In-wheel motor electric vehicles have the advantages of independently controllable four-wheel torque, high energy utilization rate, and fast motor response speed, which greatly reduces the curb weight of the vehicle and simplifies the structure of the vehicle, making it an expert at home and abroad research hotspots. However, the in-wheel motor independently drives the electric vehicle. The in-wheel motor directly drives the vehicle, and the motion states of each wheel are independent of each other; that is, each wheel can be independently driven by wire control, which puts forward higher requirements for the torque distribution control of the entire vehicle. Starting from the driving form of the car, this paper focuses on the design of the torque distribution scheme of the in-wheel motor by experts and scholars in the past, such as the use of genetic algorithm, BP neural network, particle swarm algorithm, and fuzzy control algorithm to distribute the torque of the in-wheel motor, and the research on vehicle economy and stability under torque distribution optimization is reviewed. The future development direction of in-wheel motor torque distribution is prospected.

No abstract

Background: The on-board test system is the key technology of in-wheel motor electric vehicles, which plays a vital role in the safety of the driver and the efficient operation of the vehicle. Methods: Based on the requirements of the current in-wheel motor electric vehicle experiment teaching content, this research develops an in-wheel motor electric vehicle experimental teaching platform based on Matlab/Simulink and LabVIEW to meet the current needs of the in-wheel motor electric vehicle experiment teaching content. Results: The vehicle speed, sideslip angle, and road adhesion coefficient can be accurately estimated using the vehicle test platform developed in the article. Conclusion: With accurate experimental results, the functionality, value, and teaching value of the in-wheel motor electric vehicle experimental teaching platform were fully verified.