基于自适应模糊卡尔曼滤波的锂电池SOC估计  

SOC Estimation of Lithium Batteries Based on Adaptive Fuzzy Kalman Filter

作　　者：孙庆 卫能 侯卫国 李峰 SUN Qing;WEI Neng;HOU Weiguo;LI Feng(Wuhu Ceprei Robotics Industry Technology Research Institute Co.,Ltd.,Wuhu 241003,China)

机构地区：[1]芜湖赛宝机器人产业技术研究院有限公司,安徽芜湖241003

出　　处：《电子产品可靠性与环境试验》2020年第S01期19-23,共5页Electronic Product Reliability and Environmental Testing

摘　　要：在基于卡尔曼滤波的锂电池荷电状态估计过程中,噪声的不确定严重地影响了常规卡尔曼滤波结果的精度,较大的噪声变化甚至会导致滤波发散。为此提出了一种基于自适应模糊卡尔曼滤波的SOC估计方法,根据模糊推理系统在线监测到的残差变化情况,对系统噪声和量测噪声进行调整,从而提高了卡尔曼滤波精度。在城市道路循环工况下的仿真结果表明,基于自适应模糊卡尔曼滤波的SOC估算误差可以达到3%以内,提高了SOC估计精度。During the estimation of the SOC of the lithium battery based on Kalman filter,the uncertainty of the noise seriously affects the accuracy of the conventional Kalman filter results,and the large noise change will even lead to the divergence of the filter.Therefore,a SOC estimation method based on adaptive fuzzy kalman filter is proposed,and the system noise and measurement noise are adjusted according to the residual variation on-line monitored by the fuzzy inference system,which improves the accuracy of Kalman filter.The simulation results under the UDDS show that the SOC error based on adaptive fuzzy Kalman filter can reach less than 3%,which improves the accuracy of SOC estimation.

关 键 词：电池荷电状态 模糊卡尔曼滤波 噪声方差 自适应 

分 类 号：TM911[电气工程—电力电子与电力传动]