摘要
针对电动汽车锂离子电池和超级电容的混合储能系统不同工作模式的功率最优分配困难的问题,提出基于遗传算法的混合储能系统能量功率的最优分配策略。对储能系统的不同工作模式进行分类管理,建立能量管理系统输出功率与需求功率误差最小的目标函数。采用遗传算法求解目标函数,获得锂离子电池和超级电容的出力系数,进而优化功率分配。最后,搭建混合储能系统仿真模型和实验台进行仿真和实验,结果表明,在EUDS和UDDS路况下,与传统滞环控制相比,采用遗传算法优化的能量管理总损耗降低1.2%和0.9%。
To overcome the difficulty of optimal power distribution of different working modes in battery and super capacitor hybrid energy storage system of electric vehicles,an optimized hybrid energy management strategy based on genetic algorithm was proposed.The different working modes of energy storage system were classified management and a target function with minimal output demand with power error of the energy management system was built.The genetic algorithm was utilized to solve the objective function.The output coefficients of lithium-ion batteries and super capacitors were obtained to optimize power allocation.Finally,a hybrid energy storage system simulation model and the experimental platform were built for simulation and verification.The results show that under EUDS and UDDS scheduling,compared with traditional hysteresis control,the energy management using genetic algorithm can reduce the total loss by 1.2%and 0.9%.
作者
吴铁洲
薛竹山
向富超
张振东
WU Tiezhou;XUE Zhushan;XIANG Fuchao;ZHANG Zhendong(Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy,Hubei University of Technology,Wuhan 430068,Hubei,China)
出处
《电气传动》
北大核心
2019年第2期49-55,共7页
Electric Drive
基金
国家自然科学基金(51677058)
关键词
电动汽车
遗传算法
工作模式
混合储能系统
功率分配
electric vehicle
genetic algorithm
working modes
hybrid energy storage system(HESS)
power distribution
