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Zhang, D. (author), Wang, Zhenpo (author), Liu, Peng (author), She, Chengqi (author), Wang, Qiushi (author), Zhou, Litao (author), Qin, Z. (author)
Accurately evaluating battery degradation is not only crucial for ensuring the safe and reliable operation of electric vehicles (EVs) but also fundamental for their intelligent management and maximum utilization. However, the non-linearity, non-measurability, and multi-stress coupled operating conditions have posed significant challenges for...
journal article 2024
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Ji, Y. (author), Fu, Xiaoqian (author), Ding, Feng (author), Xu, Yongtao (author), He, Yang (author), Ao, Min (author), Xiao, Fulai (author), Chen, Dihao (author), Dey, P. (author), Qin, Wentao (author), Xiao, Kui (author), Ren, Jingli (author), Kong, Decheng (author), Li, Xiaogang (author), Dong, Chaofang (author)
Efficiently designing lightweight alloys with combined high corrosion resistance and mechanical properties remains an enduring topic in materials engineering. Due to the inadequate accuracy of conventional stress-strain machine learning (ML) models caused by corrosion factors, a novel reinforcement self-learning ML algorithm combined with...
journal article 2024