...
机译:基于长短期内存网络建模和自适应H-Infinity滤波器的锂离子电池的合成状态
Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China|Queen Mary Univ London Sch Engn & Mat Sci London E1 4NS England;
Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China;
Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China;
Queens Univ Belfast Sch Mech & Aerosp Engn Belfast BT9 5AG Antrim North Ireland;
Kunming Univ Sci & Technol Fac Transportat Engn Kunming 650500 Yunnan Peoples R China;
Chongqing Univ State Key Lab Mech Transmiss Chongqing 400044 Peoples R China|Chongqing Univ Sch Automot Engn Chongqing 400044 Peoples R China;
Lithium-ion batteries; State of charge; Long short-term memory network; Adaptive H-Infinity filter;
机译:一种使用长短期存储器网络和自适应Cubature Kalman滤波器的锂离子电池的充电元件估计的组合方法
机译:通过将增量自回归和移动平均建模与自适应H-无穷大滤波器相结合,可以在线估算锂离子电池的充电状态
机译:通过使用Adaptive H-Infinity滤波器组合增量自回归和移动平均建模的锂离子电池的在线状态
机译:具有长短期记忆的递归神经网络用于锂离子电池的充电状态估计
机译:基于改进的戴维南电路模型的神经网络锂离子电池充电状态估计
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:通过使用Adaptive H-Infinity滤波器组合增量自回归和移动平均建模的锂离子电池的在线状态