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1. \u5148\u8fdb\u7684\u4eba\u5de5\u667a\u80fd\u7b97\u6cd5\uff1a<\/strong>\u878d\u5408\u7535\u6c60\u5bff\u547d\u3001\u51fa\u884c\u9700\u6c42\u4e0e\u6210\u672c\u7684\u591a\u76ee\u6807\u4f18\u5316\u6a21\u578b\u3002<\/p>\n\n\n\n

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3. \u6a21\u578b\u8f7b\u91cf\u5316\u90e8\u7f72\u6280\u672f<\/strong>\uff1a \u7ed3\u5408\u84b8\u998f\u4e0e\u88c1\u526a\u6280\u672f\uff0c\u5b9e\u73b0\u6a21\u578b\u8f7b\u91cf\u5316\u5de5\u7a0b\u90e8\u7f72\u3002<\/p>\n\n\n\n

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Jing H, Ou S*<\/strong>, Lv Z, et al. Battery Safety: Mechanisms, Monitoring, and Machine Intelligence[J]. Advanced Energy Materials<\/em><\/strong>, 2026<\/strong>. JCR, Q1<\/strong>, IF 24.4.<\/strong><\/p>\n\n\n\n

Lv Z, Ou S<\/strong>*<\/strong>, Jing H, et al. Self-supervised learning for electric vehicle battery remaining useful life prediction using real-world unlabeled data[J]. Energy<\/em><\/strong>, <\/strong>2026. <\/strong>JCR, Q1,<\/strong> IF 9.0<\/strong><\/p>\n\n\n\n

Qi H, Ou S*<\/strong>, Jia Y H, et al. Cross-temporal framework for driving behavior impact on electric vehicle battery health[J]. Communications in Transportation Research<\/em><\/strong>, 2026. JCR Q1<\/strong>,<\/strong> <\/strong>IF 14.5<\/strong><\/p>\n\n\n\n

Jing H, Hu J, Ou S*<\/strong>, et al. A data-driven and physics-based model for assessing real-world usage behavior impacts on electric vehicle battery life[J]. Journal of Energy Storage, <\/em><\/strong>2026,<\/strong> JCR<\/strong> <\/strong>Q1,<\/strong> <\/strong>IF 9.8<\/strong><\/strong><\/p>\n\n\n\n

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