Battery state estimation with a self-evolving electrochemical ageing model
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- 作者：Yilu Zhang ; Xinyu Du ; xinyu.du@gm.com" class="auth_mail" title="E-mail the corresponding author ; Mutasim Salman
- 关键词：Battery ageing model ; State of charge ; State of health ; Particle filter ; Diagnosis
- 刊名：International Journal of Electrical Power & Energy Systems
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：85
- 期：Complete
- 页码：178-189
- 全文大小：1312 K
文摘
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An electrochemical model is tailored to estimate states for lead-acid batteries.
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The model ageing parameters can be updated by the particle filter algorithm.
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A two-time-scale scheme is proposed to reduce the computational cost.
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An adaptive importance density algorithm is proposed to increase convergence speed.
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A battery change detection algorithm is developed to adapt to the battery change.