谷歌学术出版物主页：https://scholar.google.com/citations?user=XEqm9GIAAAAJ&hl=en&oi=ao

代表性论文

1）模型与状态估计：

[1]       H. Zhang, X. Hu, Z. Hu, and S. Moura, “Sustainable plug-in electric vehicle integration into power systems,” Nature Reviews Electrical Engineering, 1: 35–52, 2024.

[2]       X. Gu, H. Bai, X. Cui, J. Zhu, W. Zhuang, X. Hu, and Z. Song, “Challenges and opportunities for second-life batteries: Key technologies and economy”, Renewable and Sustainable Energy Reviews, 192: 114191,2024.  (IF: 15.9)

[3]       Y. Zheng, Y. Che, X. Hu, X. Sui, D. Stroe, and R. Teodorescu, “Thermal state monitoring of lithium-ion batteries: Progress, challenges, and opportunities”, Progress in Energy and Combustion Science, 100: 101120, 2024.  (IF=29.5)

[4]       Y. Zheng, Y. Che, X. Hu, X. Sui, and R. Teodorescu, “Sensorless temperature monitoring of lithium-ion batteries by integrating physics with machine learning,” IEEE Transactions on Transportation Electrification, 2023.  (IF=7.0)

[5]       W. Liu, A. Khalatbarisoltani, C. Hou, and X. Hu, “A New Safety-Oriented Multi-State Joint Estimation Framework for High-Power Electric Flying Car Batteries,” SAE Technical Paper, 2023.

[6]       Y. Che, Y. Zheng, Y. Wu, X. Lin, J. Li, X. Hu, and R. Teodorescu, “Battery States Monitoring for Electric Vehicles Based on Transferred Multi-Task Learning,” IEEE Transactions on Vehicular Technology, 72(8): 10037–10047, 2023.   (IF= 6.8)

[7]       徐乐, 邓忠伟, 谢翌, 胡晓松. 锂离子电池电化学-热耦合模型对比研究. 机械工程学报,  58(22): 304-320, 2023.

[8]       W. Liu, X. Hu, X. Lin, X. Yang, Z. Song, A. M. Foley, and J. Couture, “Toward high-accuracy and high-efficiency battery electrothermal modeling: A general approach to tackling modeling errors,” Etransportation, 14: 100195, 2022.  (IF=11.9)

[9]       Y. Xie, W. Li, X. Hu, M. Tran, S. Panchal M. Fowler Y. Zhang and K. Liu, “Coestimation of SOC and three-dimensional SOT for lithium-ion batteries based on distributed spatial–temporal online correction,” IEEE Transactions on Industrial Electronics, 70(6): 5937-5948, 2022.  (IF= 7.7, Highly Cited paper)

[10]   L. Xu, X. Lin, Y. Xie, and X. Hu, “Enabling high-fidelity electrochemical P2D modeling of lithium-ion batteries via fast and non-destructive parameter identification,” Energy Storage Materials, 45: 952-968, 2022.  (IF=20.4)

[11]   Y. Xie, X. Wang, X. Hu, W. Li, Y. Zhang, and X. Lin, “An enhanced electro-thermal model for EV battery packs considering current distribution in parallel branches,” IEEE Transactions on Power Electronics, 37(1): 1027-1043, 2021.  (IF: 6.7)

[12]   Z. Deng, X. Hu, X. Lin, L. Xu, J. Li, and W. Guo, “A reduced-order electrochemical model for all-solid-state batteries,” IEEE Transactions on Transportation Electrification, 7(2): 464-473, 2020.   (IF: 7.0)

[13]   X. Hu, W. Liu, X. Lin Y. Xie, A. M. Foley, and L. Hu, “A control-oriented electrothermal model for pouch-type electric vehicle batteries,” IEEE Transactions on Power Electronics, 36(5): 5530-5544,2020.   (IF: 6.7)

[14]   L. Hu, X. Hu, Y. Che, F. Feng, X. Lin, and Z. Zhang, “Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering,” Applied Energy, 262: 114569, 2020.   (IF: 11.2)

[15]   X. Hu, H. Jiang, F. Feng, and B. Liu, “An enhanced multi-state estimation hierarchy for advanced lithium-ion battery management,” Applied Energy, 257: 114019, 2020.  (IF: 1.65)

[16]   Y. Xie, W. Li, X. Hu, C. Zou, F. Feng, and X. Tang, “Novel mesoscale electrothermal modeling for lithium-ion batteries,” IEEE Transactions on Power Electronics, 35(3): 2595-2614, 2019.   (IF: 6.7)

[17]   X. Hu, W. Liu, X. Lin, and Y. Xie, “A comparative study of control-oriented thermal models for cylindrical Li-ion batteries,” IEEE Transactions on Transportation Electrification, 5(4): 1237-1253, 2019.   (IF: 7.0)

[18]   X. Hu, F. Feng, K. Liu, L. Zhang, J. Xie and B. Liu, “State estimation for advanced battery management: Key challenges and future trends,” Renewable and Sustainable Energy Reviews, 114: 109334, 2019.  (IF: 15.9, Highly Cited Paper)

 

2）故障诊断：

[1]       X. You, Z. Deng, Y. Yang, X. Lin and X. Hu, “Fault Diagnosis of Electric City Bus High-voltage Load System Based on Multi-Domain Sparse Representation,” IEEE Transactions on Transportation Electrification, 1-1,2023.  (IF=7.0)

[2]       K. Zhang, L. Jiang, Z. Deng, Y. Xie, J. Couture, X. Lin, J. Zhou, and X. Hu, “An Early Soft Internal Short-Circuit Fault Diagnosis Method for Lithium-Ion Battery Packs in Electric Vehicles,” IEEE/ASME Transactions on Mechatronics, 28(2): 644-655, 2023.  (IF=6.4)

[3]       L. Jiang, Z. Deng, X. Tang, L. Hu, X. Lin, and X. Hu, "Data-driven fault diagnosis and thermal runaway warning for battery packs using real-world vehicle data," Energy, 234: 121266, 2021.  (IF=9.0)

[4]       Ojo, H. Lang, Y. Kim, X. Hu, B. Mu and X. Lin, "A Neural Network Based Method for Thermal Fault Detection in Lithium-Ion Batteries," IEEE Transactions on Industrial Electronics, 68(5): 4068-4078, 2021.   (IF=7.7)

[5]       X. Hu, K. Zhang, K. Liu, X. Lin, S. Dey and S. Onori, "Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures," IEEE Industrial Electronics Magazine, 14(3): 65-91, 2020.   (IF=6.3, Highly Cited paper)

[6]       F. Feng, X. Hu, L. Hu, F. Hu, Y. Li and L. Zhang, “Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs” Renewable and Sustainable Energy Reviews，112: 102-113, 2019.   (IF: 15.9, Highly Cited Paper)

[7]       W. Gao, Y. Zheng, M. Ouyang, J. Li, X. Lai and X. Hu, "Micro-Short-Circuit Diagnosis for Series-Connected Lithium-Ion Battery Packs Using Mean-Difference Model," IEEE Transactions on Industrial Electronics, 66(3): 2132-2142, 2019.   (IF:7.7, Highly Cited Paper)

 

3）健康与寿命：

[1]       Y. Che, Y Zheng, S. Onori, X. Hu, and R. Teodorescu. “Increasing generalization capability of battery health estimation using continual learning,” Cell Reports Physical Science 4, no. 12 ,2023.  (IF=8.9)

[2]       Y. Che, X. Hu, X. Lin, J. Guo, and R. Teodorescu. “Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects,” Energy & Environmental Science ,2023.  (IF=32.5, Highly Cited paper)

[3]       Z. Deng, L. Xu, H. Liu, X. Hu, Z. Duan, and Y. Xu. “Prognostics of battery capacity based on charging data and data-driven methods for on-road vehicles,” Applied Energy 339: 120954,2023.  (IF=11.2)

[4]       Y. Che, Z. Deng, P. Li, X. Tang, K. Khosravinia, X. Lin, and X. Hu. “State of health prognostics for series battery packs: A universal deep learning method,” Energy 238: 121857,2022.  (IF=9.0)

[5]       Z. Deng, X. Lin, J. Cai, and X. Hu. “Battery health estimation with degradation pattern recognition and transfer learning,” Journal of Power Sources 525: 231027,2022.  (IF=9.2, Highly Cited paper)

[6]       Z. Deng, X. Hu, Y. Xie, L. Xu, P. Li, X. Lin, and X. Bian. “Battery health evaluation using a short random segment of constant current charging,” Iscience 25, no. 5 ,2022.  (IF=5.8)

[7]       Y. Che, D. Stroe, X. Hu, and R. Teodorescu. “Semi-supervised self-learning-based lifetime prediction for batteries,” IEEE Transactions on Industrial Informatics ,2022.  (IF=12.3, Highly Cited paper)

[8]       L. Xu, Z. Deng, Y. Xie, X. Lin, and X. Hu. “A novel hybrid physics-based and data-driven approach for degradation trajectory prediction in Li-ion batteries,” IEEE Transactions on Transportation Electrification,2022.  (IF=7.0)

[9]       Y. Che, Z. Deng, X. Lin, L. Hu, and X. Hu, “Predictive battery health management with transfer learning and online model correction,” IEEE Transactions on Vehicular Technology, 70(2): 1269-1277,2021.  (IF=6.239, Highly Cited paper)

[10]   X. Hu, Y. Che, X. Lin, and S. Onori, “Battery health prediction using fusion-based feature selection and machine learning,” IEEE Transactions on Transportation Electrification, 7(2): 382-398, 2020.  (IF=6.519, Highly Cited paper)

[11]   Z. Deng, X. Hu, X. Lin, L. Xu, Che. Y, L. Hu, “General discharge voltage information enabled health evaluation for lithium-ion batteries,” IEEE/ASME Transactions on Mechatronics, 26(3): 1295-1306, 2020.  (IF=5.303, Highly Cited paper)

[12]   Y. Che, A. Foley, M. El-Gindy, X. Lin, X. Hu, and M. Pecht. “Joint estimation of inconsistency and state of health for series battery packs,” Automotive Innovation, 4: 103-116, 2021.

[13]   X. Hu, L. Xu, X. Lin, and M. Pecht. “Battery lifetime prognostics,” Joule, 4(2): 310-346, 2020.  (IF=41.248, Highly Cited paper)

[14]   X. Hu, Y. Che, X. Lin, and Z. Deng. “Health prognosis for electric vehicle battery packs: A data-driven approach,” IEEE/ASME transactions on mechatronics, 25(6): 2622-2632, 2020.  (IF=5.303)

[15]   Liu K, Hu X, Wei Z, Y. Li, and Y. Jiang, “Modified Gaussian process regression models for cyclic capacity prediction of lithium-ion batteries,” IEEE Transactions on Transportation Electrification, 5(4): 1225-1236, 2019.  (IF:8.1, Highly Cited Paper)

 

4）能量管理：

[1]       N. Zhao, F. Zhang, Y. Yang, S. Coskun, X. Lin and X. Hu, “Dynamic Traffic Prediction-Based Energy Management of Connected Plug-In Hybrid Electric Vehicles with Long Short-Term State of Charge Planning,” IEEE Transactions on Vehicular Technology, 72(5): 5833-5846, 2023.   (IF = 6.8)

[2]       A. Khalatbarisoltani, L. Boulon and X. Hu, “Integrating Model Predictive Control with Federated Reinforcement Learning for Decentralized Energy Management of Fuel Cell Vehicles,” IEEE Transactions on Intelligent Transportation Systems, 24(12): 13639-13653, 2023.   (IF = 8.5)

[3]       Y. Li, F. Wang, X. Tang, X. Lin, C. Liu and X. Hu, “Real-Time Multiobjective Energy Management for Electrified Powertrains: A Convex Optimization-Driven Predictive Approach,” in IEEE Transactions on Transportation Electrification, 8(3): 3139-3150, 2022.   (IF = 7.0)

[4]       J. Han, H. Shu, X. Tang, X. Lin, C. Liu, X. Hu, “Predictive energy management for plug-in hybrid electric vehicles considering electric motor thermal dynamics,” Energy Conversion and Management, 251:115022, 2022.   (IF = 10.4)

[5]       F. Zhang, X. Hu, T. Liu, K. Xu, Z. Duan and H. Pang, “Computationally Efficient Energy Management for Hybrid Electric Vehicles Using Model Predictive Control and Vehicle-to-Vehicle Communication,” IEEE Transactions on Vehicular Technology, 70(1): 237-250, 2021.   (IF = 6.8)

[6]       X. Hu, C. Zou, X. Tang, T. Liu and L. Hu, "Cost-Optimal Energy Management of Hybrid Electric Vehicles Using Fuel Cell/Battery Health-Aware Predictive Control," IEEE Transactions on Power Electronics, 35(1):382-392, 2020.   (IF = 6.7, Highly Cited paper)

[7]       S. Xie, X. Hu, Q. Zhang, X. Lin, B. Mu, and H. Ji, “Aging-aware co-optimization of battery size, depth of discharge, and energy management for plug-in hybrid electric vehicles,” Journal of Power Sources, 450:227638,2020.   (IF = 9.2)

[8]       B. Xu, X. Hu, X. Tang, X. Lin, D. Rathod, and Z. Filipi, “Ensemble Reinforcement Learning-Based Supervisory Control of Hybrid Electric Vehicle for Fuel Economy Improvement,” IEEE Transactions on Transportation Electrification, 6(2): 717-727, 2020.   (IF = 7)

[9]       S. Xie, X. Hu, Z. Xin, and J. Brighton, “Pontryagin’s Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus,” Applied Energy, 236: 893-905, 2019.   (IF = 11.2, Highly Cited Paper, High-Impact Paper Award)

[10]   F. Zhang, X. Hu, R. Langari, and D. Cao, “Energy management strategies of connected HEVs and PHEVs: Recent progress and outlook,” Progress in Energy and Combustion Science, 73:235-256, 2019.   (IF = 29.5, Highly Cited Paper)

 

5）经济性驾驶：

[1]       W. Yu, C. Zhao, H. Wang, J. Liu, X. Ma, Y. Yang, J. Li, W. Wang, X. Hu, and D. Zhao. “Online legal driving behavior monitoring for self-driving vehicles,” Nature Communications, 15:408,2024.   (IF =16.6)

[2]       H. Long, A. Khalatbarisoltani, Y. Yang and X. Hu, “Hierarchical Control Strategies for Connected Heavy-Duty Modular Fuel Cell Vehicles via Decentralized Convex Optimization,” IEEE Transactions on Vehicular Technology, 73(1): 333-347, 2024.  (IF = 6.239)

[3]       J. Peng, F. Zhang, S. Coskun, X. Hu, Y. Yang, R. Langari, and J. He, “Hierarchical Optimization of Speed Planning and Energy Management for Connected Hybrid Electric Vehicles Under Multi-Lane and Signal Lights Aware Scenarios,” IEEE Transactions on Intelligent Transportation Systems, 24(12): 14174-14188, 2023.   (IF = 8.5)

[4]       Y. Li, X. Lin and X. Hu, “Traffic information-based eco-driving for plug-in electric vehicles: A hierarchical control strategy,” 2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI), Nanjing, China, 1-3, 2022.

[5]       Y. Li, F. Wang, X. Tang, X. Hu, and X. Lin, “Convex optimization-based predictive and bi-level energy management for plug-in hybrid electric vehicles,” Energy, 257: 124672, 2022.   (IF = 8.9)

[6]       Y. Wu, Z. Huang, H. Hofmann, Y. Liu, J. Huang, X. Hu, J. Peng, and Z. Song, “Hierarchical predictive control for electric vehicles with hybrid energy storage system under vehicle-following scenarios,” Energy, 251: 123774,2022.   (IF = 8.9)

[7]       X. Tang, J. Chen, K. Yang, M. Toyoda, T. Liu and X. Hu, “Visual Detection and Deep Reinforcement Learning-Based Car Following and Energy Management for Hybrid Electric Vehicles,” IEEE Transactions on Transportation Electrification, 8(2):2501-2515, 2022.   (IF = 7)

[8]       X. Tang, Z. Duan, X. Hu, H. Pu, D. Cao and X. Lin, “Improving Ride Comfort and Fuel Economy of Connected Hybrid Electric Vehicles Based on Traffic Signals and Real Road Information,” IEEE Transactions on Vehicular Technology, 70(4): 3101-3112, 2021.  (IF = 6.8)

[9]       S. Xie, X. Hu, T. Liu, S. Qi, K. Lang, and H. Li, “Predictive vehicle-following power management for plug-in hybrid electric vehicles,” Energy, 166:701-714, 2019.   (IF = 8.9)

 

代表性专利

[1]      Tang X., Gan J., Yang W., Hu X.*, et al. Hybrid electric vehicle control method based on multi-agent deep reinforcement learning, China Invention Patent, No. 202211434764.2, 2023   (granted)

[2]      Tang X., Deng L., Gan J., Zhu H., Hu X.*, et al. Fuel cell automobile learning type collaborative energy management method considering air conditioning system, China Invention Patent, No. 202211385462.0, 2023   (granted)

[3]      Tang X., Yang K., Li S., Wang F., Shen Z., Deng Z., Hu X.*, et al. Method for realizing automatic driving automobile behavior decision, China Invention Patent, No. 202210528980.7, 2022   (granted)

[4]      Hu X.*, Liu W., Deng Z., et al. Battery pack multi-state joint estimation method based on cloud edge collaboration, China Invention Patent, No. 202111333506.0, 2022  (granted)

[5]      Hu X.*, Liu W., Xie Y., et al. Square lithium battery electrothermal coupling modeling error source analysis method, China Invention Patent, No. 202111044985.4, 2021   (granted)

[6]      Tang X., Chen J., Wang F., Hu X.*, et al. Hybrid power system control method based on pavement recognition and deep reinforcement learning, China Invention Patent, No.202110766400.3, 2021   (granted)

[7]      Hu X.*, You X., Li J., et al. Energy optimization device and method for power battery system, China Invention Patent, No. 202110550678.7, 2021   (granted)

[8]      Tang X., Zhou H., Wang F., Hu X.*, et al. Fuel cell vehicle energy management method based on TD3 algorithm, China Invention Patent, No.202110506276.7, 2021   (granted)

[9]      Tang X., Jin S., Wang F., Deng Z., Hu X.*, et al. Deep reinforcement learning automatic driving automobile control method based on supervision signal guidance, China Invention Patent, No.202110475638.0, 2021   (granted)

[10]   Hu X.*, You X., Li J., et al. Battery thermal management device and control method, China Invention Patent, No. 202110203413.X, 2021   (granted)

[11]   Hu X.*, Che Y., Li J., et al. Battery pack residual life prediction method based on migration deep learning, China Invention Patent, No. 202110048627.4, 2021   (granted)

[12]   Tang X., Zhang J., Qin Y., Deng Z., Hu X.*, et al. A parametric optimization method based on Pareto optimality under multi-objective conditions for two-mode configurations, China Invention Patent, No.202110019579.6, 2021   (granted)

[13]   Hu X.*, You X., Li J., et al. Electric vehicle safety protection device and method, China Invention Patent, No. 202011581850.7, 2021   (granted)

[14]   Hu X.*, You X., Deng Z., et al. Battery system power limit value estimation method based on multi-factor fusion, China Invention Patent, No. 202011583075.9, 2021   (granted)

[15]   Tang X., Zhou H., Deng Z., Hu X.*, et al. Fuel cell vehicle energy management method based on deep reinforcement learning algorithm, China Invention Patent, No. 202011212191.X, 2021   (granted)

[16]   Hu X.*, Che Y., Deng Z., et al. A battery health prediction method for predictive maintenance, China Invention Patent, No. 202011141793.0, 2020   (granted)

[17]   Tang X., Zhang Z., Chen J., Yang X., Hu X.*, et al. An unmanned vehicle vision enhancement device and method in extreme environment, China Invention Patent, No. 2020106223422, 2020   (granted)

[18]   Tang X., Chen J., Pu H., Zhang Z., Yang X., Hu X.*,et al. An HEV energy management method based on deep reinforcement learning A3C algorithm, China Invention Patent, No. 2020106579174, 2020   (granted)

[19]   Xie Y., Wang C., Hu X.*,et al. Electric vehicle battery thermal management method based on model predictive control, China Invention Patent, No. 202010062895.7, 2020   (granted)

[20]   Tang X., Chen J., Yang K., Deng Z., Hu X.*, et al. A deep reinforcement learning-based energy management method for HEVs in a car-following environment, China Invention Patent, No. 2020107779680, 2020   (granted)

[21]   Tang X., Jia T., Yang X., Hu X.*, et al. PMP-based plug-in hybrid electric vehicle model prediction control energy management method, China Invention Patent, No. 202011475175X, 2020    (granted)

[22]   Hu X.*, Zhang X., Tang X., et al. Multi-target energy management method in HEV self-adaptive cruise based on MPC, China Invention Patent, No. 202011475175X, 2020    (granted)

[23]   Tang X., Yang K., Yang X., Ji Q., Hu X.*, et al. Traction type trailer trajectory tracking method based on robust H infinite control, China Invention Patent, No. 2020107779680, 2020   (granted)

[24]   Tang X., Chen J., Deng Z., Hu X.*, et al. A hierarchical control method for intelligent hybrid vehicles based on visual perception and deep reinforcement learning, China Invention Patent, No. 202011475175X, 2020    (granted)

[25]   Tang X., Yang X., Yang K., Hu X.*, et al. Pull-type trailer trajectory tracking method based on model predictive control, China Invention Patent, No. 201911370775.7, 2020    (granted)

[26]   Feng F., Hu X.*, Hu F., et al. A diagnostic method for inconsistency of power battery pack parameters, China Invention Patent, No. 2019103730013, 2019   (granted)

[27]   Feng F., Hu X.*, Yang X., et al. A fusion-based algorithm for predicting the remaining life of lithium-ion batteries, China Invention Patent, No. 2019105732598, 2019   (granted)

[28]   Hu X.*, Zhang F., Tang X., et al. Hierarchical Control Method of HEV Energy Management Considering Lane Change Behavior in Connected Environment, China Invention Patent, No. 202010898329.X, 2020   (granted)

[29]   Hu X.*, Li Y., Han J., et al. Convex Optimization-based Energy Management Method for Hybrid Electric Vehicle Considering Motor Thermal State, China Invention Patent, No. 202010930943.X, 2020   (granted)

[30]   Hu X.*, Deng Z., Wang P., et al. General Discharge Voltage Information Enabled Health Evaluation for Lithium-Ion Batteries, China Invention Patent, 2020108597035, 2020   (granted)

[31]   Hu X.*, Liu J., Deng Z., et al. A balanced method for battery packs considering battery charge and discharge condition based on multi-variable fusion, China Invention Patent, 202010719239X, 2020   (granted)

[32]   Hu X.*, Hu F., Feng F., et al. A transmission method for on-board data of new energy vehicles based on adaptive time interval, China Invention Patent, No. 201911320859X, 2019 (granted)

[33]   Hu X.*, Liu W., Xie Y., et al. A joint estimation method for SOC and SOT of square lithium batteries based on multiple time scales, China Invention Patent, No. 2019112440664, 2019  (granted)

[34]   Hu X.*, Liu W., Xie Y., et al. A control - oriented thermal modeling method for lithium batteries, China Invention Patent, No. 2019112440626, 2019   (granted)

[35]   Feng F., Hu X.*, Li J., et al. Lithium-ion power battery pack full-life-cycle balance control method, China Invention Patent, No. 201910523087.3, 2019   (granted)

[36]   Hu X.*, Deng X., Feng F., et al. State of Charge Estimation of Lithium-ion Battery Based on Improved Fractional order model, China Invention Patent, No. 201910372379.1, 2019  (granted)

[37]   Hu X.*, Hou C., Xie S., et al. Power Mode Determination System for Series Hybrid Electric Vehicle, China Invention Patent, No. 201910563298.X, 2019   (granted)

[38]   Hu X.*, Li Y., Feng F., et al. Dual Motor Configuration of Pure Electric Vehicle and Torque Optimization Method Based on Convex Optimization Algorithm, China Invention Patent, No. 201810002393.8, 2018   (granted)

[39]   Hu X.*, Chen K., Feng F., et al. Hybrid Power Fleet Collaborative Energy Management Method Based on Model Predictive Control, China Invention Patent, No. 201810123988.9, 2018 (granted)

[40]   Hu X.*, Liu W., Feng F., et al. A Joint Estimation Method of SOC and SOT Based on Battery Electro-thermal Coupling Model, China Invention Patent, No. 201810124009.1, 2018   (granted)

[41]   Hu X.*, Li Y., Feng F., et al. Three-motor Transmission Structure for Pure Electric Vehicle and Its Torque Distribution Optimization Algorithm, China Invention Patent, No. 201810283989.X, 2018   (granted)

[42]   Hu X.*, Li Y., Feng F., et al. Adaptive Cruise Control Method of Pure Electric Vehicle Based on MPC and Convex Optimization Algorithm, China Invention Patent, No. 201810313067.9, 2018   (granted)

[43]   Hu X.*, Feng F., Jiang H., et al. A SOC/SOH/SOP Joint Estimation Method for Power Battery Based on Equivalent Circuit Model, China Invention Patent, No. 201810313074.9, 2018   (granted)

[44]   Hu X.*, Feng F., Xu J., et al. Observer-based Fault Diagnosis Method for Sensors of Lithium-ion Battery in Electric Vehicles, China Invention Patent, No. 201810967540.5, 2018   (granted)

[45]   Yang Y., Zhang J., Hu X.*, et al. Single-planetary-line multi-mode hybrid power drive system, China Invention Patent, No. 201711378367.7, 2018   (granted)

[46]   Hu X.*, Feng F., Zheng Y., et al. A Data Driven Method for Li-plating Diagnosis of Lithium-ion Battery in Electric Vehicles, China Invention Patent, No. 201811319070.8, 2018  (granted)

[47]   Hu X.*, Zhang S., Feng F., et al. A Shifting Strategy for AMT of Hybrid Bus Based on Dynamic Programming, China Invention Patent, No. 201811487895.0, 2018   (granted)

[48]   Yang Y., Zhang J., Hu X.*, et al. Multi-gear dynamic coupling drive system, China Invention Patent, No. 201711377529.5, 2018  (granted)