中国电气工程学报（英文） ›› 2019, Vol. 5 ›› Issue (2): 72-78.

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  • 出版日期:2019-06-20 发布日期:1900-01-01
  • 通讯作者: Supported by the Key Research and Development Program of Hunan Province of China (2018GK2031), the National Natural Science Foundation of China (51822702), and the Excellent Innovation Youth Program of Changsha of China (KQ1802029).

PSO-based Optimization for Constant-current Charging Pattern for Li-ion Battery*

Yixiao Wang, Yong Li*, Li Jiang, Yuduo Huang, Yijia Cao   

  1. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
  • Online:2019-06-20 Published:1900-01-01
  • About author:Yixiao Wang was born in Hunan, China, in 1996. He received his B.S. degree in electrical engineering, from the College of Electrical and Information Engineering, Hunan University, Changsha, China. He is currently working towards his M.S degree at Hunan University. His current research interests include charging strategy, battery model, power electronics and power systems.
    Yong Li (S’09-M’12-SM’14) was born in Henan, China, in 1982. He received the B.Sc. and Ph.D. degrees in 2004 and 2011, respectively, from the College of Electrical and Information Engineering, Hunan University, Changsha, China. Since 2009, he worked as a Research Associate at the Institute of Energy Systems, Energy Efficiency, and Energy Economics (ie3), TUDortmund University, Dortmund, Germany, where he received the second Ph.D. degree in June 2012. After then, he was a Research Fellow with The University of Queensland, Brisbane, Australia. Since 2014, he is a Full Professor of electrical engineering with Hunan University. His current research interests include power system stability analysis and control, ac/dc energy conversion systems and equipment, analysis and control of power quality, and HVDC and FACTS technologies.
    Li Jiang was born in Hunan, China, in 1991. He received B.S. degree from the Hunan University of Technology, Zhuzhou, China, in 2015, and the M.S. degree from Central South University, Changsha, China, in 2018, both in Control Science and Engineering. He is currently working toward the Ph.D. degree in electrical engineering at Hunan University, Changsha, China. His current research interests include bidirectional DC/DC converters, solid-state transformers, modeling and charging strategy for Li-ion battery.
    Yuduo Huang was born in Fujian, China, in 1995. He received his B.S degree in electrical engineering from Hunan University, Changsha, China. He is currently working towards his M.S degree at Hunan University. His current research interests include charging strategy, battery model, power electronics and power systems.
    Yijia Cao (M’98) was born in Hunan, China, in 1969. He graduated from Xi'an Jiaotong University, Xi’an, China, in 1988 and received M.Sc. degree from Huazhong University of Science and Technology (HUST), Wuhan, China in 1991 and Ph.D. from HUST in 1994. From September 1994 to April 2000, he worked as a visiting research fellow, research fellow at Loughborough University, Liverpool University and University of the West of England, UK. From 2000 to 2001, he was employed as a full professor of HUST, and from 2001 to 2008, he was employed as a full professor of Zhejiang University, China. He was appointed deputy dean of College of Electrical Engineering, Zhejiang University in 2005. Currently, he is a full professor and president of Changsha University of Science and Technology, Changsha, China. His research interests are power system stability control and the application of intelligent systems in power systems.
  • Supported by:
    yongli@hnu.edu.cn

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Abstract: A particle swarm optimization algorithm to search for an optimal five-stage constant-current charge pattern is proposed. The goal is to maximize the objective function for the proposed charge pattern based on the charging capacity, time, and energy efficiency, which all share the same weight. Firstly, an equivalent circuit model is built and battery parameters are identified. Then the optimal five-stage constant-current charge pattern is searched using a particle swarm optimization algorithm. At last, comparative experiments using the constant current-constant voltage (CC-CV) method are performed. Although the charging SOC of the proposed charging pattern was 2.5% lower than that of the CC-CV strategy, the charging time and charging energy efficiency are improved by 15.6% and 0.47% respectively. In particular, the maximum temperature increase of the battery is approximately 0.8 ℃ lower than that of the CC-CV method, which indicates that the proposed charging pattern is more secure.

Key words: Li-ion batteries, charging strategy, multi-stage constant current, particle swarm optimization, equivalent circuit model