Title
An Adaptive Backstepping Sliding Mode Controller to Improve Vehicle Maneuverability and Stability via Torque Vectoring Control
Abstract
To improve the maneuverability and stability of a vehicle and fully leverage the advantages of torque vectoring technology in vehicle dynamics control, a finite-time yaw rate and sideslip angle tracking controller is proposed by combining a second-order sliding mode (SOSM) controller with the backstepping method in this paper. However, existing research indicates that first-order sliding mode (FOSM) control suffers from the chattering problem, while the traditional SOSM controller requires knowing the bound of the uncertain term in advance to obtain the switching gain, which is difficult in practice. To address these problems, this paper proposes an adaptive second-order sliding mode (ASOSM) controller based on the backstepping method by adding the high-frequency switching term to the first derivative of the sliding mode variable, which implies that the actual control can be acquired after an integration process. The switching gain in the ASOSM controller is obtained by an adaptive algorithm without knowing any information of the uncertainty. The proposed algorithm is compared with FOSM and SOSM in different scenarios to demonstrate its applicability and robustness. Simulation results show that the bandwidth of the vehicle transient response can be improved by 21%. In addition, ASOSM and SOSM controllers are insensitive to vehicle mass and tire type, implying their robustness to such disturbances. Furthermore, ASOSM requires less control action because of the adaptive law when it performs similarly with SOSM and FOSM.
Year
DOI
Venue
2020
10.1109/TVT.2019.2950219
IEEE Transactions on Vehicular Technology
Keywords
DocType
Volume
Vehicle maneuverability and stability,torque vectoring control,sliding mode control,electric vehicle
Journal
69
Issue
ISSN
Citations 
3
0018-9545
1
PageRank 
References 
Authors
0.35
0
7
Name
Order
Citations
PageRank
Lin Zhang110451.47
haitao ding2184.45
Jianpeng Shi310.35
Yanjun Huang47910.54
Hong Chen528056.04
Konghui Guo6123.78
Qin Li710.35