期刊
JOURNAL OF CLEANER PRODUCTION
卷 230, 期 -, 页码 1061-1073出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.05.144
关键词
Battery pack; Peak power; Battery inconsistency; Representative cells; Multi-parameter limited method
资金
- National Natural Science Foundation of China [61527809, U1764258, 61633015]
- National key R&D program of China
- Shandong Province [2018YFB0104000, 2016ZDJS03A02]
Accurate power prediction for a battery pack is of great importance for efficient and safe operation of electric vehicles. However, a battery pack typically consists of dozens of cells connected in series, and how to accurately predict its peak power in practical applications has always been a challenging issue. This paper proposes a low-complexity peak power prediction method for a series-connected battery pack, where the peak power of battery pack is predicted depending only on representative cells. Firstly, considering state of charge and voltage limits for power prediction, the representative cells are selected by using two easily available variables, namely characteristic voltage and ohmic resistance. Secondly, the state of charge and voltage of the representative cell are estimated accurately by the dual adaptive extended Kalman filter algorithm. Finally, the multi-parameter limited method for battery pack is developed to predict the peak power under Urban Dynamometer Driving Schedule test at different temperatures. The experimental results verify the feasibility and robustness of the proposed selection method, and the peak power of battery pack is predicted with low complexity and high accuracy. (C) 2019 Elsevier Ltd. All rights reserved.
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