基于自适应LTTB与DTW-DBA-Means的动力电池组不一致性评估方法

doi:10.3969/j.issn.1000-1158.2024.06.15

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Abstract Aiming at the problem that the inconsistency of electric vehicle power battery pack is difficult to be effectively evaluated through external parameters, when analyzing the battery pack voltage data, the Silhouette Coefficient is introduced as the inconsistency evaluation index, and a new inconsistency evaluation method for power battery pack is proposed by integrating adaptive down-sampling (LTTB) and time-series clustering (DTW-DBA-Means) algorithms. Adaptive LTTB can adaptively adjust the compression ratio and sample point allocation in compression intervals according to the characteristics of the battery pack voltage sequence, which can improve the DTW-DBA-Means operation efficiency and ensure the clustering effect. Experiments is conducted based on the real vehicle data running for nine months, the results show that the adaptive LTTB down-sampling effect is better than dynamic LTTB and LTTB, and the DTW-DBA-Means time-series clustering effect is better than k-Shape, and the proposed method can save about 96.7% operation time while ensuring the accuracy of evaluation.

Key words： electrical metrology power battery pack;inconsistency assessment silhouette coefficient down-sampling time-series clustering

Received: 04 August 2023 Published: 06 June 2024

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TB971

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	Articles by authors
	WU Fenghe
	CHAI Haining
	ZHANG Zhengzhu
	ZHANG Ning
	WANG Zhengming
	JIANG Zhanpeng
	GUO Baosu

Cite this article:

WU Fenghe,CHAI Haining,ZHANG Zhengzhu, et al. An Inconsistency Assessment Method for Power Battery Pack Based on Adaptive LTTB and DTW-DBA-Means[J]. Acta Metrologica Sinica, 2024, 45(6): 890-898.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2024.06.15 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2024/V45/I6/890

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