基于启发式PSO算法的新能源电池组串联充放电均衡优化  

Optimization of Series Charge-Discharge Equilibrium of New Energy Battery Pack Based on Heuristic PSO Algorithm

作　　者：王莎莎 罗留祥 WANG Shasha;LUO Liuxiang(Shangqiu Polytechnic School of Transportation,Shangqiu 476000,China;Shangqiu Polytechnic School of Engineering and Technology,Shangqiu 476000,China)

机构地区：[1]商丘职业技术学院交通学院,河南商丘476000 [2]商丘职业技术学院工程技术学院,河南商丘476000

出　　处：《通信电源技术》2023年第18期110-112,共3页Telecom Power Technology

摘　　要：由于新能源电池串联成组后会出现性能参数上的差异,导致电池组能量利用率较低,提出基于启发式粒子群优化(Particle Swarm Optimization,PSO)算法的新能源电池组串联充放电均衡优化。构建以电池组内单体电池实际可充入电量一致为目标的均衡优化模型,以最劣粒子排斥作用为启发式规则应用于PSO算法,得到最佳新能源电池组串联充放电均衡优化方案。实验表明,设计方法优化电池组充放电均衡后,较优化前电池可充入与放出的容量有所增加,证实该方法可提高新能源电池组能量利用率。Due to differences in performance parameters after new energy batteries are connected in series and grouped,the energy utilization rate of the battery pack is low.A heuristic Particle Swarm Optimization(PSO)algorithm based optimization of series charging and discharging balance for new energy battery packs is proposed.By constructing an equilibrium optimization model with the goal of consistent actual charging capacity of individual batteries within the battery pack,and applying the worst particle repulsion as a heuristic rule to the PSO algorithm,the optimal series charging and discharging equilibrium optimization scheme for new energy battery packs is obtained.The experiment shows that after optimizing the charging and discharging balance of the battery pack using the design method,the capacity of the battery that can be charged and discharged is improved compared to before optimization,confirming that this method can improve the energy utilization rate of the new energy battery pack.

关 键 词：启发式粒子群优化(PSO)算法 新能源电池组 串联 充放电 均衡优化 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TM715[自动化与计算机技术—控制科学与工程]