Lateral Stability Control of Four-Wheel Independent Drive Electric Vehicles Based on Model Predictive Control

Four-wheel independent drive electric vehicle was used as the research object to discuss the lateral stability control algorithm, thus improving vehicle stability under limit conditions. After establishing hierarchical integrated control structure, we designed the yaw moment decision controller based on model predictive control (MPC) theory. Meanwhile, the wheel torque was assigned by minimizing the sum of consumption rates of adhesion coefficients of four tires according to the tire friction ellipse theory. The integrated simulation platform of Carsim and Simulink was established for simulation verification of yaw/rollover stability control algorithm. Then, we finished road experiment verification of real vehicle by integrated control algorithm. The result showed that this control method can achieve the expectation of effective vehicle tracking, significantly improving the lateral stability of vehicle

Mitigating Instability in Electric Drive Vehicles Due to Time Varying Delays with Optimised Controller

The instability in the Electric vehicle would reduce the performance and even severely damage the system. This instability is mainly due to the random time-varying delays occurring in CAN network and the improper efficiency of controllers. This uncertainty and error occurrence makes it difficult to design the electric vehicles considering the advantages of Electric Vehicles being, the future to reduce harmful emissions due to fossil fuels, the instability can be mitigated by using optimized H∞ controller. The results of Simulations through MATLAB demonstrate the Effectiveness of the improved controller by comparing with the normal PI controller. The results of comparison illustrate the strength of explicitly

Control of an Independent 4WD electric vehicle by DYC method

Current advances in the application of control systems to vehicle dynamics has made it practicable to improve the vehicle’s longitudinal, lateral and vertical dynamics. Some of the examples of application of these systems to vehicle control are traction control (longitudinal dynamics) to prevent wheel slip, ESP (lateral dynamics) to prevent loss of stability, and active suspension (vertical dynamics) to increase ride comfort. In this paper, the vehicle lateral motion is controlled by direct yaw control (DYC) method. This uses the yaw moment produced by the longitudinal forces of the tyres, for stabilising the vehicle motion during critical cornering conditions. The system is been designed to give substantially enhanced active safety and dynamic handling control. The vehicle dynamics control algorithm is developed for a FOX vehicle by controlling couple traction/braking torque of the four in-wheel motors, from basic driving slogans. These are the steering angle, position of the accelerator pedal and brake by the position of the brake pedal, as shown in Figure 1

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs

Dynamic Optimization Self-adaptive AI Controller for a Four-wheel Independent Drive Electric Rover

In this paper, a dynamic optimization self-adaptive controller for a four-wheel independent drive electric rover has been investigated to enhance the dynamic stability. The proposed self-adaptive AI controller is based on dynamic Fuzzy Logic (FL) control mechanism. The dynamic self-adaptive properties have been integrated into the proposed FL controller through a dynamically tuned Particle Swarm Optimization (PSO) mechanism. Nevertheless, the dynamic FL controller and the dynamic PSO mechanism has been synchronized together for every sampling instance k to obtain the optimum performance of the electric rover. In this electric rover, all the four wheels have a fixed orientation and each wheel powered by a 250-Watt Brushless Direct Current (BLDC) motor through separate gear ratio mechanisms to obtain the desired torque and angular velocity. Therefore, the steering mechanism was achieved in this rover through the proposed AI controller, which was based on the differential speed mechanism. However, this paper presents the control methodology and obtained test results related to straight road tests under different slippery road conditions. The rover test results show that on different slippery road conditions the proposed PSO based FL controller has maintained the wheel slip ratio of all the four wheels which was less than 0.35 approximately. Here, the translational speed has been limited to 40 km/hr approximately within its recorded top speed of 90 km/hr while maintaining the desired fix orientation