Coordinated control of active front steering and direct yaw moment control for in-wheel-motor-drive electric vehicles

Author(s):  
Pengyu Guo ◽  
Lei Zhang ◽  
Zhenpo Wang
2018 ◽  
Vol 41 (9) ◽  
pp. 2428-2440 ◽  
Author(s):  
Jiaxu Zhang ◽  
Jing Li

This paper presents an integrated vehicle chassis control (IVCC) strategy to improve vehicle handling and stability by coordinating active front steering (AFS) and direct yaw moment control (DYC) in a hierarchical way. In high-level control, the corrective yaw moment is calculated by the fast terminal sliding mode control (FTSMC) method, which may improve the transient response of the system, and a non-linear disturbance observer (NDO) is used to estimate and compensate for the model uncertainty and external disturbance to suppress the chattering of FTSMC. In low-level control, the null-space-based control reallocation method and inverse tyre model are utilized to transform the corrective yaw moment to the desired longitudinal slips and the steer angle increment of front wheels by considering the constraints of actuators and friction ellipse of each wheel. Finally, the performance of the proposed control strategy is verified through simulations of various manoeuvres based on vehicle dynamic software CarSim.


2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Wanke Cao ◽  
Zhiyin Liu ◽  
Yuhua Chang ◽  
Antoni Szumanowski

This paper investigates the robust direct yaw-moment control (DYC) through parameter-dependent fuzzy sliding mode control (SMC) approach for all-wheel-independent-drive electric vehicles (AWID-EVs) subject to network-induced delays. AWID-EVs have obvious advantages in terms of DYC over the traditional centralized-drive vehicles. However it is one of the most principal issues for AWID-EVs to ensure the robustness of DYC. Furthermore, the network-induced delays would also reduce control performance of DYC and even deteriorate the EV system. To ensure robustness of DYC and deal with network-induced delays, a parameter-dependent fuzzy sliding mode control (FSMC) method based on the real-time information of vehicle states and delays is proposed in this paper. The results of cosimulations with Simulink® and CarSim® demonstrate the effectiveness of the proposed controller. Moreover, the results of comparison with a conventional FSMC controller illustrate the strength of explicitly dealing with network-induced delays.


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