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| An Inconsistency Assessment Method for Power Battery Pack Based on Adaptive LTTB and DTW-DBA-Means |
| WU Fenghe1,CHAI Haining1,ZHANG Zhengzhu1,2,ZHANG Ning1,WANG Zhengming2,JIANG Zhanpeng1,GUO Baosu1 |
1. Mechanical Engineering College, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Geely Holding Group, Hangzhou, Zhejiang 310051, China |
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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.
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Received: 04 August 2023
Published: 06 June 2024
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2024, Vol. 45 
