model estimates the output current and voltage by considering as input the solar irradiance (G) and the ambient temperature (Ta) from the MP model. The model considers the configuration of the PV-panel connection and finally estimates the PVinverter DC-Link voltage and current variations. Considering the Maximum Power Point Tracking (MPPT) strategy, the references for the converter voltage and current are obtained.
2. Proposed reliability oriented design tool 2.3. PV-inverter model This paper introduces a reliability oriented design tool for the new generation of SiC-based grid connected PV-inverters. According to Fig. 2, the proposed design tool consists of a real field mission profile model, a PV-panel model, a grid connected PVinverter model, an electro-thermal model and a Lifetime model. The involved parameters emphasized in Fig. 2 are as follows: G – solar irradiance, Ta – ambient temperature, VDC-Link – DC-Link voltage, Iconv – converter output current, IM – MOSFET drain current, ID – freewheeling diode current, VDC – device off-state voltage, Fsw – switching frequency of the device, Zth_device/grease/heatsink – junction to case/grease/heatsink thermal impedance, Tj – device junction temperature, VG – gate voltage, RG – gate resistance, TC – case temperature of the device, D – device degradation (aging). A description of each model is presented as follows:
The proposed PV-system, depicted in Fig. 3, consists of a 25 kVA SiC-based 2 Level Full Bridge (2L-FB) inverter connected to the three phase grid through a passive LCL-filter. Table 1 presents the PV-system design ratings. Fig. 3 introduces the main control blocks, which are used to achieve the desired converter functionalities. A more detailed description of the grid connected PV-inverter control design has been presented in [6]. The PV-inverter model receives as input the reference current and voltage from the MPPT. By considering the input, the model estimates the realistic device (MOSFET and Diode) loading current (IM or ID) and the voltage variations (offstate voltage VDC). 2.4. Electro-thermal model
2.1. Real field mission profile model The proposed design tool presented in Fig. 2 considers the Mission Profile (MP) of the real field where the converter will operate. In order to study the impact on the PV-inverter devices reliability, the mission profile model is developed based on one year measurements of solar irradiance (G) and ambient temperature (Ta) of harsh environment conditions from USA-Arizona. The sampling
The proposed model aims at estimating the junction and case temperature for the new generation of power electronics devices. The input signals in the model are: the realistic device (MOSFET and Diode) loading current (IM or ID) and voltage variations (offstate voltage VDC), the switching frequency (fSW), the ambient temperature (Ta), the gate-driver operation point (VG and RG) and the device degradation level (D).
Fig. 2. Proposed reliability oriented design structure for the new generation of grid connected PV-inverters.
N.C. Sintamarean et al. / Microelectronics Reliability 54 (2014) 1655–1660
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Fig. 3. Three phase grid connected 2L-FB PV-inverter application.
Table 1 PV-system design ratings. 3L-FB VSI PV-inverter specifications Rated power Conv. output phase voltage Max. output current Max. DC-link voltage Switching frequency
S = 25 kVA VN = 230 V (RMS) (325 V peak) Imax = 37 A (RMS) (52 A peak) VDC-max = 1000 V fsw = 50 kHz
Thermal impedance values Heatsink Thermal grease
s = 570 (s) s = 1.3 (s)
Rth = 0.13 (K/W) Rth = 0.0059 (K/W)
LCL-filter parameters Parameters
LC = 4e4 H
Lg = 1.5e4 H
Device characteristics Device type
CREE MOSFET module (CCS050M12CM2)
PV-Panel characteristics-connection PV-panel type Conn. type
ET black module (ET-M660250BB) Series = 24
According to Fig. 5, three types of models are involved in the electro-thermal analysis: the device model, the power loss model and the thermal model. The device model estimates the voltage drop across the device and the switching energies as a function of the current, the off-state blocking voltage and junction temperature. Furthermore, the estimated parameters and the switching frequency will be used into the power loss PLoss model where the instantaneous conduction and switching losses of the device are calculated. The total losses (Ptotal_loss) and the ambient temperature
99.2
Efficiency [%]
99 98.8 98.6 98.4 98.2 98
Measured Eff.
97.8
0
Cf = 0.4 lF
5
10
15
Estimated Eff. 20
25
Power [kW] Fig. 4. Estimated and measured efficiency curve of the SiC-based 2L-FB PV-inverter.
Parallel = 3
(Ta) are feed into the thermal model which estimates the device case temperature (Tc) and the junction temperature (Tj). Moreover, by providing the junction temperature as a feedback to the device model, the temperature impact in the losses is also considered. Finally, the device degradation (D) and gate-driving strategy (GDs) influence into the junction and the case temperature estimation are also included as follows: Device degradation (analyzed in Section 2.5) in terms of junction to case thermal impedance degradation (given by solder fatigue) and on-state resistance degradation (given by bondwire lift-off). Gate-driving strategy impact in terms of VG and RG variations. By combining the Shockley model of the diode [7] with the resistance model, an accurate estimation of the device parameters in the whole working area has been achieved. A detailed description of the proposed electro-thermal model has been presented in [8]. In order to validate the proposed electro-thermal model in a PVinverter application, the design of 25 kVA grid connected PV-inverter has been performed in agreement with the power rating parameters given in Table 1. A detailed description of the PV-inverter hardware implementation has been presented in [9].
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Fig. 5. Proposed electro-thermal model structure for device junction and case temperature estimation.
The PV-inverter simulation and the laboratory test are performed at the same conditions. The main purpose is to measure the PV-inverter devices (MOSFET power-module) efficiency for different active power levels injected into the grid. The efficiency is measured for power ratings from 0 to 25 kW with load steps of 2.5 kW, by using the Yokogawa WT3000 power analyzer [9]. According to the obtained results presented in Fig. 4, it is worth to mention that the model is performing a good estimation of the power losses in the whole working area range. The largest deviation from the experimental measurements (being of 7% in terms of power-losses) is in the low power operation. 2.5. Device lifetime model Since the intensive work on the power cycling testing of SiC power devices is still undergoing, well-developed degradation models and lifetime models are still unavailable for the analyzed SiC power-module. For demonstrating the procedures of the proposed design tool, the state-of-the-art lifetime models of Si IGBT modules are applied for the SiC devices. Therefore, the results of the lifetime evaluation could be interpreted for relative evaluation and for comparison only. A more relevant lifetime evaluation is upon the replacement by the specific lifetime models of the SiC power-modules in future. The procedures in the proposed design tool are still valid. There are various failure modes for power electronics devices. Two of the most commonly observed (packaging related) failures are die-attach solder fatigue and bond-wire damage [10–12]. They are both caused by temperature cycling during operation and Thermal Expansion Coefficient (CTE) mismatch between adjacent layers. Bond-wire damage is more pronounced after die-attach solder is seriously degraded [13,14]. The solder fatigue will not destroy the device directly, whereas the end of life failure is bond-wire damage related [10,14]. Therefore, device junction temperature (mean junction temperature Tj and junction temperature variation DTj) is one of the critical parameters required for lifetime estimation. The failure criteria are defined based on previous research works [10,15,13]. Thus, [10,15] claims that 10% increase of on-state voltage VDS indicates the bond-wire damage. Moreover, [10,13] suggested that a 40% increase of junction to case thermal resistance Rth_jc indicates the solder-fatigue failure. The Rth_jc has a linear degradation behavior with lifetime level and VDS is mainly changing in the last stage of the lifetime (from 80% to 100%) [10]. Table 2 presents the degradation impact on Rth_jc and VDS with lifetime level. As shown in Fig. 5, the degradation (of Rth_jc and VDS) is provided as a feedback in the electro-thermal model, thus the degradation impact in the losses is also included. As a tradeoff between accu-
Table 2 Device degradation with lifetime level. Lifetime level
1. 2. 3. 4. 5.
0–20% 20–40% 40–60% 60–80% 80–100%
Degradation-aging impact Normalized Rth_jc
Normalized VDS
1 1.1 1.2 1.3 1.4
1 1 1.01 1.03 1.1
racy and simulation time, five degradation levels are included according to Table 2. The lifetime model (SKiM 63) proposed by Semikron is used for the device lifetime estimation [16]. The model uses as a base-line the LESIT lifetime model [15]. Moreover, the dependency on the: wire bond aspect ratio (ar), load pulse duration (ton) and on the freewheeling diode chip thickness (fDiode) are also considered. The lifetime equation which expresses the number of cycles to failure (Nf) is described by (1).
Ea C þ t yon ar b1 DT j þb0 fDiode Nf ¼ A DT aj exp K B T jm Cþ1
ð1Þ
Moreover, Table 3 presents the parameters values used in the model. 3. Lifetime analysis of PV-inverter devices The proposed reliability oriented design tool is used to study the impact of the MP-variation and device aging degradation in the PV-inverter lifetime. For this purpose the simulation has been performed (using the GD parameters: VG = 15 V and RG = 20 O) with and without considering the device aging impact feedback.
Table 3 Device lifetime parameters. Parameter
Value
Technology factor: A
3.4368e+14 4.923 0.06606 0.31 1.942 9.012e3 1.434 1.208 0.07 0.6204
a Activation energy: Ea (eV) Bond-wire aspect ratio: ar b0 b1 C
c Cycling period: ton (s) Diode chip-thickness: fDiode
1659
1400
Ambient Temperature [°C]
Solar Irradiance [W/m2]
N.C. Sintamarean et al. / Microelectronics Reliability 54 (2014) 1655–1660
G-Solar Irradiance
1200 1000 800 600 1200 960 720 480 240 0
400 200 0
Jan
Feb Mar
Apr May
Jun
July Aug
Sep Oct
Nov
Dec
Ta-Ambient Temp.
40 30 20 10
40 35
0
30
-10 -20
Jan
Feb Mar
(a) One year solar irradiance G
Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(b) One year ambient temperature Ta
Fig. 6. The Real Field Mission Profile (RFMP) for one year measurements of solar irradiance G (a) and ambient temperature Ta (b) in USA-Arizona.
Ic-Converter Current
50 40 30 20
50 40 30 20 10 0
10 0
Jan
Feb Mar Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(a) Converter current for one year operation
100
Device Temperature [°C]
Converter Current [A]
60
80
TjMOSFET TjFwD Tcase
60 40 20
90 70
0
50 30
-20 Jan
Feb Mar Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(b) Thermal loading estimation for one year operation
Fig. 7. The realistic PV-inverter loading current (a) and thermal loading estimation (b) of the inverter devices (MOSFET, Diode) for one year operation in USA-Arizona.
4. Conclusions
Table 4 MP and device-aging impact in lifetime. MP
USA-Arizona
Lifetime Without degradation
With degradation
5.5 (years)
4.2 (years)
Degradation impact in lifetime
30%
The simulation model is using as an input the one year MP from USA-Arizona: solar irradiance G (Fig. 6(a)) and ambient temperature Ta (Fig. 6(b)). The obtained simulation results are presented in Fig. 7 and shows the realistic load current of the converter (for one year operation in USA Fig. 7(a)) due to the real field mission profile applied as an input to the model (Fig. 6). Moreover, the thermal loading distribution of the converter devices (MOSFET and Diode) in terms of junction and case temperature (Fig. 7(b)) has been estimated. The obtained one year thermal loading distribution of the converter devices in terms of mean junction temperature (Tj) and junction temperature variation (DTj) has been further used as an input to the lifetime model presented in Section 2.5. Furthermore, the total device accumulated damage has been determined according to Miner’s rule, with and without considering the device degradation feedback loop in the model. The expected PV-inverter devices lifetime is predicted considering that the device fails when the accumulated damage is 1. The MP and device degradation impact in the PV-inverter lifetime is presented in Table 4. According to the obtained results emphasized in Table 4, the device degradation feedback has an impact of 30% in the PV-inverter lifetime estimation accuracy. In order to have correct lifetime estimation it is crucial to consider also the device degradation feedback loop in the simulation model. It can be concluded that the MP of the field where the PV-inverter is operating has a major impact in the converter reliability and it should be considered in the design stage to better optimize the converter design margin selection.
A reliability oriented design tool for the new generation of grid connected PV-inverters applications has been implemented. The detailed simulation model of the tool has been performed considering a real field mission profile model (for operating region USAArizona), a PV-panel model, a grid connected PV-inverter model, an electro-thermal model and the lifetime model. The estimation of one year thermal loading distribution of the converter devices (MOSFET, Diode) has been achieved and further used as an input to the lifetime model. The proposed reliability oriented design tool has been used to assess and study the impact of the MP and the device degradation (aging) in the PV-inverter devices lifetime. The obtained results indicate that the MP of the field, where the PV-inverter is operating has an important impact in the converter reliability and it should be considered from the design phase in order to avoid overdesign–underdesign of the product by choosing an optimum design margin in respect with the stress margin. Moreover, it has been shown that in order to improve the accuracy of the lifetime estimation, it is crucial to consider also the device degradation feedback in the simulation model, which has an impact of 30% in the lifetime estimation for the studied case.
References [1] De Leon-Aldaco SE, Calleja H, Chan F, Jimenez-Grajales HR. Effect of the mission profile on the reliability of a power converter aimed at photovoltaic applications—a case study. IEEE Trans Power Electron. 2013;28(6):2998–3007. [2] Wang H, Liserre M, Blaabjerg F, Rimmen Pde P, Jacobsen JB, Kvisgaard T, et al. Transitioning to physics-of-failure as a reliability driver in power electronics. IEEE J Emer Sel Top Power Electron 2014;2(1):97–114. [3] Chan F, Calleja H, Martinez E. Grid connected PV systems: a reliability-based comparison. In: Proc IEEE int symp ind electron, July 2006. p. 1583–8. [4] Moore LM, Post HN. Five years of operating experience at a large, utility-scale photovoltaic generating plant. J Prog Photovolt: Res Appl 2008;16(3):249–59. [5] Bazzi AM, Kim KA, Johnson BB, Krein PT,Dominguez-Garc´ıa A. Fault impacts on solar power unit reliability. In: Proc 26th annu IEEE appl power electron conf expo, March 2011. p. 1223–31.
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[6] Sintamarean C, Blaabjerg F, Wang H. Comprehensive evaluation on efficiency and thermal loading of associated Si and SiC based PV inverter applications. In: Proc of IECON, November 2013. p. 555–60. [7] Fred Schubert E. Light-emitting diodes. 2nd ed. Cambridge University Press; 2006. ISBN 978-0-521-86538-8. [8] Sintamarean C, Blaabjerg F, Wang H. A novel electro-thermal model for Wide Bandgap WBG-semiconductor based devices. In: IEEE European conference on power electronics and applications, EPE – ECCE Europe, September 2013. p. 1– 10. [9] Sintamarean C, Emi EP, Blaabjerg F, Teodorescu R, Wang H. Wide-bandgap devices in PV systems-opportunities and challenges. In: Proc of IPEC; 2014. [10] Huang H, Mawby PA. A lifetime estimation technique for voltage source inverters. IEEE Trans Power Electron 2013;28(8):4113–9.
[11] Ciappa M. Selected failure mechanisms of modern power modules. Microelectron Reliab 2002;42:653–67. [12] Bayerer R, Hermann T, Licht T, Lutz J, Feller M. Model for power cycling lifetime of IGBT modules various factors influencing lifetime. In: Proc 5th int conf integr power electron syst, Nuremberg, Germany, March 2008. p. 1–6. [13] Scheuermann U, Hecht U. Power cycling lifetime of advanced power modules for different temperature swings. In: Proc PCIM Nuremberg; 2002. p. 59–64. [14] Lee WW, Nguyen LT, Selvaduray GS. Solder joint fatigue models: review and applicability to chip scale packages. Microelectron Reliab 2000;40:231–44. [15] Held M, Jacob P, Nicoletti G, Scacco P. Fast power cycling test for IGBT modules in traction application. In: Proc int conf power electron drive syst, vol. 1; 1997. p. 425–30. [16] ECPE Workshop ‘Lifetime Modelling and Simulation’, July 03–04, 2013. Dusseldorf, Germany.
Contents lists available at ScienceDirect
Microelectronics Reliability journal homepage: www.elsevier.com/locate/microrel
A design tool to study the impact of mission-profile on the reliability of SiC-based PV-inverter devices N.C. Sintamarean a,⇑, H. Wang a, F. Blaabjerg a, P.de P. Rimmen b a b
Department of Energy Technology, Center of Reliable Power Electronics, Aalborg University, Pontoppidanstraede 101, 9220 Aalborg, Denmark Danfoss Power Electronics, R&D Design Center Europe, 6300 Graasten, Denmark
a r t i c l e
i n f o
Article history: Received 27 June 2014 Accepted 8 July 2014 Available online 23 August 2014 Keywords: Mission-profile variation Device-degradation feedback Long term simulation Power electronics devices reliability
a b s t r a c t This paper introduces a reliability-oriented design tool for a new generation of grid connected PV-inverters. The proposed design tool consists of a real field mission profile model (for one year operation in USA-Arizona), a PV-panel model, a grid connected PV-inverter model, an electro-thermal model and the lifetime model of the power semiconductor devices. A simulation model able to consider one year real field operation conditions (solar irradiance and ambient temperature) is developed. Thus, one year estimation of the converter devices thermal loading distribution is achieved and is further used as an input to a lifetime model. The proposed reliability oriented design tool is used to study the impact of MP and device degradation (aging) in the PV-inverter lifetime. The obtained results indicate that the MP of the field where the PV-inverter is operating has an important impact in the converter lifetime expectation, and it should be considered in the design stage to better optimize the converter design margin. In order to improve the accuracy of the lifetime estimation it is crucial to consider also the device degradation feedback (in the simulation model) which has an impact of 30% in the precision of the lifetime estimation in the studied case. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The converter availability in PV-system applications is one of the most important aspects and it depends mostly on the component reliability and its maintenance [1,2]. Therefore, highly reliable components are required in order to minimize the downtime during the lifetime of the converter and implicitly also limit the maintenance costs [3,4]. Even if the typical design target of the lifetime for PV-systems is around 20 years, there is a discrepancy between the lifetime of the PV-inverter (typically 5–10 years) and the PV-panel (20–25 years). The system reliability can be improved by replacing devices before their failure [4,5]. Great variations of the PV-inverters lifetime are encountered due to the Mission Profile (MP) variation from one region to another. Therefore, in order to achieve reliability improvement and cost reduction of the PV-technology, it is of major importance to predict the lifetime of the PV-inverter, according to the MP operating conditions. The loading stress (e.g. thermal loading of devices, cyclic load, voltage etc.) of the PV-inverter devices is a
⇑ Corresponding author. Tel.: +45 2392 9795. E-mail address: [email protected] (N.C. Sintamarean). http://dx.doi.org/10.1016/j.microrel.2014.07.055 0026-2714/Ó 2014 Elsevier Ltd. All rights reserved.
consequence of the MP variations. Moreover, the device strength model is a consequence of the any resisting physical properties (e.g. hardness, melting point, adhesion, etc.) which defines how much loading the component can withstand [2]. A component failure occurs when the applied stress exceeds the designed strength. By analysing the overlap area between the stress-strength distributions, the probability of failure can be obtained (Fig. 1). Therefore, stress and strength, are two of the most important factors which have to be considered for lifetime or reliability estimation of PVinverters. Moreover, the MP will have an impact in the device degradation (D) influencing the failure distribution as shown in Fig. 1. The device strength is well known, thus the main factor which influence the failure distribution is the MP, which usually is not taken into consideration by the producers in the design stage of the PV-inverters. This is the main reason why PV-inverter lifetime varies so much. In order to avoid overdesign-underdesign of the product, a proactive measure can be taken from the design phase by selecting an optimum design margin in respect with the stress margin. This paper proposes a reliability oriented design tool for the new generation of SiC-based grid connected PV-inverters in order to study the impact of mission profile and device degradation in the PV-inverter lifetime.
1656
N.C. Sintamarean et al. / Microelectronics Reliability 54 (2014) 1655–1660
Load Stress
Device Strength
Occurance
Ideal Case Without Degr.
time of the measured data is one minute. Thus a realistic loading of the converter devices can be achieved, taking into account short time and longer time variations.
Failures
2.2. PV-panel model
(MP) Stress Distribuon (D) Strength Distribuon Design Margin Fig. 1. Stress–strength analysis emphasize the failure due to MP variation and device aging.
The PV-panel model estimates the output current and voltage by considering as input the solar irradiance (G) and the ambient temperature (Ta) from the MP model. The model considers the configuration of the PV-panel connection and finally estimates the PVinverter DC-Link voltage and current variations. Considering the Maximum Power Point Tracking (MPPT) strategy, the references for the converter voltage and current are obtained.
2. Proposed reliability oriented design tool 2.3. PV-inverter model This paper introduces a reliability oriented design tool for the new generation of SiC-based grid connected PV-inverters. According to Fig. 2, the proposed design tool consists of a real field mission profile model, a PV-panel model, a grid connected PVinverter model, an electro-thermal model and a Lifetime model. The involved parameters emphasized in Fig. 2 are as follows: G – solar irradiance, Ta – ambient temperature, VDC-Link – DC-Link voltage, Iconv – converter output current, IM – MOSFET drain current, ID – freewheeling diode current, VDC – device off-state voltage, Fsw – switching frequency of the device, Zth_device/grease/heatsink – junction to case/grease/heatsink thermal impedance, Tj – device junction temperature, VG – gate voltage, RG – gate resistance, TC – case temperature of the device, D – device degradation (aging). A description of each model is presented as follows:
The proposed PV-system, depicted in Fig. 3, consists of a 25 kVA SiC-based 2 Level Full Bridge (2L-FB) inverter connected to the three phase grid through a passive LCL-filter. Table 1 presents the PV-system design ratings. Fig. 3 introduces the main control blocks, which are used to achieve the desired converter functionalities. A more detailed description of the grid connected PV-inverter control design has been presented in [6]. The PV-inverter model receives as input the reference current and voltage from the MPPT. By considering the input, the model estimates the realistic device (MOSFET and Diode) loading current (IM or ID) and the voltage variations (offstate voltage VDC). 2.4. Electro-thermal model
2.1. Real field mission profile model The proposed design tool presented in Fig. 2 considers the Mission Profile (MP) of the real field where the converter will operate. In order to study the impact on the PV-inverter devices reliability, the mission profile model is developed based on one year measurements of solar irradiance (G) and ambient temperature (Ta) of harsh environment conditions from USA-Arizona. The sampling
The proposed model aims at estimating the junction and case temperature for the new generation of power electronics devices. The input signals in the model are: the realistic device (MOSFET and Diode) loading current (IM or ID) and voltage variations (offstate voltage VDC), the switching frequency (fSW), the ambient temperature (Ta), the gate-driver operation point (VG and RG) and the device degradation level (D).
Fig. 2. Proposed reliability oriented design structure for the new generation of grid connected PV-inverters.
N.C. Sintamarean et al. / Microelectronics Reliability 54 (2014) 1655–1660
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Fig. 3. Three phase grid connected 2L-FB PV-inverter application.
Table 1 PV-system design ratings. 3L-FB VSI PV-inverter specifications Rated power Conv. output phase voltage Max. output current Max. DC-link voltage Switching frequency
S = 25 kVA VN = 230 V (RMS) (325 V peak) Imax = 37 A (RMS) (52 A peak) VDC-max = 1000 V fsw = 50 kHz
Thermal impedance values Heatsink Thermal grease
s = 570 (s) s = 1.3 (s)
Rth = 0.13 (K/W) Rth = 0.0059 (K/W)
LCL-filter parameters Parameters
LC = 4e4 H
Lg = 1.5e4 H
Device characteristics Device type
CREE MOSFET module (CCS050M12CM2)
PV-Panel characteristics-connection PV-panel type Conn. type
ET black module (ET-M660250BB) Series = 24
According to Fig. 5, three types of models are involved in the electro-thermal analysis: the device model, the power loss model and the thermal model. The device model estimates the voltage drop across the device and the switching energies as a function of the current, the off-state blocking voltage and junction temperature. Furthermore, the estimated parameters and the switching frequency will be used into the power loss PLoss model where the instantaneous conduction and switching losses of the device are calculated. The total losses (Ptotal_loss) and the ambient temperature
99.2
Efficiency [%]
99 98.8 98.6 98.4 98.2 98
Measured Eff.
97.8
0
Cf = 0.4 lF
5
10
15
Estimated Eff. 20
25
Power [kW] Fig. 4. Estimated and measured efficiency curve of the SiC-based 2L-FB PV-inverter.
Parallel = 3
(Ta) are feed into the thermal model which estimates the device case temperature (Tc) and the junction temperature (Tj). Moreover, by providing the junction temperature as a feedback to the device model, the temperature impact in the losses is also considered. Finally, the device degradation (D) and gate-driving strategy (GDs) influence into the junction and the case temperature estimation are also included as follows: Device degradation (analyzed in Section 2.5) in terms of junction to case thermal impedance degradation (given by solder fatigue) and on-state resistance degradation (given by bondwire lift-off). Gate-driving strategy impact in terms of VG and RG variations. By combining the Shockley model of the diode [7] with the resistance model, an accurate estimation of the device parameters in the whole working area has been achieved. A detailed description of the proposed electro-thermal model has been presented in [8]. In order to validate the proposed electro-thermal model in a PVinverter application, the design of 25 kVA grid connected PV-inverter has been performed in agreement with the power rating parameters given in Table 1. A detailed description of the PV-inverter hardware implementation has been presented in [9].
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Fig. 5. Proposed electro-thermal model structure for device junction and case temperature estimation.
The PV-inverter simulation and the laboratory test are performed at the same conditions. The main purpose is to measure the PV-inverter devices (MOSFET power-module) efficiency for different active power levels injected into the grid. The efficiency is measured for power ratings from 0 to 25 kW with load steps of 2.5 kW, by using the Yokogawa WT3000 power analyzer [9]. According to the obtained results presented in Fig. 4, it is worth to mention that the model is performing a good estimation of the power losses in the whole working area range. The largest deviation from the experimental measurements (being of 7% in terms of power-losses) is in the low power operation. 2.5. Device lifetime model Since the intensive work on the power cycling testing of SiC power devices is still undergoing, well-developed degradation models and lifetime models are still unavailable for the analyzed SiC power-module. For demonstrating the procedures of the proposed design tool, the state-of-the-art lifetime models of Si IGBT modules are applied for the SiC devices. Therefore, the results of the lifetime evaluation could be interpreted for relative evaluation and for comparison only. A more relevant lifetime evaluation is upon the replacement by the specific lifetime models of the SiC power-modules in future. The procedures in the proposed design tool are still valid. There are various failure modes for power electronics devices. Two of the most commonly observed (packaging related) failures are die-attach solder fatigue and bond-wire damage [10–12]. They are both caused by temperature cycling during operation and Thermal Expansion Coefficient (CTE) mismatch between adjacent layers. Bond-wire damage is more pronounced after die-attach solder is seriously degraded [13,14]. The solder fatigue will not destroy the device directly, whereas the end of life failure is bond-wire damage related [10,14]. Therefore, device junction temperature (mean junction temperature Tj and junction temperature variation DTj) is one of the critical parameters required for lifetime estimation. The failure criteria are defined based on previous research works [10,15,13]. Thus, [10,15] claims that 10% increase of on-state voltage VDS indicates the bond-wire damage. Moreover, [10,13] suggested that a 40% increase of junction to case thermal resistance Rth_jc indicates the solder-fatigue failure. The Rth_jc has a linear degradation behavior with lifetime level and VDS is mainly changing in the last stage of the lifetime (from 80% to 100%) [10]. Table 2 presents the degradation impact on Rth_jc and VDS with lifetime level. As shown in Fig. 5, the degradation (of Rth_jc and VDS) is provided as a feedback in the electro-thermal model, thus the degradation impact in the losses is also included. As a tradeoff between accu-
Table 2 Device degradation with lifetime level. Lifetime level
1. 2. 3. 4. 5.
0–20% 20–40% 40–60% 60–80% 80–100%
Degradation-aging impact Normalized Rth_jc
Normalized VDS
1 1.1 1.2 1.3 1.4
1 1 1.01 1.03 1.1
racy and simulation time, five degradation levels are included according to Table 2. The lifetime model (SKiM 63) proposed by Semikron is used for the device lifetime estimation [16]. The model uses as a base-line the LESIT lifetime model [15]. Moreover, the dependency on the: wire bond aspect ratio (ar), load pulse duration (ton) and on the freewheeling diode chip thickness (fDiode) are also considered. The lifetime equation which expresses the number of cycles to failure (Nf) is described by (1).
Ea C þ t yon ar b1 DT j þb0 fDiode Nf ¼ A DT aj exp K B T jm Cþ1
ð1Þ
Moreover, Table 3 presents the parameters values used in the model. 3. Lifetime analysis of PV-inverter devices The proposed reliability oriented design tool is used to study the impact of the MP-variation and device aging degradation in the PV-inverter lifetime. For this purpose the simulation has been performed (using the GD parameters: VG = 15 V and RG = 20 O) with and without considering the device aging impact feedback.
Table 3 Device lifetime parameters. Parameter
Value
Technology factor: A
3.4368e+14 4.923 0.06606 0.31 1.942 9.012e3 1.434 1.208 0.07 0.6204
a Activation energy: Ea (eV) Bond-wire aspect ratio: ar b0 b1 C
c Cycling period: ton (s) Diode chip-thickness: fDiode
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Ambient Temperature [°C]
Solar Irradiance [W/m2]
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G-Solar Irradiance
1200 1000 800 600 1200 960 720 480 240 0
400 200 0
Jan
Feb Mar
Apr May
Jun
July Aug
Sep Oct
Nov
Dec
Ta-Ambient Temp.
40 30 20 10
40 35
0
30
-10 -20
Jan
Feb Mar
(a) One year solar irradiance G
Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(b) One year ambient temperature Ta
Fig. 6. The Real Field Mission Profile (RFMP) for one year measurements of solar irradiance G (a) and ambient temperature Ta (b) in USA-Arizona.
Ic-Converter Current
50 40 30 20
50 40 30 20 10 0
10 0
Jan
Feb Mar Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(a) Converter current for one year operation
100
Device Temperature [°C]
Converter Current [A]
60
80
TjMOSFET TjFwD Tcase
60 40 20
90 70
0
50 30
-20 Jan
Feb Mar Apr May
Jun
July Aug
Sep Oct
Nov
Dec
(b) Thermal loading estimation for one year operation
Fig. 7. The realistic PV-inverter loading current (a) and thermal loading estimation (b) of the inverter devices (MOSFET, Diode) for one year operation in USA-Arizona.
4. Conclusions
Table 4 MP and device-aging impact in lifetime. MP
USA-Arizona
Lifetime Without degradation
With degradation
5.5 (years)
4.2 (years)
Degradation impact in lifetime
30%
The simulation model is using as an input the one year MP from USA-Arizona: solar irradiance G (Fig. 6(a)) and ambient temperature Ta (Fig. 6(b)). The obtained simulation results are presented in Fig. 7 and shows the realistic load current of the converter (for one year operation in USA Fig. 7(a)) due to the real field mission profile applied as an input to the model (Fig. 6). Moreover, the thermal loading distribution of the converter devices (MOSFET and Diode) in terms of junction and case temperature (Fig. 7(b)) has been estimated. The obtained one year thermal loading distribution of the converter devices in terms of mean junction temperature (Tj) and junction temperature variation (DTj) has been further used as an input to the lifetime model presented in Section 2.5. Furthermore, the total device accumulated damage has been determined according to Miner’s rule, with and without considering the device degradation feedback loop in the model. The expected PV-inverter devices lifetime is predicted considering that the device fails when the accumulated damage is 1. The MP and device degradation impact in the PV-inverter lifetime is presented in Table 4. According to the obtained results emphasized in Table 4, the device degradation feedback has an impact of 30% in the PV-inverter lifetime estimation accuracy. In order to have correct lifetime estimation it is crucial to consider also the device degradation feedback loop in the simulation model. It can be concluded that the MP of the field where the PV-inverter is operating has a major impact in the converter reliability and it should be considered in the design stage to better optimize the converter design margin selection.
A reliability oriented design tool for the new generation of grid connected PV-inverters applications has been implemented. The detailed simulation model of the tool has been performed considering a real field mission profile model (for operating region USAArizona), a PV-panel model, a grid connected PV-inverter model, an electro-thermal model and the lifetime model. The estimation of one year thermal loading distribution of the converter devices (MOSFET, Diode) has been achieved and further used as an input to the lifetime model. The proposed reliability oriented design tool has been used to assess and study the impact of the MP and the device degradation (aging) in the PV-inverter devices lifetime. The obtained results indicate that the MP of the field, where the PV-inverter is operating has an important impact in the converter reliability and it should be considered from the design phase in order to avoid overdesign–underdesign of the product by choosing an optimum design margin in respect with the stress margin. Moreover, it has been shown that in order to improve the accuracy of the lifetime estimation, it is crucial to consider also the device degradation feedback in the simulation model, which has an impact of 30% in the lifetime estimation for the studied case.
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