The research focuses on fundamental theories and core technologies in the fields of vehicle dynamics theory, advanced intelligent safety control, and electromechanical coupling drive/brake control for new energy vehicles. Over the past 15 years, efforts have been dedicated to advancing the independent industrialization of core products for advanced automotive intelligent safety control systems, including ESC (ABS/TCS/ESC/EPBi), IBooster, L3-EPS, ADAS, AEB, Autonomous Driving (AD), AMT, and hybrid powertrain electromechanical coupling systems. The work aims to meaningfully contribute to achieving self-reliance in core technologies for the domestic automotive industry.

Vehicle System Dynamics and Intelligent Safety Control

Design of High-Efficiency Hybrid Powertrain Systems

Intelligent By-Wire Chassis and Chassis Domain Control

Self-Reliant Industrialization Technology for Automotive Electronic Control Systems

[1] Hua, C., Chen, J., Li, Y., &Li, L. (2018). Adaptive prescribed performance control of half-car active suspension system with unknown dead-zone input. Mechanical Systems & Signal Processing, 111, 135-148.

[2] Wang, X., Li, L.*, He, K., & Liu, C. (2017). Dual-loop self-learning fuzzy control for amt gear engagement: design and experiment. IEEE Transactions on Fuzzy Systems, 26(4), 1813-1822.

[3] Hua, C., Liu, G., Li, L., & Guan, X. (2018). Adaptive fuzzy prescribed performance control for nonlinear switched time-delay systems with unmodeled dynamics. IEEE Transactions on Fuzzy Systems, 26(4), 1934-1945.

[4] Wang, X.,Li, L.*, He, K., Liu, Y., & Liu, C. (2018). Position and force switching control for gear engagement of automated manual transmission gear-shift process. ASME, Journal of Dynamic Systems Measurement & Control, 140(8).

[5] Xie, S., Hu, X., Xin, Z., & Li, L.* (2018). Time-efficient stochastic model predictive energy management for a plug-in hybrid electric bus with adaptive reference state-of-charge advisory. IEEE Transactions on Vehicular Technology, 67(7), 5671-5682.

[6] Cheng, S., Li, L.*, & Chen, J. (2017). Fusion algorithm design based on adaptive sckf and integral correction for side-slip angle observation. IEEE Transactions on Industrial Electronics, 65(7), 5754-5763.

[7] Liu, B., Li, L.*, Wang, X., & Cheng, S. (2018). Hybrid electric vehicle downshifting strategy based on stochastic dynamic programming during regenerative braking process. IEEE Transactions on Vehicular Technology, 67(6), 4716-4727.

[8] Xiqun Chen, Shuaichao Zhang, LiLi, LiangLi. Adaptive Rolling Smoothing With Heterogeneous Data for Traffic State Estimation and Prediction. IEEE Transactions on Intelligent Transportation Systems: 2018,( Early Access ), Pages:1-12.

[9] Zhen cheng, Liang Li, Xiaosong Hu, Bingjie Yan. Temporal-Difference Learning Based Stochastic Energy Management for Plug-in Hybrid Electric Buses. IEEE Transactions on Intelligent Transportation Systems, 10.1109/TITS.2018.2869731.

[10]Congzhi Liu, Liang Li*, Xun Zhao, Et al. Cooperative Control of the Clutch and Hydraulic Control Unit, IEEE Transactions on Industrial Electronics, DOI:10.1109/TIE.2018.2874615, 2018.9.

[11] Wu, Jian; Wang, Xiangyu; Li, Liang*. Hierarchical control strategy with battery aging consideration for hybrid electric vehicle regenerative braking control, ENERGY, Vol. 145, p:301-312, 2018

[12] Xiqun Chen, Shuaichao Zhang, Li Li, Liang Li. Adaptive Rolling Smoothing With Heterogeneous Data for Traffic State Estimation and Prediction, IEEE Transactions on Intelligent Transportation Systems ( Early Access ), 2018. DOI: 10.1109/TITS.2018.2847024

[13] Yonggang Liu, Xiao Wang, Liang Li, Shuo Cheng, Zheng Chen. A Novel Lane Change Decision-Making Model of Autonomous Vehicle Based on Support Vector Machine. IEEE Access, 2019 , ( Early Access ) DOI: 10.1109/ACCESS.2019.2900416

[14] Yong Sun, Shuo Cheng, Cong-Zhi Liu, Liang Li, Jian Wu, Da Guo. A H ∞ PI ε D-Based Observer Designed by LMI for Some Special System, IEEE Access, 2019. P. 5502 – 5507.

[15]Xun Zhao, Liang Li, Xiangyu Wang, Mingming Mei, Congzhi Liu, Jian Song. Braking force decoupling control without pressure sensor for a novel series regenerative brake system. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, doi.org/10.1177/0954407018785740. First Published 25 Jul 2018.

[16]Guest Editorial Focused Section on Mechatronics in Cyber-Physical Systems, IEEE/ASME Transactions on Mechatronics, Vol.23, Issue 6, DOI: 10.1109/TMECH.2018.2853596.

[18] Shuo Cheng, Mingm Mei, Xu Ran, Liang Li*，Xun Zhao. Adaptive Unified Monitoring System Design for Tire-Road Information, ASME Transaction, Journal of Dynamic Systems, Measurement and Control, Accept.