摘要
锂电池在实际应用中面临着频繁充放电、容量衰减等问题,而超级电容具有功率密度高、充放电速度快等优点,将超级电容和锂电池结合起来构成的混合储能系统对资源的合理利用有着重要的意义。提出了一种Buck-Boost变换器和Boost功率变换器相结合的混合储能并联控制系统,采用自适应变异粒子群(AMPSO)与BP神经网络相结合的算法估计锂电池的荷电状态,提出了一种基于模糊算法的混合储能优化控制策略,建立了混合储能系统仿真模型。仿真和实验结果显示了所提出的混合储能系统控制方法的正确性和有效性。
Lithium batteries face problems in practical applications,such as frequent charge and discharge and capacity attenuation.Supercapacitors have the advantages of high power density and fast charge and discharge.The hybrid energy storage system that combines supercapacitors and lithium batteries is of great significance to the rational use of resources.A hybrid energy storage parallel control system combining Buck-Boost converter and Boost power converter was proposed.Particle swarm optimization with adaptive mutation(AMPSO)was combined with BP neural network to estimate the state of charge of lithium battery,and a hybrid energy storage optimization control strategy based on fuzzy algorithm was proposed.A hybrid energy storage system simulation model was established.The simulation and experimental results show that the proposed hybrid energy storage system control method is correct and effective.
作者
刘晓悦
陈瑞
白尚维
LIU Xiaoyue;CHEN Rui;BAI Shangwei(College of Electrical Engineering,North China University of Science And Technology,Tangshan Hebei 063200,China)
出处
《电源技术》
CAS
北大核心
2021年第9期1181-1184,共4页
Chinese Journal of Power Sources
基金
国家自然科学基金(51574102
51474086)
河北省自然科学基金(E2019209492)。
关键词
超级电容
自适应变异粒子群优化
荷电状态
模糊算法
混合储能
supercapacitor
particle swarm optimization with adaptive mutation
state of charge
fuzzy algorithm
hybrid energy storage
