汤爱华，男，博士，教授/硕士生导师，IEEE会员，中国电工技术学会会员、IEEE PES 电动汽车动力电池技术分委会常务理事，机械工程学期刊编委，重庆理工大学学报（自然科学）青年编委，中国电工技术学会科普传播专家，重庆理工大学首批“士继英才”领军人才，2017年6月毕业于北京理工大学电动车辆国家工程实验室，获博士学位。目前主要从事新能源汽车、电动汽车动力电池智能监测、故障诊断与安全预警的基础理论与工程应用研究。近年来主持国家自然科学基金面上项目、重庆市自然科学基金面上项目、省部级重点项目及企业项目10余项。近年来在IEEE T INTELL TRANSP、eTransportation、APPL ENERG、ENERGY、J ENERGY STORAG等国内外重要期刊发表学术论文50余篇，其中，一作/通讯作者SCI收录26篇，ESI高被引论文1篇，指导学生获ICEIV2022优秀青年学者奖，申请国家发明专利18项，受邀担任多个国际学术会议分会场主席，Energies、Processes等SCI源期刊客座主编，电工技术学报特约副主编，多个顶级SCI期刊审稿人。
新能源汽车，电动汽车动力电池系统建模及状态估计，储能与动力锂离子电池系统寿命预测，基于大数据的动力电池系统性能评价、故障诊断及安全预警，氢燃料电池技术，人工智能理论及应用
[1] 锂离子电池储能系统性能衰退演化机理及多维评估方法.国家级(52277213), 国家自然科学基金面上项目, 2023.01～2026.12,主持,在研；
[2] 基于云端数据的新能源汽车动力电池健康状态预测及充电安全. 省部级重点( KJZD-K202201103), 重庆市教委科学技术研究计划重点项目, 2023.10～2026.09,主持,在研;
[3] 基于日常片段充电数据的动力电池健康状态估计及剩余寿命预测. 省部级重点( KJZD-K202201103), 重庆市教委科学技术研究计划重点项目, 2022.10～2025.09,主持,在研;
[4]电动汽车锂离子动力电池多场耦合机理及多模型动态参数/状态协同估计.省部级( cstc2021jcyj-msxmX0464), 重庆市自然科学基金（面上项目），2021.07～2023.06, 主持,在研;
[5] 电动汽车锂电池多模型建模与动态状态融合估计, 重庆理工大学科研启动基金资助项目， 2021.07～2024.06, 主持,在研;
[6]多尺度下电动汽车锂离子动力电池老化失效研究，四川省教育厅项目，2016.07～2018.06，主持;
[7]多尺度下纯电动车辆动力电池老化（失效）研究，自贡市重点科技计划项目, 2016.1～2017.12，主持;
[8]旅客登机梯车TK-eKT58动力电池SOC精确估计技术研究, 企业委托项目，2021.01～2023.01, 主持;
[9]基于三元锂离子电池全生命周期容量衰减规律研究, 企业委托项目, 2021.12～2022.12, 主持;
[10]基于车桩运行大数据的充电安全预警服务, 企业委托项目, 2022.05～2022.09,主持.
[1] Aihua Tang, Zhikang Wu, Tingting Xu, et al. Week-level early warning strategy for thermal runaway risk based on real-scenario operating data of electric vehicles[J], eTransportation,2024,19,doi: https://doi.org/10.1016/j.etran.2023.100308.
[2] Aihua Tang, Xinyu Wu, Tingting Xu, et al. State of health estimation based on inconsistent evolution for lithium-ion battery module. Energy 2024,286,129575. https://doi.org/10.1016/j.energy.2023.129575
[3] Aihua Tang, Peng Gong, Yukun Huang, et al. Orthogonal Design based Pulse Preheating Strategy for Cold Lithium-ion batteries [J], Applied Energy. 2024, 355,122277.
https://doi.org/10.1016/j.apenergy.2023.122277
[4] Quanqing Yu,Yuwei Nie,Shizhuo Liu, Junfu Li, Aihua Tang*,State of Health Estimation Method for Lithium-ion Batteries Based on Multiple Dynamic Operating Conditions[J], Journal of Power Sources2023, 582:233541. https://doi.org/10.1016/j.jpowsour.2023.233541.
[5] Aihua Tang, Yukun Huang, Shangmei Liu, et al. A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models[J], Applied Energy. 2023, 348,121578.
https://doi.org/10.1016/j.apenergy.2023.121578
[6] Aihua Tang, Yihan Jiang, Yuwei Nie, et al. Health and lifespan prediction considering degradation patterns of lithium-ion batteries based on transferable attention neural network[J], Energy,2023,279(15),128137.
[7]Aihua Tang, Yihan Jiang, Quanqing Yu, Zhigang Zhang, A hybrid neural network model with attention mechanism for state of health estimation of lithium-ion batteries[J], Journal of Energy Storage, 2023, 68:107734.
[8] Aihua Tang, Lin Yang, Tao Zeng, Quanqing Yu*.Cascade control method of sliding mode and PID for PEMFC air supply system[J]. Energies, 2023, 16 (1),228,1-13. https://doi.org/10.3390/en16010228.
[9]Aihua Tang, Peng Gong, Yukun Huang, Xinyu Wu, Quanqing Yu. Research on pulse charging current of lithium-ion battery for electric vehicles in low-temperature environment. Energy Reports.2023,9,1447-1457.
[10] Aihua Tang, Chun Wang,Dongyang Zhang, et al. A multi-model real covariance-based battery state-of-charge fusion estimation method for electric vehicles using ordered weighted averaging operator. International Journal of Energy Research, 2022,13 July 2022. http://doi.org/10.1002/er.8392., IF=5.164
[11] Quanqing Yu, Yukun Huang, Aihua Tang*, et al. OCV-SOC-Temperature relationship construction and state of charge estimation for a series-parallel lithium-ion battery pack[J]. IEEE Transactions on Intelligent Transportation Systems.2023,24(6),6362-6371. (ESI高被引)
[12] Chun Wang, Rui Liu and Aihua Tang*, Energy Management Strategy of Hybrid Energy Storage System for Electric Vehicles Based on Genetic Algorithm Optimization and Temperature Effect [J]. Journal of Energy Storage, 2022, 51: 104314. DOI:10.1016/j.est.2022.104314.
[13] Aihua Tang*, Lei Yao, Peng Gong, and Yihan Jiang. Lithium-ion battery state-of-charge estimation of an order-reduced physics-based model in electric vehicles considering erroneous initialization[J]. International Journal of Energy Research. DOI: 10.1002/er.7403, 2021,12,113, IF=5.164
[14] Cheng Lin, Aihua Tang*, Jilei Xing. Evaluation of electrochemical models based battery state-of-charge estimation methods for Electric Vehicles [J]. Applied Energy. DOI:10.1016/j.apenergy.2017.05.109. IF=9.746
[15] Cheng Lin, Jilei Xing, Aihua Tang*. Failure Analysis of Electrochemical-mechanical Interactions within Nanowire Electrode Materials of Lithium-ion Batteries. Journal of Nanoscience and Nanotechnology (2017).
[16] Aihua Tang, Guangzhong Hu, Ming Liu. Mechanical Degradation of Electrode Materials within Single Particle Model in Li-ion Batteries for Electric Vehicles [J]. Journal of Mathematical Chemistry,2017(6):1-13.
[17] Cheng Lin, Aihua Tang*, Ningning Wu, Jilei Xing. Analysis for Mechanical Failure of DISs with Graphite Anode in Lithium ion Batteries for Electric Vehicles [J]. Nanomaterials and Nanotechnology, 2016:6(1-7),DOI: 10.1177/1847980416680806.
[18] Aihua Tang*, Yuanhang Yang, Quanqing Yu *, Zhigang Zhang, Lin Yang. A review of life prediction methods for PEMFCs in electric vehicles[J]. sustainability,2022, 14,9842
[19] 汤爱华*，龚鹏，姚疆，张莹莹.电动汽车用锂离子动力电池大功率快充方法研究[J].南京理工大学学报（自然科学版）.45(6):761-772, 2021.12. (CSCD,北大中文核心)
[20] 于全庆，王灿，李建明，汤爱华，赵立军，多拓扑结构锂电池组外短路特性分析及模型评价，机械工程学报，2023,59，1-14.(EI收录)
注：*为通讯作者
[1] 汤爱华.基于有序加权平均算子的动力电池多模型融合估计方法，2021.202111177546.0
[2] 汤爱华.一种基于证据理论的动力电池多模型容错融合建模方法，2021. 202111177852.4
[3] 汤爱华. 基于贝叶斯概率的动力电池多算法融合SOC估计方法，2022. 202210135245.X
[4]汤爱华.一种基于0-1规划的汽车零配件生产排程设计方法、系统及设备2022.202210242862.X
[5] 汤爱华. 基于神经网络的并联电池组安全预警方法，2022. 202210556458X
[6] 汤爱华. 用于五阶恒流快速充电的电流选取方法，2022. 202210583641.9
[7] 汤爱华. 用于电池组的温度-OCV-SOC响应面构建方法，2022. 2022106036730
[8] 汤爱华. 一种计及不一致性的储能电池系统状态估算方法，2022. 202210783435.2
[9] 汤爱华. 适用于多工况全电量区间的动力电池状态估算方法,2022. 202210744779.2
[10] 汤爱华. 基于深度学习的不同老化路径储能电池健康状态估计方法，2022. 2022108617339
[11] 汤爱华. 基于迁移学习微调策略的多类型储能电池容量估计方法，2022. 2022108592990
[12] 汤爱华. 基于混合深度神经网络的储能电池端到端容量估计方法，2022. 2022108592825
[13] 汤爱华. 基于PEMFC供气系统的滑模与PID级联控制方法，2022. 2022113135961
[14] 汤爱华. 基于三维响应面的脉冲电流最优频率获取方法，2022. 2022115066171
[15] 汤爱华. 基于支路电流估计误差的并联电池组健康状态估计方法，2023. 202310742319.0
国际学术会议
The 5th International Conference on Applied Energy (ICEIV2022)大会副秘书长，The 4th International Conference on Electric and Intelligent Vehicles (ICEIV2021, 南京) 大会副秘书长及电池管理系统分会场主席，The 8th International Conference on Applied Energy (ICAE2016, 北京) 和 International Conference on Energy, Ecology and Environment 2019 (ICEEE2019 挪威) 等多个国际学术会议分会主席
Energies、Processes等SCI源期刊客座主编，机械工程学期刊编委，IEEE Transactions on Industrial Electronics、IEEE Transactions on Mechatronics, IET Intelligent Transport Systems, IET Power Electronics, Applied Energy, Energy, Journal of Mechanical Engineering Science, International Journal of Energy Research, International Journal of Electrochemical Science, Energy Storage, Electrochimica Acta等SCI期刊
E-mail：aihuatang@cqut.edu.cn
