基于自适应卡尔曼滤波的锂电池SOC估计OA北大核心CSCDCSTPCD
Estimation of state of charge of Li-ion battery based on adaptive Kalman filtering
考虑到传统的卡尔曼滤波策略在未知干扰噪声环境下不能对锂离子电池的荷电状态(soc)进行准确的估计,简要论述了锂离子电池的等效电路模型,提出了自适应卡尔曼滤波方法,利用Matlab/Simulink建立了基于自适应和常规的卡尔曼滤波法的锂离子电池SOC估计的仿真模型,分析研究了在未知干扰噪声下两种滤波法的SOC估计值变化曲线以及误差关系.仿真结果表明,采用自适应卡尔曼滤波方法估计的SOC误差较传统的要小,从而有效降低了未知干扰噪声对电池管理系统所受…查看全部>>
Taking into account the traditional Kalman filtering strategy that can not estimate state of charge (SOC) of lithium-ion battery accurately in the unknown environment interference noise,the equivalent circuit model of lithium-ion battery was discussed,and an adaptive Kalman filtering method was put forward.The lithium-ion battery SOC estimation simulation model was built by using Matlab/Simulink based on adaptive Kalman filtering and conventional…查看全部>>
彭湃;程汉湘;陈杏灿;李蕾
广东工业大学自动化学院,广东广州510006广东工业大学自动化学院,广东广州510006广东工业大学自动化学院,广东广州510006广东工业大学自动化学院,广东广州510006
信息技术与安全科学
SOC锂离子电池自适应卡尔曼滤波Matlab电池管理系统
SOClithium ion batteryadaptive Kalman filterMatlabbattery management system
《电源技术》 2017 (11)
1541-1544,4
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