Online estimation of power capacity with noise effect attenuation for lithium-ion battery

Accurate estimation of power capacity is critical to ensure battery safety margins and optimize energy utilization. Power capacity estimators based on online identified equivalent circuit model have been widely investigated due to the high accuracy and affordable computing cost. However, the impact...

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Main Authors: Wei, Zhongbao, Zhao, Jiyun, Xiong, Rui, Dong, Guangzhong, Pou, Josep, Tseng, King Jet
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2020
主題:
在線閱讀:https://hdl.handle.net/10356/144528
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機構: Nanyang Technological University
語言: English
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總結:Accurate estimation of power capacity is critical to ensure battery safety margins and optimize energy utilization. Power capacity estimators based on online identified equivalent circuit model have been widely investigated due to the high accuracy and affordable computing cost. However, the impact of noise corruption which is common in practice on such estimators has never been investigated. This paper scrutinizes the effect of noises on model identification, state of charge (SOC) and power capacity estimation. An online model identification method based on adaptive forgetting recursive total least squares (AF-RTLS) is proposed to compensate the noise effect and attenuate the identification bias of model parameters. A Luenberger observer is further used in combination with the AF-RTLS to estimate the SOC in real time. Leveraging the estimated model parameters and SOC, a multiconstraint analytical method is proposed to online estimate the power capacity. Simulation and experimental results verify that the proposed method is superior in terms of estimation accuracy and the robustness to noise corruption.