机译:使用自适应扩展卡尔曼滤波器的多种类型锂离子电池的鲁棒充电状态估计器
National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguuncun Street,Haidian District. Beijing 100081, China,Department of Electrical and Computer Engineering, University of Michigan, Dearborn, 4901 Evergreen Road, Dearborn, Ml 48128, USA;
Department of Electrical and Computer Engineering, University of Michigan, Dearborn, 4901 Evergreen Road, Dearborn, Ml 48128, USA;
Department of Electrical and Computer Engineering, University of Michigan, Dearborn, 4901 Evergreen Road, Dearborn, Ml 48128, USA;
National Engineering Laboratory for Electric Vehicles, School of Mechanical Engineering, Beijing Institute of Technology, No. 5 South Zhongguuncun Street,Haidian District. Beijing 100081, China;
Lithium-ion battery; Data driven; Dynamic universal battery model; Adaptive extended Kalman filter; State of charge;
机译:基于全局粒子群优化和改进的扩展卡尔曼滤波器的锂离子电池全区域电量估算器
机译:一种基于双自适应扩展卡尔曼滤光片的新型单向传输的共同估算框架,用于基于双自适应扩展卡尔曼滤波器的锂离子电池
机译:基于鲁棒扩展卡尔曼滤波器的电动汽车数据驱动充电状态估计器
机译:基于交互式多模型扩展卡尔曼滤波器的锂离子电池荷电状态估计
机译:交互式多模型卡尔曼滤波器的锂离子电池电芯寿命估算的改进方法
机译:自适应扩展卡尔曼滤波器具有鲁棒电力系统状态估计的固定损耗
机译:基于扩展卡尔曼滤波算法的锂离子电池的充电状态估计