孟锦豪 副研究员/硕士生导师/四川大学双百人才计划
研究方向：先进电力储能技术、退役电池梯次利用技术、锂电池应用、混合储能系统的能量管理。
电子邮箱：jinhao@scu.edu.cn, scmjh2008@163.com
地址：四川大学望江校区高压楼605实验室 邮编：610065
学习与工作经历
· 2014.03-2019.06 西北工业大学自动化学院电气工程专业博士（导师：骆光照）
· 2016.12-2018.12 奥尔堡大学能源技术系联合培养博士（导师：Remus Teodorescu）
· 2019.11-至今 四川大学电气工程学院 副研究员 团队：电力系统稳定与高压直流输电团队 实验室：电气工程学院新能源实验室
科研项目
主持或参与的科研项目：
[1] 国家自然科学基金青年基金，2022，在研；
[2] 四川大学人才引进经费，2020，在研；
[3] 计及锂电池可靠性的新能源汽车快速充电策略研究, 四川省应用基础研究面上项, 2021，在研；
[4] 新能源汽车动力锂电池电-热-老化实时模型研究, 博士后基金面上项目, 2020，在研；
[5] 特殊环境机器人技术四川省重点实验室开放基金，2020，在研；
[6] 轨道交通车载电池运维芯片、算法及智能云管理系统研发, 湖南省高新技术产业科技创新引领计划（科技攻关类）, 2020, 在研；
[7] 基于云储能的AI调度策略研究，国网总部科技项目,2021，在研。
结题项目：
[1] 混合储能和多电机组合驱动系统的设计与能量管理策略研究，陕西省重点研发计划，2017.01-2018.12，主研；
[2] 基于超级电容储能的模块化多电平变换器变频运行与能量管理机制研究，国家自然科学基金，2016.01-2018.12，主研。
教学工作
本科生：《新能源发电技术》、《工程师创新训练》；研究生课程：《可再生能源发电系统的建模、分析与控制》。
代表性论文
[1] J. Meng, G. Luo, and F. Gao, “Lithium Polymer Battery State-of-Charge Estimation Based on Adaptive Unscented Kalman Filter and Support Vector Machine,” IEEE Transactions on Power Electronics, 2016, vol. 31, no. 3, pp. 2226–2238. (SCI, ESI高被引论文)
[2] J. Meng et al. “An Overview and Comparison of Online Implementable SOC Estimation Methods for Lithium-Ion Battery,” IEEE Transactions on Industry Applications, 2018, vol. 54, no. 2, pp. 1583–1591. (SCI, ESI高被引论文)
[3] J. Meng, et al. “A Simplified Model based State-of-Charge Estimation Approach for Lithium-ion Battery with Dynamic Linear Model,” IEEE Transactions on Industrial Electronics, 2019, vol. 66, no. 10, pp. 7717-7727. (SCI)
[4] J. Meng et al., “Low-complexity Online Estimation for LiFePO₄ Battery State of Charge in Electric Vehicles,” Journal of Power Sources, vol. 395, pp. 280–288, 2018. (SCI)
[5] J. Meng et al., “Lithium-ion Battery State-of-Health Estimation in Electric Vehicle Using Optimized Partial Charging Voltage Profiles,” Energy, vol.185, pp. 1054-1063, 2019. (SCI)
[6] J. Meng, et al. “A Novel Multiple Correction Approach for Fast Open Circuit Voltage Prediction of Lithium-ion Battery”, IEEE Transactions on Energy Conversion, 2019, vol. 34, no. 2, pp. 1115-1123. (SCI)
[7] L. Cai, J. Meng*, D.-I. Stroe, G. Luo, and R. Teodorescu, “An Evolutionary Framework for Lithium-ion Battery State of Health Estimation,” Journal of Power Sources, vol. 412, pp. 615–622, 2019. (SCI)
[8] J. Meng, G. Luo, M. Ricco, M. Swierczynski, D.-I. Stroe, and R. Teodorescu, “Overview of Lithium-Ion Battery Modeling Methods for State-of-Charge Estimation in Electrical Vehicles,” Applied Science, vol. 8, no. 5, pp. 659, Apr. 2018. (SCI, Invited Paper)
[9] J. Meng, L. Cai, G. Luo, D.-I. Stroe, and R. Teodorescu, “Lithium-ion Battery State of Health Estimation with Short-term Current Pulse Test and Support Vector Machine,” Microelectronics Reliability, vol. 88–90, pp. 1216–1220, 2018. (SCI)
[10] J. Meng, L. Cai, D.-I. Stroe, J. Ma, G. Luo and R. Teodorescu, “An optimized ensemble learning framework for lithium-ion Battery State of Health estimation in energy storage system”, Energy, vol. 206, 118140, 2020.(SCI)
[11] L. Cai, J. Meng*, D.-I. Stroe, G. Luo, J. Peng and R. Teodorescu, “Multi-objective Optimization of Data-driven Model for Lithium-ion Battery SOH estimation with Short-term Feature”, IEEE Transactions on Power Electronics, 2020, vol. 35, no. 11, pp. 11855-11864. (SCI)
[12] X. Du, J. Meng*, Y. Zhang, Xinrong Huang, S. Wang, P. Liu, “An Information Appraisal Procedure Endows Reliable Online Parameter Identification to Lithium-ion Battery Model,” IEEE Transactions on Industrial Electronics, 2021, doi: 10.1109/TIE.2021.309192. (SCI)
[13] J. Meng et al.,“An Automatic Weak Learner Formulation for Lithium-ion Battery State of Health Estimation”, IEEE Transactions on Industrial Electronics , 2021, doi: 10.1109/TIE.2021.**. (SCI)
[14] X. Sui, S. He, J. Meng, et al. Fuzzy entropy-based state of health estimation for li-ion batteries[J]. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020, doi: 10.1109/JESTPE.2020.**, early access. (SCI)
[15] X. Sui, S. He, S. B. Vilsen, J. Meng, R. Teodorescu, D.I. Stroe, “A review of non-probabilistic machine learning-based state of health estimation techniques for Lithium-ion battery”, Applied Energy, 2021, vol. 300, pp. 117346. (SCI)
[16] J.Wu, X. Liu, J. Meng, M.Lin, “Cloud-to-edge based state of health estimation method for Lithium-ion battery in distributed energy storage system”, Journal of Energy Storage, 2021. (SCI)
代表性会议论文
[1] J. Meng et al., “An Overview of Online Implementable SOC Estimation Methods for Lithium-ion Batteries,” in Proceedings - 2017 International Conference on Optimization of Electrical and Electronic Equipment, OPTIM 2017 and 2017 Intl Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2017, 2017, pp. 573–580.
[2] G. Luo, J. Meng, X. Ji, X. Cai, and F. Gao, “A Data Driven Model for Accurate SOC Estimation in EVs,” in 2017 IEEE International Conference on Industrial Technology (ICIT), 2017, pp. 352–357.
[3] J. Meng, G. Luo, E. Breaz, and F. Gao, “A Robust Battery State-of-charge Estimation Method for Embedded Hybrid Energy System,” in IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society, 2015, pp. 001205–001210.
[4] J. Meng, G. Luo, and F. Gao, “State-of-charge Estimation for Lithium-ion Battery Using AUKF and LSSVM,” in 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014, pp. 1–6.
[5] T. Gherman, M. Ricco, J. Meng, R. Teodorescu, and D. Petreus, “Smart Integrated Charger with Wireless BMS for EVs,” in IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, 2018, pp. 2151–2156.
[6] J. Peng, W. Liu, J. Meng, T. Meng, and G. Luo, “Initial Orientation and Sensorless Starting Strategy of Wound-Rotor Synchronous Starter/Generator,” in Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC, 2016.
[7] X. Sui, S. He, D. Stroe, X. Huang, J. Meng, R. Teodorescu, “A Review of Sliding Mode Observers based on Equivalent Circuit Model for Battery SoC Estimation,” in IEEE 28th International Symposium on Industrial Electronics (ISIE), 2019.
[8] X. Huang, Y. Li, J. Meng, X. Sui, R. Teodorescu, and D.I. Stroe, “The Effect of Pulsed Current on the Performance of Lithium-ion Batteries,” in 2020 IEEE Energy Conversion Congress and Exposition (ECCE),2020.


国家发明专利
[1] 孟锦豪, 蔡磊，彭纪昌，马俊鹏，王顺亮，刘天琪. 基于充电电压曲线几何特征的锂电池健康状态估计方法[P], 中国：2, 2021-06-01.
[2]孟锦豪, 刘平, 王建武.一种无电流传感器的电池荷电状态估计方法[P]. 公开号：A，2019-5-14.
[3] 刘平, 孟锦豪, 王建武.一种锂电池单体的荷电状态估计算法[P]. 公开号：A, 2019-4-16.
[4] 刘平, 孟锦豪, 王建武. 一种分布式电池组荷电状态估计算法[P]. 公开号：A，2019-4-16.
获奖情况
[1] 西北工业大学优秀博士毕业生
[2] 西北工业大学优秀硕士论文
[3] 西北工业大学优秀博士论文
[4] 陕西省自然科学论文三等奖，陕西省人民政府，2020，排名1/3
[5] 高空长航时无人机燃料电池系统关键技术研究及应用，陕西省高校科学技术二等奖，陕西省教育厅，2020，排名4/8。
学术兼职
IEEE会员，电工技术学会高级会员，IEEE PES电动汽车技术委员会（中国）动力电池系统技术分委会理事。
长期担任 IEEE Transaction on Power Electronics、IEEE Transaction on Industrial Electronics、IEEE Transaction on Energy Conversion、Journal of Power Sources等国内外高水平学术期刊审稿人。


欢迎各位同学联系报考我的研究生，进入电力系统稳定与高压直流输电团队，为电气工程学院新能源实验室的发展贡献力量。联系方式：jinhao@scu.edu.cn