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收藏A novel Long-term degradation trends predicting method for Multi-Formulation Li-ion batteries based on deep reinforcement learning基于深度强化学习的多配方锂离子电池长期退化趋势预测方法
Wang, Chao; Ding, Yu; Yan, Ning; Ma, Liang; Ma, Jian; Lu, Chen; Yang, Chao; Su, Yuzhuan; Chong, Jin; Jin, Haizu; Lin, Yongshou
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收藏A hybrid transfer learning scheme for remaining useful life prediction and cycle life test optimization of different formulation Li-ion power batteries不同配方锂离子动力电池剩余寿命预测和循环寿命试验优化的混合迁移学习方案
Ma, Jian; Shang, Pengchao; Zou, Xinyu; Ma, Ning; Ding, Yu; Sun, Jinwen; Cheng, Yujie; Tao, Laifa; Lu, Chen; Su, Yuzhuan; Chong, Jin; Jin, Haizu; Lin, Yongshou
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收藏Cycle life test optimization for different Li-ion power battery formulations using a hybrid remaining-useful-life prediction method使用混合剩余寿命预测方法对不同锂离子动力电池配方的循环寿命测试优化
Ma, Jian; Xu, Shu; Shang, Pengchao; Ding, Yu; Qin, Weili; Cheng, Yujie; Lu, Chen; Su, Yuzhuan; Chong, Jin; Jin, Haizu; Lin, Yongshou
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收藏A modified reliability model for lithium-ion battery packs based on the stochastic capacity degradation and dynamic response impedance基于随机容量退化和动态响应阻抗的锂离子电池组可靠性修正模型
Xia, Quan; Wang, Zili; Ren, Yi; Tao, Laifa; Lu, Chen; Tian, Jun; Hu, Daozhong; Wang, Yituo; Su, Yuzhuan; Chong, Jin; Jin, Haizu; Lin, Yongshou
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