2017年博士毕业于中国科学技术大学自动化系，获控制科学与工程博士学位（获中科院院长特别奖、中科院优博论文）

节能与新能源汽车技术、电池安全管理、综合能源系统管控、数字孪生、AI在能源系统中的应用等

2017.07-2020.01 中国科学技术大学 电子工程与信息科学系 博士后
2020.02-2023.03 中国科学技术大学 自动化系 特任副研究员
2023.04-迄今 中国科学技术大学 自动化系 副教授

中国自动化学会自然科学一等奖 （2018.12）
中国仿真学会自然科学一等奖 （2022.12）
教育部技术发明二等奖 （2019.12）
安徽省科学技术二等奖 （2019.03）
中国自动化学会技术发明二等奖（2022.12）
中国科学院院长特别奖 （2017.08）
中国科学院优博论文 （2019.09）
中国自动化学会优秀科技工作者 （2021.12）
中国仿真学会优秀科技工作者 （2019.12）
第34届世界电动汽车大会 Excellent Paper Award （2021.06）

面向氢-电混合动力系统的寿命预测与能量管控方法研究 国家自然科学基金面上项目/基金委 (Grant No. 62373340) 2024.01-2027.12 主持
基于虚拟电厂的电动汽车充放电行为双向导引机制研究 安徽省自然科学基金能源互联网联合基金/安徽省科技厅 (Grant No. 2208085UD12) 2022.08-2025.08 主持
基于模型驱动的设计/制造/服务全域一体化技术研发 国家重点研发计划课题/科技部 (Grant No. 2020YFB1712402) 2020.11-2023.10 主持
基于贝叶斯理论的动力电池系统参数与状态联合估计方法研究 国家自然科学基金青年基金/基金委 (Grant No. 61803359) 2019.01-2021.12 主持
5G 智能电池管理系统的研发与产业化 安徽省高校协同创新项目/安徽省教育厅 (Grant No. GXXT-2019-002) 2019.11-2021.10 主持
动力能源系统的建模、状态估计与优化管理关键技术 支持“率先行动”计划中科院和中国博士后科学基金会联合资助优秀博士后项目/中科院、中国博士后科学基金会 (Grant No. 2017LH007) 2018.01-2019.12 主持
混合储能系统的建模与能量管理优化方法研究 中国博士后科学基金/中国博士后科学基金会 (Grant No. 2017M622019) 2018.01-2019.12 主持 
基于云端辅助计算的智能电池管理关键技术研究 中国科学技术大学青年创新重点基金/中国科学技术大学 (Grant No. YD2350002002) 2019.11-2021.10 主持
面向电动汽车的混合储能系统功率分配方法研究 中国科学技术大学青年创新基金/中国科学技术大学 (Grant No. WK2100100032) 2019.01-2020.12 主持

出版英文专著4部，教材1部，发表SCI论文80余篇，申请专利20余项。
专著、教材：
K. Liu, Y. Wang, X. Lai. Data Science-Based Full-Lifespan Management of Lithium-Ion Battery: Manufacturing, Operation and Reutilization. 10 April 2022, Springer Nature. (ISBN: 978-3-031-01340-9) https://doi.org/10.1007/978-3-031-01340-9
S. Wang, Y. Wang, K. Liu, J. Wu, Y. Shang, J. M. Guerrero. Battery State Estimation: Methods and models, Institution of Engineering and Technology (IET), 2021. (ISBN: 978-1-83953-529-1) https://doi.org/10.1049/PBPO212E
S. Wang, K. Liu, Y. Wang, D. Stroe, C. Fernandez, J. M. Guerrero. AI for Status Monitoring of Utility Scale Batteries, Institution of Engineering and Technology (IET), 2022. (ISBN：978-1-83953-738-7) https://doi.org/10.1049/PBPO238E
S. Wang, K. Liu, Y. Wang, D. Stroe, C. Fernandez, J. M. Guerrero. Multidimensional Lithium-Ion Battery Status Monitoring. 2022, CRC Press. (ISBN：978-1-03235-602-0) https://doi.org/10.1201/9781003333791
陈宗海，杨晓宇，汪玉洁编著，《计算机控制工程（第2版）》，中国科学技术大学出版社，2021. 
期刊论文：
H. Xiang, Y. Wang*, X. Zhang, Z. Chen. Two-level Battery Health Diagnosis using Encoder-decoder Framework and Gaussian Mixture Ensemble Learning Based on Relaxation Voltage, IEEE Transactions on Transportation Electrification, early access. https://doi.org/10.1109/TTE.2023.3317449
H. Xiang, Y. Wang*, Z. Chen. A comprehensive study on state-of-charge and state-of-health estimation of sodium-ion batteries, Journal of Energy Storage, 72(2023), 108314. https://doi.org/10.1016/j.est.2023.108314
Y. Wang*, X. Zhang, K. Li, G. Zhao, Z. Chen. Perspectives and Challenges for Future Lithium-ion Battery Control and Management, eTransportation, 18(2023), 100260. https://doi.org/10.1016/j.etran.2023.100260
X. Zhang, Y. Wang*, Z. Chen. SoC-modified Core Temperature Estimation of Lithium-ion Battery Based on Control-Oriented Electro-thermal Model, IEEE Transactions on Power Electronics, 38(2023), 11642-11651. https://doi.org/10.1109/TPEL.2023.3288539
Y. Wang*, W. Li, Z. Liu, L. Li. An Energy Management Strategy of Hybrid Energy Storage System based on Reinforcement Learning, World Electric Vehicle Journal, vol 14, no 3, 57(2023). https://doi.org/10.3390/wevj14030057
Y. Wang*, G. Zhao. A comparative study of different fractional-order models for lithium-ion batteries, Control Engineering Practice, 133(2023), 105451. https://doi.org/10.1016/j.conengprac.2023.105451
Y. Wang*, K. Li, P. Peng, Z. Chen. Health diagnosis for lithium-ion battery by combining partial incremental capacity and deep belief network during insufficient discharge profile, IEEE Transactions on Industrial Electronics, 2022, 70(11), 11242-11250. https://doi.org/10.1109/TIE.2022.3224201
G. Zhao, Y. Wang*, Z. Chen. Health-aware multi-stage charging strategy for lithium-ion batteries based on whale optimization algorithm, Journal of Energy Storage, 55(2022), 105620. https://doi.org/10.1016/j.est.2022.105620
K. Li, Y. Wang*, Z. Chen. A comparative study of battery state-of-health estimation based on empirical mode decomposition and neural network, Journal of Energy Storage, 54(2022), 105333. https://doi.org/10.1016/j.est.2022.105333
Y. Wang*, G. Zhao, C. Zhou, M. Li, Z. Chen. Lithium-ion battery optimal charging strategy using moth-flame optimization algorithm and fractional-order model, IEEE Transactions on Transportation Electrification, early access. https://doi.org/10.1109/TTE.2022.3192174
Y. Wang*, K. Li, Z. Chen. Battery full life cycle management and health prognosis based on cloud service and broad learning, IEEE/CAA Journal of Automatica Sinica, vol. 9, no 8, 2022, 1540-1542. https://doi.org/10.1109/JAS.2022.105779
Y. Wang*, X. Kang, Z. Chen. A survey of digital twin techniques in smart manufacturing and management of energy applications, Green Energy and Intelligent Transportation, 1(2022), 100014. https://doi.org/10.1016/j.geits.2022.100014
Y. Wang*, X. Zhang, Z. Chen. Low temperature preheating techniques for lithium-ion batteries: recent advances and future challenges, Applied Energy, 313(2022), 118832. https://doi.org/10.1016/j.apenergy.2022.118832
Y. Wang*, C. Zhou, G. Zhao, Z. Chen. A framework for battery internal temperature and state of charge estimation based on fractional-order thermoelectric model, Transactions of the Institute of Measurement and Control, 2022. https://doi.org/10.1177/01423312211067293
Y. Wang*, C. Zhou, Z. Chen. Optimization of battery charging strategy based on nonlinear model predictive control, Energy, 241(2022), 122877. https://doi.org/10.1016/j.energy.2021.122877
Y. Wang, R. Xu, C. Zhou, X. Kang, Z. Chen*. Digital twin and cloud-side-end collaboration for intelligent battery management system, Journal of Manufacturing Systems, 62(2022), 124-134. https://doi.org/10.1016/j.jmsy.2021.11.006
周才杰, 汪玉洁*, 李凯铨, 陈宗海. 基于灰色关联度分析-长短期记忆神经网络的锂离子电池健康状态估计. 电工技术学报, 2022, 37(23):6065-6073. https://doi.org/10.19595/j.cnki.1000-6753.tces.211366
Y. Wang*, C. Zhou, Z. Chen. An enhanced approach for load behavior and battery residual capacity prediction using Markov chain and Monte Carlo method, IEEE Journal of Emerging and Selected Topics in Industrial Electronics, vol 4, no 1, 2023, 159-167. https://doi.org/10.1109/JESTIE.2021.3115468
X. Tang, Y. Wang*, Q. Liu, F. Gao*. Reconstruction of the incremental capacity trajectories from current-varying profiles for lithium-ion batteries, iScience, 24(10)(2021), 103103. https://doi.org/10.1016/j.isci.2021.103103
Y. Wang, M. Li, Z. Chen*. Experimental study of fractional-order models for lithium-ion battery and ultra-capacitor: modeling, system Identification, and validation, Applied Energy, 278(2020), 115736. https://doi.org/10.1016/j.apenergy.2020.115736
Y. Wang, J. Tian, Z. Sun, L. Wang, R. Xu, M. Li, Z. Chen*. A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems, Renewable & Sustainable Energy Reviews, 131(2020), 110015. https://doi.org/10.1016/j.rser.2020.110015
Y. Wang, L. Wang, M. Li, Z. Chen*. A review of key issues for control and management in battery and ultra-capacitor hybrid energy storage systems, eTransportation, 4(2020), 100064. https://doi.org/10.1016/j.etran.2020.100064
Y. Wang*, G. Gao, X. Li, Z. Chen. A fractional-order model-based state estimation approach for lithium-ion battery and ultra-capacitor hybrid power source system considering load trajectory, Journal of Power Sources, 449(2020), 227543. https://doi.org/10.1016/j.jpowsour.2019.227543
Y. Wang, Z. Chen*. A framework for state-of-charge and remaining discharge time prediction using unscented particle filter, Applied Energy, 260(2020), 114324. https://doi.org/10.1016/j.apenergy.2019.114324
Y. Wang, Z. Sun, X. Li, X. Yang, Z. Chen*. A comparative study of power allocation strategies used in fuel cell and ultracapacitor hybrid systems, Energy, 189(2019), 116142. https://doi.org/10.1016/j.energy.2019.116142
X. Tang, Y. Wang*, K. Yao, Z. He, F. Gao*. Model migration based battery power capability evaluation considering uncertainties of temperature and aging, Journal of Power Sources, 440(2019), 227141. https://doi.org/10.1016/j.jpowsour.2019.227141
Y. Wang*, X. Li, Li Wang, Z. Sun. Multiple-grained velocity prediction and energy management strategy for hybrid propulsion systems, Journal of Energy Storage, 26(2019), 100950. https://doi.org/10.1016/j.est.2019.100950
Y. Wang, Z. Sun, Z. Chen*. Energy management strategy for battery/ supercapacitor/ fuel cell hybrid source vehicles based on finite state machine, Applied Energy, 254(2019), 113707. https://doi.org/10.1016/j.apenergy.2019.113707
Y. Wang, Z. Sun, Z. Chen*. Development of energy management system based on a rule-based power distribution strategy for hybrid power sources, Energy, 175(2019), 1055-1066. https://doi.org/10.1016/j.energy.2019.03.155
X. Tang, Y. Wang*, C. Zou, K. Yao, Y. Xia, F. Gao*. A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging, Energy Conversion and Management, 180(2019), 162-170. https://doi.org/10.1016/j.enconman.2018.10.082
Y. Wang, J. Tian, Z. Chen*, X. Liu. Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles, Measurement, 131(2019), 443-451. https://doi.org/10.1016/j.measurement.2018.09.007
Y. Wang, X. Zhang, C. Liu, R. Pan, Z. Chen*. Multi-timescale power and energy assessment of lithium-ion battery and supercapacitor hybrid system using extended Kalman filter, Journal of Power Sources, 389(2018), 93-105. https://doi.org/10.1016/j.jpowsour.2018.04.012
Y. Wang, R. Pan, C. Liu, Z. Chen*, Q. Ling. Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation, Journal of Power Sources, 374(2018), 12-23. https://doi.org/10.1016/j.jpowsour.2017.11.019
Y. Wang, Z. Chen*, C. Zhang. On-line remaining energy prediction: a case study in embedded battery management system, Applied Energy, 194(2017), 688-695. https://doi.org/10.1016/j.apenergy.2016.05.081
Y. Wang, C. Liu, R. Pan, Z. Chen*. Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator, Energy, 121(2017), 739-750. https://doi.org/10.1016/j.energy.2017.01.044
Y. Wang, C. Zhang, Z. Chen*. On-line battery state-of-charge estimation based on an integrated estimator, Applied Energy, 185(2017), 2026-2032. https://doi.org/10.1016/j.apenergy.2015.09.015
Y. Wang, D. Yang, X. Zhang, Z. Chen*. Probability based remaining capacity estimation using data-driven and neural network model, Journal of Power Sources, 315(2016), 199-208. https://doi.org/10.1016/j.jpowsour.2016.03.054
Y. Wang, C. Zhang, Z. Chen*. An adaptive remaining energy prediction approach for lithium-ion batteries in electric vehicles, Journal of Power Sources, 305(2016), 80-88. https://doi.org/10.1016/j.jpowsour.2015.11.087
Y. Wang, C. Zhang, Z. Chen*, J. Xie, X. Zhang. A novel active equalization method for lithium-ion batteries in electric vehicles, Applied Energy, 145(2015), 36-42. https://doi.org/10.1016/j.apenergy.2015.01.127
Y. Wang, C. Zhang, Z. Chen*. A method for state-of-charge estimation of LiFePO4 batteries at dynamic currents and temperatures using particle filter, Journal of Power Sources, 279(2015), 306-311. https://doi.org/10.1016/j.jpowsour.2015.01.005
Y. Wang, C. Zhang, Z. Chen*. A method for state-of-charge estimation of Li-ion batteries based on multi-model switching strategy, Applied Energy, 137(2015), 427-434. https://doi.org/10.1016/j.apenergy.2014.10.034
Y. Wang, C. Zhang, Z. Chen*. A method for joint estimation of state-of-charge and available energy of LiFePO4 batteries, Applied Energy, 135(2014), 81-87. https://doi.org/10.1016/j.apenergy.2014.08.081