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孟锦豪

日期:2019年11月27日     本文发布:www.3499.com

  孟锦豪  副研究员

   专业:电气工程

   研究方向:电力储能系统的建模与分析、锂电池的建模及状态估计、混合储能系统的能量管理。

     电子邮箱:jinhao@scu.edu.cn, scmjh2008@163.com 

   地址:www.3499.com望江校区高压电实验室

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- www.3499.comwww.3499.com 副研究员  团队:电力系统稳定与控制研究团队  实验室:www.3499.com新能源实验室

科研项目

在研的科研项目:

[1] www.3499.com人才引进经费,2019.12-2022.12,主持;

结题的科研项目:

[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。

论文与专利

[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, vol. 31, no. 3, pp. 2226–2238, Mar. 2016. (SCI, IF=7.224, 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, IF=3.347, 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, IF=7.503)

[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, IF=7.467)

[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, IF=5.537)

[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, IF=4.614)

[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, IF=7.467)

[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, IF=2.217,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, IF=1.483)

[10] A.-I. Stroe, J. Meng, D.-I. Stroe, M. ?wierczyński, R. Teodorescu, and S. K. K?r, “Influence of Battery Parametric Uncertainties on the State-of-charge Estimation of Lithium Titanate Oxide-based Batteries,” Energies, vol. 11, no. 4, 2018. (SCI, IF=2.707)

[11] M. Ricco, J. Meng, T. Gherman, G. Grandi, R. Teodorescu, “Smart Battery Pack for Electric Vehicles Based on Active Balancing with Wireless Communication Feedback,” Energies, vol. 12, no. 20, 2019. (SCI, IF=2.707)

[12] W. Li, Z. Jiao, Q. Xiao, J. Meng, H. Jia, R. Teodorescu, and F. Blaabjerg, “A Study on Performance Characterization Considering Six-Degree-of-Freedom Vibration Stress and Aging Stress for Electric Vehicle Battery Under Driving Conditions,” IEEE Access, vol. 7, 2019. (SCI, IF=4.098)

[13] X. Sui, D.-I. Stroe, S. He, X. Huang, J. Meng, R. Teodorescu, “The Effect of Voltage Dataset Selection on the Accuracy of Entropy-Based Capacity Estimation Methods for Lithium-Ion Batteries,” Applied Sciences, vol. 9, no. 19, 2019. (SCI, IF=2.217)

[14] 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.

[15] 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.

[16] 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.

[17] 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.

[18] 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.

[19] 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.

[20] 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.

国家发明专利

[1] 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:109752660A2019-5-14.

[2] 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:109633472A, 2019-4-16.

[3] 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:109633473A2019-4-16.

[4] 骆光照, 张蓉, 张莎, 涂文聪, 韩复振, 孟锦豪. 一种基于优化灰色预测补偿的永磁同步电机转速控制方法 [P]. 陕西:CN104242744A, 2014-12-24.


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