Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration

Yu You Chou; Cheng Wen Wu; Ming Der Shieh; Chao Hsun Chen

doi:10.1109/ATS56056.2022.00024

Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration

Yu You Chou, Cheng Wen Wu, Ming Der Shieh, Chao Hsun Chen

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In the fast-growing electric vehicle (EV) industry, key technology challenges include the improvement of battery efficiency, reliability, and endurance. In this paper, we propose a novel battery pack design methodology that supports dynamic reconfiguration of the battery pack architecture, which partitions the battery modules into the primary group and secondary group. The proposed reconfigurable design effectively improves the battery pack reliability and endurance, especially for battery packs that contain modules with uneven aging conditions. Simulation results show that, with our approach, the equivalent average aging speed among all battery modules is slowed down, and the battery pack's endurance is increased.

Original language	English
Title of host publication	Proceedings - 2022 IEEE 31st Asian Test Symposium, ATS 2022
Publisher	IEEE Computer Society
Pages	66-71
Number of pages	6
ISBN (Electronic)	9781665472272
DOIs	https://doi.org/10.1109/ATS56056.2022.00024
Publication status	Published - 2022
Event	31st IEEE Asian Test Symposium, ATS 2022 - Taichung, Taiwan Duration: 2022 Nov 21 → 2022 Nov 23

Publication series

Name	Proceedings of the Asian Test Symposium
Volume	2022-November
ISSN (Print)	1081-7735

Conference

Conference	31st IEEE Asian Test Symposium, ATS 2022
Country/Territory	Taiwan
City	Taichung
Period	22-11-21 → 22-11-23

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering

Access to Document

10.1109/ATS56056.2022.00024

Cite this

@inproceedings{3bb772662062405f88535d9e7b1b3069,

title = "Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration",

abstract = "In the fast-growing electric vehicle (EV) industry, key technology challenges include the improvement of battery efficiency, reliability, and endurance. In this paper, we propose a novel battery pack design methodology that supports dynamic reconfiguration of the battery pack architecture, which partitions the battery modules into the primary group and secondary group. The proposed reconfigurable design effectively improves the battery pack reliability and endurance, especially for battery packs that contain modules with uneven aging conditions. Simulation results show that, with our approach, the equivalent average aging speed among all battery modules is slowed down, and the battery pack's endurance is increased.",

author = "Chou, {Yu You} and Wu, {Cheng Wen} and Shieh, {Ming Der} and Chen, {Chao Hsun}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 31st IEEE Asian Test Symposium, ATS 2022 ; Conference date: 21-11-2022 Through 23-11-2022",

year = "2022",

doi = "10.1109/ATS56056.2022.00024",

language = "English",

series = "Proceedings of the Asian Test Symposium",

publisher = "IEEE Computer Society",

pages = "66--71",

booktitle = "Proceedings - 2022 IEEE 31st Asian Test Symposium, ATS 2022",

address = "United States",

}

Chou, YY, Wu, CW, Shieh, MD & Chen, CH 2022, Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration. in Proceedings - 2022 IEEE 31st Asian Test Symposium, ATS 2022. Proceedings of the Asian Test Symposium, vol. 2022-November, IEEE Computer Society, pp. 66-71, 31st IEEE Asian Test Symposium, ATS 2022, Taichung, Taiwan, 22-11-21. https://doi.org/10.1109/ATS56056.2022.00024

Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration. / Chou, Yu You; Wu, Cheng Wen; Shieh, Ming Der et al.
Proceedings - 2022 IEEE 31st Asian Test Symposium, ATS 2022. IEEE Computer Society, 2022. p. 66-71 (Proceedings of the Asian Test Symposium; Vol. 2022-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration

AU - Chou, Yu You

AU - Wu, Cheng Wen

AU - Shieh, Ming Der

AU - Chen, Chao Hsun

PY - 2022

Y1 - 2022

N2 - In the fast-growing electric vehicle (EV) industry, key technology challenges include the improvement of battery efficiency, reliability, and endurance. In this paper, we propose a novel battery pack design methodology that supports dynamic reconfiguration of the battery pack architecture, which partitions the battery modules into the primary group and secondary group. The proposed reconfigurable design effectively improves the battery pack reliability and endurance, especially for battery packs that contain modules with uneven aging conditions. Simulation results show that, with our approach, the equivalent average aging speed among all battery modules is slowed down, and the battery pack's endurance is increased.

AB - In the fast-growing electric vehicle (EV) industry, key technology challenges include the improvement of battery efficiency, reliability, and endurance. In this paper, we propose a novel battery pack design methodology that supports dynamic reconfiguration of the battery pack architecture, which partitions the battery modules into the primary group and secondary group. The proposed reconfigurable design effectively improves the battery pack reliability and endurance, especially for battery packs that contain modules with uneven aging conditions. Simulation results show that, with our approach, the equivalent average aging speed among all battery modules is slowed down, and the battery pack's endurance is increased.

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EP - 71

BT - Proceedings - 2022 IEEE 31st Asian Test Symposium, ATS 2022

PB - IEEE Computer Society

T2 - 31st IEEE Asian Test Symposium, ATS 2022

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ER -

Battery Pack Reliability and Endurance Enhancement for Electric Vehicles by Dynamic Reconfiguration

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