@inproceedings{76b0403261e2443191e983d5f7adeb1a,
title = "Impact of Loss Model Selection on Power Semiconductor Lifetime Prediction in Electric Vehicles",
abstract = "Power loss estimation is an indispensable procedure to conduct lifetime prediction for power semiconductor device. The previous studies successfully perform steady-state power loss estimation for different applications, but which may be limited for the electric vehicles (EVs) with high dynamics. Based on two EV standard driving cycle profiles, this paper gives a comparative study of power loss estimation models with two different time resolutions, i.e., the output period average and the switching period average. The correspondingly estimated power losses, thermal profiles, and lifetime clearly pointed out that the widely applied power loss model with the output period average is limited for EV applications, in particular for the highly dynamic driving cycle. The difference in the predicted lifetime can be up to 300 times due to the unreasonable choice the loss model, which calls for the industry attention on the differences of the EVs and the importance of loss model selection in lifetime prediction.",
keywords = "electric vehicle, lifetime, loss model, power semiconductor device",
author = "Hongjian Xia and Yi Zhang and Dao Zhou and Minyou Chen and Wei Lai and Yunhai Wei and Huai Wang",
note = "Funding Information: ACKNOWLEDGEMENT This research is partially supported by Independent Research Fund Denmark with the number 1031-00024B. Publisher Copyright: {\textcopyright} 2022 IEEE.; 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 ; Conference date: 17-10-2022 Through 20-10-2022",
year = "2022",
doi = "10.1109/IECON49645.2022.9968430",
language = "British English",
series = "IECON Proceedings (Industrial Electronics Conference)",
publisher = "IEEE Computer Society",
booktitle = "IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society",
address = "United States",
}