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
Shenzhen Univ Coll Phys & Optoelect Engn Key Lab Optoelect Devices & Syst Minist Educ & Guangdong Prov Shenzhen 518060 Peoples R China;
Shenzhen Univ Coll Phys & Optoelect Engn Key Lab Optoelect Devices & Syst Minist Educ & Guangdong Prov Shenzhen 518060 Peoples R China;
Shenzhen Univ Coll Phys & Optoelect Engn Key Lab Optoelect Devices & Syst Minist Educ & Guangdong Prov Shenzhen 518060 Peoples R China;
Shenzhen Univ Coll Phys & Optoelect Engn Key Lab Optoelect Devices & Syst Minist Educ & Guangdong Prov Shenzhen 518060 Peoples R China;
Shenzhen Univ Coll Phys & Optoelect Engn Key Lab Optoelect Devices & Syst Minist Educ & Guangdong Prov Shenzhen 518060 Peoples R China|Shenzhen Univ Guangdong Lab Artificial Intelligence & Digital E Shenzhen 518060 Peoples R China;
State of charge; Long short-term memory network; Adaptive cubature Kalman filter; Lithium-ion batteries;
机译:基于自适应高度Cubature Kalman滤波器的锂离子电池的负荷估计
机译:基于自适应平方根扩展卡尔曼滤波器的复杂条件下电力锂离子电池的电荷估计方法
机译:一种使用新型自适应扩展卡尔曼滤波器的EV功率锂离子电池的充电估计方法
机译:基于神经网络组合方法的锂离子电池和Unscented Kalman滤波器的充电状态估计
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:一种在随机振动环境中使用长短期存储器网络和卡尔曼滤波器的MEMS陀螺仪误差补偿的组合方法
机译:一种新型关节支持向量机 - 锂离子电池充电预测自适应状态的Cubature Kalman滤波方法