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    吴慕遥

    • 讲师 硕士生导师
    • 教师拼音名称:wumuyao
    • 出生日期:1995-12-08
    • 入职时间:2022-12-27
    • 所在单位:车辆工程系
    • 学历:博士研究生毕业
    • 办公地点:安徽省合肥市屯溪路193号合肥工业大学格物楼515
    • 性别:男
    • 联系方式:18256580186
    • 学位:工学博士学位
    • 在职信息:在职
    • 毕业院校:中国科学技术大学
    • 学科:车辆工程
    • 2022-12-01曾获荣誉当选:博士研究生国家奖学金
    • 2022-05-30曾获荣誉当选:安徽省优秀毕业生
    • 2022-05-30曾获荣誉当选:中国科学技术大学优秀毕业生
    • 2019-12-09曾获荣誉当选:中科大-苏州工业园区奖学金

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    Thermo-mechanical behavior evolution analysis and fusion SOC estimation of cylindrical LiFePO4 batteries

    点击次数:

    影响因子:9.4

    DOI码:10.1016/j.energy.2025.138867

    发表刊物:Energy

    关键字:Cylindrical LiFePO4 batteries; Thermo-mechanical behavior evolution; Fusion SOC estimation; Interpretability analysis

    摘要:The intricate coupling among electrical, thermal, and mechanical dynamics in cylindrical LiFePO4 batteries poses significant challenges to accurate SOC estimation. To address this, our study conducts a comprehensive comparative analysis of the thermal-mechanical behavior evolution characteristics of cylindrical LiFePO4 batteries, across a wide temperature range and different aging stages. The core innovation of this work lies in the development of a fusion SOC estimation methodology that integrates electro-thermal-mechanical behaviors. A novel contribution rate-behavior mapping function is introduced to quantitatively evaluate and visualize the influence of each physical behavior on SOC estimation, thereby significantly enhancing its transparency and interpretability. Experimental observations reveal that both thermal and strain dynamics exhibit distinct patterns, and strain demonstrates strong SOC-dependent characteristics, with evident asymmetry between charge and discharge processes. Furthermore, the aged battery demonstrates more pronounced fluctuations in temperature and strain, with mechanical behavior showing higher sensitivity to ambient temperature variations compared to the fresh battery. The proposed fusion method achieves remarkable SOC estimation accuracy emulating real-world scenarios: at 0.1 Hz, the mean absolute error (MAE) and root mean square error (RMSE) remain below 1.10 % and 2.00 %, at 0.03 Hz, MAE and RMSE are maintained below 1.70 % and 2.30 %. Compared with no-mechanical behavior fusion, it achieves average reductions of 72.68 % in MAE and 69.69 % in RMSE at 0.1Hz, and the improvements reach 65.11 % and 63.96 % at 0.03Hz. Comparative with conventional data-driven methods, it achieves average reductions of 30.10 % in MAE and 31.51 % in RMSE at 0.1Hz, and the improvements reach 28.82 % and 29.62 % at 0.03Hz.

    备注:中科院1区Top

    合写作者:Changpeng Tan

    第一作者:Muyao Wu

    论文类型:期刊论文

    通讯作者:Li Wang

    论文编号:138867

    学科门类:工学

    文献类型:J

    卷号:338

    ISSN号:0360-5442

    是否译文:

    发表时间:2025-10-15

    收录刊物:SCI、EI

    发布期刊链接:https://www.sciencedirect.com/science/article/pii/S0360544225045098?ref=pdf_download&fr=RR-2&rr=98eb413a9d0948b7