No abstract

Background: Automobile anti-lock braking system (ABS) is an important part of automobile active safety control system, which is widely used in all kinds of automobiles. At present, the research of ABS mainly focuses on the research of control algorithm, which is intended to improve the stability, robustness and adaptability of the control algorithm. Objective: ABS control algorithm has become a research hotspot. Different research workers have proposed different control algorithms and patents because of the different tools used and the entry points of the research. These control algorithms have played a role in promoting the development of ABS. This article reviews various control algorithms. Method: According to the research status of domestic and foreign researchers in the field of ABS control algorithms, ABS control algorithms are mainly divided into two categories: control methods based on logic thresholds and control methods based on slip ratio. Results: The comparative study of ABS control methods shows that the logic threshold control method has strong maneuverability and simple implementation, but its adaptability is poor. Sliding mode control has strong robustness and good transient response, but chattering needs to be suppressed. Although the PID control algorithm is simple and easy to implement, it needs to improve the transient response of the system. In the future, it is necessary to explore adaptive robust control algorithms that adapt to extreme conditions such as high nonlinearity and road sudden changes, such as active disturbance rejection control technology, deep learning neural network control technology, etc.

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.

A fuzzy sliding mode variable structure control method based on road surface recognition was proposed to solve the problem that the Anti-lock Braking system (ABS) effect of current ABS algorithm was not ideal on complex road surface. In the road recognition module, real-time estimation of 5 typical road surfaces using fuzzy logic control. Dynamic calculation of optimal slip ratio for different road surfaces based on identified road conditions. Design of ABS sliding mode variable structure controller with optimal slip ratio and actual slip ratio as input. Aiming at the chattering problem of sliding mode control, a fuzzy controller is designed to reduce chattering. An 8-DOF dynamic simulation model of a four-wheel hub motor is established. The effectiveness of the controller is verified by braking simulation experiments on medium and low adhesion road. By comparing the simulation test with the traditional sliding mode controller under the condition of high adhesion road, the suppression effect of the system chattering is verified, and its excellent control performance is proved.

Aims and Objectives: The stability control of the four-wheel hub motor-driven electric vehicle is of great significance to the safety of the driver during the driving process, and the torque fluctuation is an important factor that affects the stability control of the vehicle. Therefore, this paper reviews the key technologies and difficulties of torque ripple suppression for in-wheel motor-driven electric vehicles from two aspects: rational design of the in-wheel motor structure to suppress the torque fluctuation of the motor and the in-wheel motor torque control distribution strategy. Methods: Through the analysis of the structural characteristics of the motor, the structural optimization design of the pole slot, cogging, core shape, and magnetic pole shape is used to suppress the torque fluctuation of the motor, and the methods of previous scholars are unified and explained; starting from the control strategy of the motor, Through explaining a series of methods and strategies of scholars to suppress the torque fluctuation of the motor; from the perspective of the motor torque control distribution strategy, the relevant strategies are explained. The previous researchers proposed the neural network PID electronic differential speed torque comprehensive control Strategies, electronic differential control algorithms based on sliding mode control, automotive electronic stability program control algorithms based on hierarchical coordinated control strategies, and other control strategies and algorithms. Results: Based on the theoretical model, the theoretical model is verified and tested through software simulation or test platform. The errors of all simulation and test results in the literature and the theoretical model are within the acceptable range. Conclusion: The theoretical model has been verified on the software simulation or test platform, which proves the feasibility and effectiveness of the theoretical model, thereby suppressing torque fluctuations and improving the stability of the vehicle. Finally, the development direction of the key technology of torque ripple suppression for four-wheel in-wheel motor-driven electric vehicles is prospected.