于全庆，博士，哈尔滨工业大学威海校区汽车工程学院副教授，威海市新能源车辆控制与仿真重点实验室副主任，美国韦恩州立大学及马里兰大学帕克分校访问学者。目前担任中国自动化学会车辆控制与智能化专委会委员、中国计算机学会智能汽车分会执行委员、中国电源学会交通电气化专委会委员、中国电工技术学会青工委委员、IEEE PES(中国)电动汽车技术委员会动力电池分委会秘书长和内蒙古汽车环境测试产业技术创新战略联盟理事会理事。担任电气工程学报、重庆理工大学学报、Batteries、Energies、Green Energy and Intelligent Transportation等期刊青年编委/编委。主要从事储能系统及载运工具的电动化和智能化研究。主持国家自然科学基金面上、山东省自然科学基金面上等项目。申请发明专利31项，发表学术论文70余篇，9篇先后入选“ESI全球高被引论文”，先后获2017年ICEEE国际会议最佳论文奖、2019年电工技术学会年会优秀论文奖、2021年中国机械工程学会优秀论文奖、第一届电源学会优秀博士学位论文提名奖、第四届《机械工程学报》高影响力论文奖、第34届世界电动车大会最佳论文奖和2022年威海市青年科技奖; 入选2022年和2023年“全球前2%顶尖科学家”榜单。 奖励荣誉 2017年ICEEE国际学术会议最佳论文奖 2019年电工技术学会年会优秀论文奖 2020年第四届《机械工程学报》高影响力论文奖 2020年第一届中国电源学会优秀博士学位论文提名奖 2021年中国机械工程学会优秀论文奖 2021年第34届世界电动车大会最佳论文奖 2021年 IEEE I&CPS Asia 国际学术会议优秀论文奖 2021年哈尔滨工业大学本科优秀毕业设计指导教师 2022年威海市第八届青年科技奖 2022年哈尔滨工业大学本科优秀毕业设计指导教师 2023年哈尔滨工业大学优秀硕士毕业设论文指导教师 入选 “全球前2%顶尖科学家”2022榜单 教研项目 车辆类专业《人工智能入门》课程教学内容改革，教育部产学合作协同育人项目，教育部高等教育司 《动力电池安全技术》课程改革与实践，教育部产学合作协同育人项目，教育部高等教育司 面向汽车类专业的四育人模式研究与实践，山东省本科教学改革研究项目，山东省教育厅 基于“I ＋ π”导师制的新工科智能车辆工程学生创新能力培养模式研究，哈尔滨工业大学 《动力电池安全技术》双语课，哈尔滨工业大学 汽车工程学院 科研项目 电池系统故障诊断及容错控制研究，中央高校基本科研业务费专项，2020.1-2021.12 车载锂离子动力电池组自适应建模和高精度状态估计方法研究，威海市科研创新基金，2021.1-2022.12 基于人工智能的电池系统故障诊断研究，潍柴专项基金，2021.1-2025.12 面向主动安全的车载动力电池系统峰值功率预测研究，国家重点实验室开放基金，20201208，2021.01-2023.10 车用动力电池系统故障诊断方法研究，山东省自然科学基金面上项目，ZR2020ME209，2021.1-2023.12 锂离子电池系统故障多维演化机理和诊断方法研究，国家自然科学基金面上项目，52177210，2022.1-2025.12 锂离子电池储能系统全寿命周期应用安全技术，国家重点研发计划子课题，2021YFB2402002，2021.12-2024.11 多传感器数采系统，北京环境特性研究所，2022.7 - 2022.12

电源管理及控制，机器视觉，深度学习，无人驾驶

学会/期刊等 中国自动化学会车辆控制与智能化专业委员会 委员 中国计算机学会智能汽车分会执行 委员 中国电源学会交通电气化专业委员会 委员 中国电工技术学会青年工作委员会 委员 IEEE PES(中国)电动汽车技术委员会动力电池分委会 秘书长 内蒙古汽车环境测试产业技术创新战略联盟理事会 理事 电气工程学报 青年编委 重庆理工大学学报 青年编委 Green Energy and Intelligent Transportation 青年编委 Batteries 编委 Energies 编委； Energy and AI 客座编辑 机械工程学报 客座编辑 电工技术学报 客座编辑。 国内/国际学术会议 ICAE2016国际会议 分会场主席 ICAE2019国际会议 分会场主席 ICAE2020国际会议 分会场主席 ICEIV2021国际会议 分会场主席及组委会秘书 EVS34国际会议 分会场主席 第六届交通电气化论坛 分会场主席 ICAE2022国际会议 分会场主席 ICEIV2022国际会议 分会场主席及组委会委员 CPEEC & CPSSC 2022 分会场主席 2023 Enegies Seminar 主席 2023 Batteries Seminar 主席 大会/分会场特邀报告人 2020年第五届电池设计与管理青年学者论坛 分会场特邀报告 2021年能源科技与工程管理国际会议（ETEM 2021）大会报告 2022年第二届动力科学与能源工程国际会议（ICDSEE 2022）大会报告 2022年SAE国际汽车安全与测试大会 分会场特邀报告 2022年ICEIV2022国际学术会议分会场特邀报告 2023年中国储能技术产教融合大会 分会场特邀报告 第六届机械、电气与材料应用国际学术会议 (MEMA 2023)大会报告

审稿中 Y. Huang, A. Tang, Y. Xu, Z. Zhang, F. Yan, Y. Tan, X. Jin, Q. Yu*. Data-Physics-Driven estimation of battery state of charge and capacity based on Gaussian distribution fusion. Energy 2023, Under Review. (一区，IF=9) A. Tang, Y. Xu, Y. Nie, C. Wang, Y. Zhang, Q. Yu*. Flexible Physics-Informed Deep Learning for Estimating Lithium-ion Battery State of Health in Dynamical Operation. IEEE Transactions on Transportation Electrification 2023, Under Review. (一区，IF=7) C. Wang, C. Wan, Q. Yu*, J. Li, W. Shen. Voltage Micro Anomaly Detection of Lithium-ion Batteries Based on A Novel Encoder-Decoder Model. Energy 2023, Under Review. (一区，IF=9) A. Tang, Z. Wu, T. Xu, X. Wu, Y. Zhao, Q. Yu*. Week-level early warning method for thermal runaway risk based on real-scenario operating data of electric vehicles. eTransportation 2023, Under Review. (一区，IF=11.9) Y. Yang, Y. Nie, J. Li, S. Liu, L. Zhao, Q. Yu*. A dual-timescale joint estimation framework for battery state of charge and state of health based on deep transfer learning model. Journal of Energy Storage 2023, Under Review. (一区，IF=9.4). J. Li , X. Li, X. Hu, Q. Yu. Parameter identification method of multi-particle model for lithium-ion batteries. Journal of Energy Storage 2023, Under Review. (一区，IF=9.4) S. Guo, X. Jiang, W. Shen, Y. Wang*, C. Ma, Q. Yu*. Investigation on the coupling effect of AC heating strategy and cycles on battery performance under low temperatures. Energy 2023, Under Review. (一区，IF=9) 代表性期刊论文 A. Tang, X. Wu, T. Xu, Y. Hu, S. Long, Q. Yu*. State of health estimation based on inconsistent evolution for lithium-ion battery module. Energy 2023:129575. DOI: 10.1016/j.energy.2023.129575. (一区，IF=9) X. Cheng, X. Liu, X. Li, Q. Yu*. An intelligent fusion method for state of charge estimation of lithium-ion batteries. Energy 2023:129462. DOI:10.1016/j.energy.2023;286:129462. (一区，IF=9). S. Liu, Y. Nie, A. Tang, J. Li, Q. Yu*. C Wang, Online health prognosis for lithium-ion batteries under dynamic discharge conditions over wide temperature range. eTransportation 2023;18:100296. (一区，IF=11.9) J. Li*, T. Li , Y. Wang, S. Guo, Z. Wang, M. Zhao, Q. Yu. Internal fault diagnosis method for lithium batteries based on a failure physical model. Engineering Failure Analysis 2023;154:107714. (二区，IF=4) S. Peng, Y. Sun, D. Liu, Q. Yu*, J. Kan, M. Pecht. State of health estimation of lithium-ion batteries based on multi-health features extraction and improved long short-term memory neural network. Energy 2023;282:108126. (一区，IF=9) Q. Yu; Y. Nie; S. Liu; J. Li; A. Tang*. State of health estimation method for lithium-ion batteries based on multiple dynamic operating conditions. Journal of Power Sources 2023;582:233541. (一区，IF=9.2) Q. Yu, Y. Nie, S. Peng*, Y .Miao, et al. Evaluation of the Safety Standards System of Power Batteries for Electric Vehicles in China. Applied Energy 2023;349:121674. (一区，IF=11.2) A. Tang, Y. Huang, S. Liu, Q. Yu*, et al. A novel lithium-ion battery state of charge estimation method based on the fusion of neural network and equivalent circuit models. Applied Energy 2023;348:121578. (一区，IF=11.2) Y. Yang, R. Wang, S. Zhao, Q. Yu*, et al. Towards a safer lithium-ion batteries: a critical review on cause, characteristics, warning and disposal strategy for thermal runaway. Advances in Applied Energy 2023;11:100146. A. Tang, P. Gong, Y. Huang, X. Wu, Q. Yu*. Research on pulse charging current of lithium-ion batteries for electric vehicles in low-temperature environment. Energy reports 2023;9:1447-1457. (二区，IF=5.2) A. Tang, Y. Jiang, Y. Nie, Q. Yu*, et al. Health and lifespan prediction considering degradation patterns of lithium-ion batteries based on transferable attention neural network. Energy 2023;279:128137. (一区，IF=9) Q. Yu, C. Wang, J. Li, R. Xiong*, M Pecht. Challenges and outlook for lithium-ion battery fault diagnosis methods from the laboratory to real world applications. eTransportation 2023;17:100254. (一区，IF=11.9) Y. Yang, L. Zhao, Q. Yu*, et al. State of charge estimation for lithium-ion batteries based on cross-domain transfer learning with a feedback mechanism. Journal of Energy Storage 2023;70:108037. (一区，IF=9.4) A. Tang, Y. Jiang, Q. Yu*, Z Zhang. A hybrid neural network model with attention mechanism for state of health estimation of lithium-ion batteries. Journal of Energy Storage 2023;68:107734. (一区，IF=9.4) Q. Yu, Y. Huang, A. Tang*, et al. OCV-SOC-Temperature relationship construction and state of charge estimation for a series-parallel lithium-ion battery pack. IEEE Transactions on Intelligent Transportation Systems 2023;24(6):6362-6371. (一区，IF=8.5) (ESI高被引论文) 于全庆，王灿，李建明等. 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(6):159-172。(EI) Q. Yu*, Y. Liu, S Long, J. Li, W. Shen. A branch current estimation and correction method for a parallel connected battery pack based on dual BP neural networks. Green Energy and Intelligent Transportation 2022;2: 100029. (中国科技期刊卓越行动计划高起点新刊). S. Xu, Y. Wang, J. Shao, J. Li*, Q. Yu. An electrochemical-thermal coupling model for prismatic lithium-ion batteries over wide temperature range. Applied Thermal Engineering 2022; 217:119282. （一区，IF=6.4） Z. Chen, R. Xiong, Z. Wang, Q. Yu. Pontryagin's Minimum Principle-based Power Management of Plug-in Hybrid Electric Vehicles to Enhance the Battery Durability and Thermal Safety. IEEE Transactions on Transportation Electrification 2022. DOI 10.1109/TTE.2022.3201029.（一区，IF=7） Q. Yu*, L. Dai, R. Xiong, et al. Current sensor fault diagnosis method based on an improved equivalent circuit battery model. Applied Energy 2022;310:118588. (一区，IF=11.2) Z. Chen, B. Zhang, R. Xiong*, W. Shen, Q. Yu. Electro-thermal coupling model of lithium-ion batteries under external short circuit. Applied Energy 2021;293:116910 . (一区，IF=11.2) R. Xiong, W. Sun, Q. Yu*, F. Sun. Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles. Applied Energy 2020;279:115855. (一区，IF=11.2) (ESI高被引论文) R. Xiong, L. Li, Q. Yu*, Q. Jin, R. Yang. A set membership theory based parameter and state of charge co-estimation method for all-climate batteries. Journal of Cleaner Production 2020;249:11389. (一区，IF=11.1) C. Wang, R. Yang*, Q. Yu, Wavelet transform based energy management strategies for plug-in hybrid electric vehicles considering temperature uncertainty. Applied Energy 2019;256:113928. (一区，IF=11.2) Q. Yu, R. Xiong*, R. Yang, M. G. Pecht. Online capacity estimation for lithium-ion batteries through joint estimation method. Applied Energy 2019;255:113817. (一区，IF=11.2) R. Xiong, Q. Yu*, W. X. Shen, C. Lin, F. Sun. A sensor fault diagnosis method for a lithium-ion battery pack in electric vehicles. IEEE Transactions on Power Electronics 2019;34(10):9709-9718. (一区，IF=6.7) (ESI高被引论文) J. Tian, R. Xiong*, Q. Yu. Fractional order model based incremental capacity analysis for degradation state recognition of lithium-ion batteries. IEEE Transactions on Industrial Electronics 2019;66(2):1576-1584. (一区，IF=7.7) (ESI高被引论文) R. Xiong, L. Li, Z. Li, Q. Yu*, et al. An electrochemical model-based degradation state identification method of Lithium-ion battery for all-climate electric vehicles application. Applied Energy 2018;219:264-275. (一区，IF=11.2) Q. Yu, R. Xiong, L. Wang, et al. A comparative study on open circuit voltage models for lithium-ion batteries. Chinese Journal of Mechanical Engineering 2018;31(1):65. (二区，IF=4.2) （第四届JME高影响力论文奖）(机械工程学会优秀论文奖) R. Xiong, Y. Duan, Q. Yu*. Battery and ultracapacitor in-the-loop approach to validate a real-time power management method for an all-climate electric vehicle. Applied Energy 2018;217(1):153-165. (一区，IF=11.2)(ESI高被引论文) R. Xiong, J. Cao, Q. Yu*. Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle. Applied Energy 2018;211(1):538-548. (一区，IF=11.2) (ESI高被引论文) M. Ye, H. Guo, R. Xiong, Q. Yu*. A double-scale and adaptive particle filter-based online parameter and state of charge estimation method for lithium-ion batteries. Energy 2018:144 (1):789-799. (一区，IF=9) Q. Yu, R. Xiong, C. Lin, et al. Lithium-ion battery parameters and state-of-charge joint estimation based on H-infinity and unscented Kalman filters. IEEE Transactions on Vehicular Technology 2017;66 (10):8693-8701. (一区，IF=6.8) (ESI高被引论文) C. Lin, Q. Yu, R. Xiong, L. Y. Wang. A study on the impact of open circuit voltage tests on state of charge estimation for lithium-ion batteries. Applied Energy 2017;205(1):892-902. (一区，IF=11.2) R. Xiong, Q. Yu*, L. Y. Wang, C. Lin. A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter. Applied Energy 2017;207(1):346-353. (一区，IF=11.2) (ESI高被引论文) R. Xiong, J. Cao, Q. Yu, et al. Critical review on the battery state of charge estimation methods for electric vehicles. IEEE Access 2017;6:1832-1843. (二区，IF=3.9) (ESI高被引论文)