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[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=6.153, 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=3.654, ESI高被引论文)
[3] J. Meng, D. Stroe, M. Ricco, G. Luo, and R. Teodorescu, “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=8.236)
[4] J. Meng, M. Ricco, A. Acharya, G. Luo, M. Swierczynski, D. Stroe, R. Teodorescu, “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=9.127)
[5] J. Meng, D. Stroe, M. Ricco, G. Luo, M. Swierczynski, R. Teodorescu, “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=4.312)
[6] 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, p. 659, 2018. (SCI, IF=2.679, Feature Paper, Editor’s Choice)
[7] 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=1.589, Highly cited paper of Microelectronics Reliability since 2018)
[8] J. Meng, L. Cai, D. Stroe, J. Ma, G. Luo, R. Teodorescu, “An Optimized Ensemble Learning Framework for Lithium-ion Battery State of Health Estimation in Energy Storage System,” Energy, vol.206, pp. 118140, 2020. (SCI, IF=7.147)
[9] J. Meng, L. Cai, D. Stroe, G. Luo, X. Sui, R. Teodorescu, “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=7.147)
[10] J. Meng, L. Cai, D. Stroe, X. Huang, J. Peng, T. Liu, R. Teodorescu, “An Automatic Weak Learner Formulation for Lithium-ion Battery State of Health Estimation”, IEEE Transactions on Industrial Electronics, 2021, vol. 69, no. 3, pp. 2659-2668. (SCI, IF=8.236)
[11] L. Cai, J. Meng*, D.-I. Stroe, J. Peng, G. Luo 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, IF=6.153)
[12] 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=9.127)
[13] X. Du, J. Meng*, Y. Zhang, X. Huang, S. Wang, P. Liu, “An Information Appraisal Procedure Endows Reliable Online Parameter Identification to Lithium-ion Battery Model,” IEEE Transactions on Industrial Electronics, 2022, vol. 69, no. 6, pp. 5889-5899. (SCI, IF=8.236)
[14] D. Chen, J. Meng*, H. Huang, J. Wu, P. Liu, J. Lu, and T. Liu, “An Empirical-data Hybrid Driven Approach for Remaining Useful Life Prediction of Lithium-ion Batteries Considering Capacity Diving”, Energy, vol. 245, p.123222, 2022. (SCI, IF=7.147)
[15] H. Huang, J. Meng*, Y. Wang, L. Cai, J. Peng, J. Wu, Q. Xiao, T. Liu, and R. Teodorescu, “An Enhanced Data-Driven Model for Lithium-Ion Battery State-of-Health Estimation with Optimized Features and Prior Knowledge,” Automotive Innovation, pp. 1-12, 2022. (高质量T1级期刊)
[16] X. Du, J. Meng*, J. Peng, Y. Zhang, T. Liu, and R. Teodorescu, “Sensorless temperature estimation of lithium-ion battery based on broadband impedance measurements”, IEEE Transactions on Power Electronics, 2022, vol. 37, no. 9, pp. 10101-10105. (SCI, IF=6.153)
[17] A. Wen, J. Meng*, J. Peng, L. Cai, Q. Xiao, “Online Parameter Identification of the Lithium-Ion Battery with Refined Instrumental Variable Estimation,” Complexity, vol. 2020, 2020. (SCI, IF= 2.833)
[18] K. Liu, X. Hu*, J. Meng*, J. M. Guerrero, R. Teodorescu, “RUBoost-Based Ensemble Machine Learning for Electrode Quality Classification in Li-ion Battery Manufacturing”, IEEE/ASME Transactions on Mechatronics, 2021, DOI: 10.1109/TMECH.2021.3115997, early access. (SCI, IF=5.303)
[19] F. Feng*, R. Yang, J. Meng*, Y. Xie, Z. Zhang, Y. Chai, and L. Mou. “Electrochemical Impedance Characteristics at Various Conditions for Commercial Solid-liquid Electrolyte Lithium-ion Batteries: Part 1. Experiment Investigation and Regression Analysis”. Energy, p. 123091, 2022. (SCI, IF=7.147)
[20] F. Feng*, R. Yang, J. Meng*, Y. Xie, Z. Zhang, Y. Chai, and L. Mou. “Electrochemical Impedance Characteristics at Various Conditions for Commercial Solid-liquid Electrolyte Lithium-ion Batteries: Part. 2. Modeling and Prediction,” Energy, vol. 243, p. 123091, 2022. (SCI, IF=7.147)
[21] H. Huang, J. Meng*, Y. Wang, F. Feng*, L. Cai, J. Peng, T. Liu. “A comprehensively optimized lithium-ion battery state-of-health estimator based on Local Coulomb Counting Curve,” Applied Energy, vol. 322, p.119469. (SCI, IF=9.746)
Co-authors：
[1] M. Lin, D. Wu, J. Meng, J. Wu, H. Wu, “A Multi-feature-based Multi-model Fusion Method for State of Health Estimation of Lithium-ion Batteries”, Journal of Power Sources, 2022, vol. 518, 230774. (SCI, IF=9.127)
[2] K. Liu, X. Tang, R. Teodorescu, F. Gao, J. Meng, “Future Ageing Trajectory Prediction for Lithium-ion Battery Considering the Knee Point Effect”, IEEE Transactions on Energy Conversion, 2022, vol. 37, no. 2, pp. 1282-1291. (IF=4.312)
[3] X. Huang, W. Liu, J. Meng, Y. Li, S. Jin, R. Teodorescu, D. Stroe, “Lifetime Extension of Lithium-ion Batteries with Low-Frequency Pulsed Current Charging”, IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, DOI: 10.1109/JESTPE.2021.3130424. (IF=4.472)
[4] X. Huang, W. Liu, A. Acharya, J. Meng, R. Teodorescu, D. Stroe, “Effect of Pulsed Current on Charging Performance of Lithium-ion Batteries”, IEEE Transactions on Industrial Electronics, 2022, vol. 69, no. 10, pp. 10144-10153. (IF=8.236)
[5] X. Sui, S. He, J. Meng, et al. “Fuzzy Entropy-based State of Health Estimation for Li-ion Batteries”, IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020, vol. 9, no. 4, pp. 5125-5137. (IF=4.472)
[6] 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. (IF=9.746)
[7] 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, vol. 41, 102974. (IF=6.583)
[8] J. Wu, L. Fang, J. Meng, M. Lin, and G. Dong, “Optimized Multi-source Fusion based State of Health Estimation for Lithium-ion Battery in Fast Charge Applications,” IEEE Transactions on Energy Conversion, 2022, vol. 37, no. 2, pp. 1489-1498. (IF=4.312)
[9] J. Li, K. Liu, Q. Zhou, J. Meng, Y. Ge, and H. Xu, “Electrothermal Dynamics-Conscious Many-Objective Modular Design for Power-Split Plug-in Hybrid Electric Vehicles,” IEEE/ASME Transactions on Mechatronics, 2022, DOI: 10.1109/TMECH.2022.3156535. (IF=5.303)
[10] M. Lin, C. Yan, J. Meng, W. Wang, and J. Wu, “Lithium-ion Batteries Health Prognosis via Differential Thermal Capacity with Simulated Annealing and Support Vector Regression,” Energy, pp. 123829, 2022. (IF=7.147)
[11] 肖迁, 穆云飞, 焦志鹏, 孟锦豪, 贾宏杰. 基于改进LightGBM的电动汽车电池剩余使用寿命在线预测[J/OL].电工技术学报:1-11[2022-05-08].
[12] 巫春玲, 胡雯博, 孟锦豪, 刘智轩, 程琰清. 基于最大相关熵扩展卡尔曼滤波算法的锂离子电池荷电状态估计[J].电工技术学报,2021,36(24):5165-5175.
[1] 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), pp. 1–6. IEEE, 2014.
[2] 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, pp. 001205-001210. IEEE, 2015.’
[3] 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), pp. 352-357. IEEE, 2017.
[4] 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.
[5] 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.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
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