机译:基于H无限和无味卡尔曼滤波器的锂离子电池参数和荷电状态联合估计
Collaborative Innovation Center of Electric Vehicles in Beijing and School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China;
Collaborative Innovation Center of Electric Vehicles in Beijing and School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China;
Collaborative Innovation Center of Electric Vehicles in Beijing and School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China;
Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC, Australia;
Collaborative Innovation Center of Electric Vehicles in Beijing and School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China;
Estimation; Mathematical model; Parameter estimation; Robustness; Current measurement;
机译:在线估计自动移动机器人锂离子电池模型参数和荷电状态的自适应无味卡尔曼滤波方法
机译:具有递归限制的锂离子电池的模型参数和充电状态的共用估算限制总方块和Unscented Kalman滤波器
机译:基于储存锂离子电池的Unscented Kalman颗粒滤波器估计充电状态
机译:使用无味卡尔曼滤波器在线估计锂离子电池的模型参数和充电状态
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:基于遗传算法的卡尔曼滤波器参数调整用于电池管理系统的荷电状态估计
机译:用于锂离子电池的锂离子电池的平行算术无需Kalman滤波器估计