【摘要】 本文提出一种由交互式多模型和扩展卡尔曼滤波两种算法相结合而形成的滤波器,并应用于锂离子电池非线性系统的状态估计.先采用两个不同参数的戴维宁电路模型描述锂离子电池的动态特征.再将交互式多模型扩展卡尔曼滤波器和传统扩展卡尔曼滤波器分别用于荷电状态估计,针对复合脉冲功率测试和城市道路循环工况进行了数值仿真实验,针对恒流放电进行了硬件仿真实验.最后,对实验结果分析表明交互式多模型卡尔曼滤波算法的有效性和相对以传统方法在估计误差方面的优势,计算量增加合理.更多还原

【Abstract】 A novel state-of-charge(SOC) estimator is presented based on a combination of the interactive multimodel algorithm and the extended Kalman filter.The estimator is used in SOC estimation for nonlinear systems of lithium-ion batteries.First,the dynamic characteristics of the lithium-ion battery are described by two Thevenin circuit models,which have different parameters.Then,interactive multi-model extended Kalman filter and conventional extended Kalman filter are applied in numerical simulations to estimate the SOC in cases of hybrid pulse power characterization and urban dynamometer driving schedule,and then in a hardware experiment in case of constant current discharge.An analysis of results shows the effectiveness of interactive multi-model extended Kalman filter and its advantage over conventional methods with respect to estimation errors.The added computational cost of the new estimator is reasonable.更多还原