With the aggravation of the energy crisis and environmental problems, the new energy electric vehicle industry has ushered in vigorous development. However, with the continuous increase in car ownership, traffic accidents and other issues have gradually attracted widespread attention. Some existing stability coordination control systems often have problems, such as single stability judgment method and strong coupling between different subsystems. Therefore, based on previous research, it is necessary to further optimize the method of judging the vehicle’s stability state, establish clear coordination rules, and reasonably solve the coupling problem between subsystems. This is of great significance for promoting the further development of the electric vehicle industry. Due to four-wheel-distributed driving and four-wheel-distributed steering electric vehicles having the characteristics of integrated driving, flexible steering, and easy fault-tolerant control, it has unique advantages in improving vehicle stability and is a good carrier for designing and constructing the stability coordination control system. In this paper, four-wheel-distributed driving and four-wheel-distributed steering (4WD-4WS) electric vehicles are taken as the research object, and a coordinated control strategy of four-wheel steering and four-wheel drive is proposed. Firstly, in order to realize the accurate judgment of vehicle stability, based on the vehicle two-degree-of-freedom two-track model and magic tire model, this paper uses the phase plane law to divide the phase plane stability region of the vehicle and introduces the stability quantification index PPS-region for the evaluation of vehicle stability. Secondly, a fuzzy variable parameter active rear-wheel steering controller and a compensated yaw moment controller are designed. Then, for the coupling problem between the two controllers, a coordination rule is proposed based on the stability index PPS-region of the phase plane stability region. Finally, a hardware-in-the-loop testbed is built to verify the feasibility of the coordination control strategy proposed in this paper. Experimental results show that: When the vehicle is in different stable states, according to the divided steady state, the control strategy can be correctly switched to the corresponding control strategy, and the work of each subsystem can be reasonably coordinated. Under the continuous gain sine condition, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 73% and the side slip angle error response curve by 85%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 20% and 62.5%. In the case of double lane-change, the control algorithm can reduce the maximum amplitude of the yaw rate error response curve by 68.5% and the side slip angle error response curve by 57.4%. Compared with a single stability control system, the coordinated stability control algorithm can improve the control effect of yaw rate and side slip angle by 40.6% and 44.7%.

A wheel motor simplifies the chassis structure of an electric bus, greatly improving its response speed and controllability. How to improve the lateral stability of the vehicle under complex and changeable driving conditions is a major problem in the motion control of electric buses. This study proposed an adaptive distributed drive control strategy for a rear-wheel drive electric bus. An adaptive fuzzy controller was designed to obtain the additional yaw moment of the vehicle and then combined with a rule distribution method to modify the steering characteristics of the vehicle to obtain the optimal driving torque distribution. Hardware-in-the-loop test results showed that under adaptive fuzzy control, the yaw rate deviations under low- and high-speed conditions were reduced from 18% and 42% without control to 10% and 23% with control, respectively. Under sine wave conditions, the deviation of the yaw rate and the vehicle’s sideslip angle were reduced from 83% and 852% without control to 12% and 15% with control, respectively. It was verified that the electric bus with adaptive fuzzy control could maintain good vehicle stability at full speed.