Research on the Optimal Charging Strategy for Li-Ion Batteries Based on Multi-Objective Optimization

Haitao Min, Weiyi Sun, Xinyong Li, Dongni Guo, Yuanbin Yu, Tao Zhu and Zhongmin Zhao
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Haitao Min: State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Weiyi Sun: State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Xinyong Li: State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Dongni Guo: China First Automobile Work shop Group Corporation Research and Development Center, Changchun 130011, China
Yuanbin Yu: State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Tao Zhu: State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
Zhongmin Zhao: China First Automobile Work shop Bus and Coach Co., Ltd., Changchun 130033, China

Energies, 2017, vol. 10, issue 5, 1-15

Abstract: Charging performance affects the commercial application of electric vehicles (EVs) significantly. This paper presents an optimal charging strategy for Li-ion batteries based on the voltage-based multistage constant current (VMCC) charging strategy. In order to satisfy the different charging demands of the EV users for charging time, charged capacity and energy loss, the multi-objective particle swarm optimization (MOPSO) algorithm is employed and the influences of charging stage number, charging cut-off voltage and weight factors of different charging goals are analyzed. Comparison experiments of the proposed charging strategy and the traditional normal and fast charging strategies are carried out. The experimental results demonstrate that the traditional normal and fast charging strategies can only satisfy a small range of EV users’ charging demand well while the proposed charging strategy can satisfy the whole range of the charging demand well. The relative increase in charging performance of the proposed charging strategy can reach more than 80% when compared to the normal and fast charging dependently.

Keywords: EV charging; Li-ion batteries; multi-objective optimization; equivalent circuit model (ECM); MOPSO algorithm; multistage constant current charging (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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