TY - GEN
T1 - Design of Control Algorithm for I-ion Battery Pile Based on Particle Swarm Optimization Algorithm
AU - Liu, Li
AU - Jiang, Yongsheng
AU - Wumaier, Tuerdi
AU - Wang, Yahui
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The power source of electric vehicles mainly depends on power batteries, and the cycle life, capacity, charging and discharging time, self-discharge rate and power of batteries are the main performance indexes of electric energy vehicles. In general, in electric vehicles, the power drive requirements of electric vehicles are met by connecting batteries in series, and the voltage level is improved. However, the current method can't guarantee the consistency of battery parameters such as SOC. In this article, a balanced control strategy of i-ion battery pile SOC based on PSO algorithm is proposed. The update strategy of global domain search and the learning mechanism of adding chaos interference and global optimal particles are adopted to overcome the shortcomings of traditional PSO algorithm, such as slow iteration speed and easy falling into local optimal value. And the simulation results show that the proposed balancing control strategy for i-ion battery pile not only balances the charging and discharging of the battery pile, but also improves the balancing structure and efficiency.
AB - The power source of electric vehicles mainly depends on power batteries, and the cycle life, capacity, charging and discharging time, self-discharge rate and power of batteries are the main performance indexes of electric energy vehicles. In general, in electric vehicles, the power drive requirements of electric vehicles are met by connecting batteries in series, and the voltage level is improved. However, the current method can't guarantee the consistency of battery parameters such as SOC. In this article, a balanced control strategy of i-ion battery pile SOC based on PSO algorithm is proposed. The update strategy of global domain search and the learning mechanism of adding chaos interference and global optimal particles are adopted to overcome the shortcomings of traditional PSO algorithm, such as slow iteration speed and easy falling into local optimal value. And the simulation results show that the proposed balancing control strategy for i-ion battery pile not only balances the charging and discharging of the battery pile, but also improves the balancing structure and efficiency.
KW - Electric car
KW - Equilibrium control
KW - i-ion battery pile
KW - Particle swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85186114722&partnerID=8YFLogxK
U2 - 10.1109/PEEEC60561.2023.00026
DO - 10.1109/PEEEC60561.2023.00026
M3 - Conference contribution
AN - SCOPUS:85186114722
T3 - Proceedings - 2023 International Conference on Power, Electrical Engineering, Electronics and Control, PEEEC 2023
SP - 102
EP - 107
BT - Proceedings - 2023 International Conference on Power, Electrical Engineering, Electronics and Control, PEEEC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Power, Electrical Engineering, Electronics and Control, PEEEC 2023
Y2 - 25 September 2023 through 27 September 2023
ER -