TY - JOUR
T1 - Chassis Coordinated Control of Corner Module Architecture Intelligent Electric Vehicles for Escaping from Pothole on Low-Adhesion Roads
AU - Liu, Shuaishuai
AU - Zhang, Lipeng
AU - Wang, Jiantao
AU - Zhang, Junda
AU - Chen, Minghan
AU - Yang, Chao
N1 - Publisher Copyright:
© China Society of Automotive Engineers (China SAE) 2025.
PY - 2025
Y1 - 2025
N2 - A study was conducted in the domain of emergency rescue operations to tackle a challenge encountered by corner module architecture intelligent electric vehicles (C-Vs). Specifically, the study addressed the issue of the two front wheels getting stuck in potholes on low-adhesion roads. To overcome this obstacle, a chassis coordinated control method was introduced. Initially, a vehicle dynamic model suitable for uneven terrains was established. This model represented the vertical motion of the tire as a rigid ring and rim model. The full vehicle model accounted for suspension geometry, center of gravity (CG) transfer, and bumper blocks. Subsequently, a chassis coordinated control method was formulated, encompassing an active suspension system (ASS), traction control system (TCS), and yaw motion control system. Controllers for ASS to navigate out of potholes were designed. The relationship between the maximum driving force and posture was delineated, and the optimal suspension deflection (SD) was calculated. Building upon the designed optimal slip rate identification method, a TCS based on dynamic sliding mode control (DSMC) was developed. As both the ASS and TCS could induce yaw instability, and considering the heightened challenges posed by variations in speed and tire cornering stiffness on yaw motion control, Takagi–Sugeno (T-S) technology was employed to fuzzify both aspects. A robust SMC (RSMC)-based yaw motion control was devised, achieving coordinated control among the three systems. Finally, the results of the hardware-in-the-loop (HIL) illustrated that the coordinated control strategy enables C-Vs to escape from conditions with an adhesion coefficient of 0.3 and a pothole depth of 250 mm.
AB - A study was conducted in the domain of emergency rescue operations to tackle a challenge encountered by corner module architecture intelligent electric vehicles (C-Vs). Specifically, the study addressed the issue of the two front wheels getting stuck in potholes on low-adhesion roads. To overcome this obstacle, a chassis coordinated control method was introduced. Initially, a vehicle dynamic model suitable for uneven terrains was established. This model represented the vertical motion of the tire as a rigid ring and rim model. The full vehicle model accounted for suspension geometry, center of gravity (CG) transfer, and bumper blocks. Subsequently, a chassis coordinated control method was formulated, encompassing an active suspension system (ASS), traction control system (TCS), and yaw motion control system. Controllers for ASS to navigate out of potholes were designed. The relationship between the maximum driving force and posture was delineated, and the optimal suspension deflection (SD) was calculated. Building upon the designed optimal slip rate identification method, a TCS based on dynamic sliding mode control (DSMC) was developed. As both the ASS and TCS could induce yaw instability, and considering the heightened challenges posed by variations in speed and tire cornering stiffness on yaw motion control, Takagi–Sugeno (T-S) technology was employed to fuzzify both aspects. A robust SMC (RSMC)-based yaw motion control was devised, achieving coordinated control among the three systems. Finally, the results of the hardware-in-the-loop (HIL) illustrated that the coordinated control strategy enables C-Vs to escape from conditions with an adhesion coefficient of 0.3 and a pothole depth of 250 mm.
KW - Chassis coordinated control
KW - Corner module architecture
KW - Intelligent electric vehicles
KW - Low-adhesion roads
KW - Potholed roads
UR - https://www.scopus.com/pages/publications/105016866191
U2 - 10.1007/s42154-024-00331-x
DO - 10.1007/s42154-024-00331-x
M3 - Article
AN - SCOPUS:105016866191
SN - 2096-4250
JO - Automotive Innovation
JF - Automotive Innovation
ER -