机译:基于自适应时移广泛学习系统的锂离子电池容量估计方法
Capital Normal Univ Informat Engn Coll Beijing 100048 Peoples R China|Capital Normal Univ Beijing Key Lab Elect Syst Reliabil Technol Beijing 100048 Peoples R China;
Capital Normal Univ Sch Math Sci Beijing 100048 Peoples R China;
Capital Normal Univ Informat Engn Coll Beijing 100048 Peoples R China|Capital Normal Univ Beijing Key Lab Elect Syst Reliabil Technol Beijing 100048 Peoples R China;
Capital Normal Univ Informat Engn Coll Beijing 100048 Peoples R China|Capital Normal Univ Beijing Key Lab Elect Syst Reliabil Technol Beijing 100048 Peoples R China;
Capital Normal Univ Informat Engn Coll Beijing 100048 Peoples R China|Capital Normal Univ Beijing Key Lab Elect Syst Reliabil Technol Beijing 100048 Peoples R China;
Lithium-ion battery; Broad learning system; Time-shifting; Capacity estimation;
机译:基于双强跟踪自适应H无限滤波器的锂离子电池充电状态和容量估计的新方法
机译:基于双重强跟踪自适应H无限滤波器的锂离子电池充电状态和容量估计的新方法
机译:新型广义极端学习机方法锂离子电池的容量估计和循环寿命预测
机译:具有锂离子电池容量估计的集合学习的深度学习方法
机译:锂离子电池SOC估计库仑计数方法:电动汽车应用电池管理系统的改进
机译:基于恒定电压充电曲线的锂离子电池剩余容量估算
机译:基于衰老试验的自适应模型算法的锂离子电池容量估计