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Capacity Estimation of Lithium-ion Battery based on Electrochemical Model with Electrolyte Dynamics⁎This work was supported in part by the National Key RD Program of China (Grant NO.2018YFA0703800), Science Fund for Creative Research Group of the National Natural Science Foundation of China (Grant NO.61621002), Nation Natural Science Foundation of China (NSFC:61873233, 61633019), Fundamental Research Funds for the Central Universities. Issue 2 (2020)
Record Type:
Journal Article
Title:
Capacity Estimation of Lithium-ion Battery based on Electrochemical Model with Electrolyte Dynamics⁎This work was supported in part by the National Key RD Program of China (Grant NO.2018YFA0703800), Science Fund for Creative Research Group of the National Natural Science Foundation of China (Grant NO.61621002), Nation Natural Science Foundation of China (NSFC:61873233, 61633019), Fundamental Research Funds for the Central Universities. Issue 2 (2020)
Main Title:
Capacity Estimation of Lithium-ion Battery based on Electrochemical Model with Electrolyte Dynamics⁎This work was supported in part by the National Key RD Program of China (Grant NO.2018YFA0703800), Science Fund for Creative Research Group of the National Natural Science Foundation of China (Grant NO.61621002), Nation Natural Science Foundation of China (NSFC:61873233, 61633019), Fundamental Research Funds for the Central Universities.
Abstract: The remaining capacity of a battery is a crucial indicator, which has significant impact on State of Charge (SoC) estimation and the safe operations of electric vehicles. In this paper, an electrochemical model considering the electrolyte dynamics is proposed to estimate the real capacity of a lithium-ion battery. The electrochemical model with electrolyte dynamics governed by several partial differential equations has the potential to accurately describe varieties of phenomenons inside the battery. Furthermore, a Pade' one-order approximation is adopted to obtain the transfer function between the boundary lithium-ion concentration and input current, then a boundary state estimator is proposed to estimate the the boundary lithium-ion concentration. After that, the least square method is used to obtain the adaptive update law for maximum concentration estimation in anode. Finally, the correctness of the aforementioned estimation methods is verified through simulation.