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In order to improve the trajectory tracking accuracy and yaw stability of vehicles under extreme conditions such as high speed and low adhesion, a coordinated control method of trajectory tracking and yaw stability is proposed based on four-wheel-independent-driving vehicles with four-wheel-steering. The hierarchical structure includes the trajectory tracking control layer, the lateral stability control decision layer, and the four-wheel angle and torque distribution layer. Firstly, the upper layer establishes a three-degree-of-freedom vehicle dynamics model as the controller prediction model, the front wheel steering controller is designed to realize the lateral path tracking based on adaptive model predictive control algorithm and the longitudinal speed controller is designed to realize the longitudinal speed tracking based on PID control algorithm.

The rapid development of city traffic makes the driving conditions faced by vehicles increasingly complex. The drive-by-wire chassis vehicle has the characteristics of four-wheel independent steering, four-wheel independent drive and four-wheel independent braking, which has become a current research hotspot because that can meet various complex working conditions. However, it is precisely because of the high degree of controllability of the drive-by-wire chassis that the research on the control strategy has become difficult. In this paper, an integrated control strategy based on the hierarchical algorithm framework is designed for the drive-by-wire chassis vehicle, which includes a centralized control layer, a tire force distribution layer and an actuator control layer.

Steering movement is the most basic movement of the vehicle, in the car driving process, the driver through the steering wheel has always been to control the direction of the car, in order to achieve their own driving intention. Four Wheel Steering (4WS) is an advanced vehicle control technique which can markedly improve vehicle steering characteristics. Compared with traditional front wheel steering vehicles, 4WS vehicles can steer the front wheels and the rear wheels individually for cornering, according to the vehicle motion states such as the information of vehicle speed, yaw velocity and lateral acceleration. Therefore, 4WS can enhance the handling stability and improve the active safety for vehicles.

This paper presents a fault-tolerant control (FTC) method for four-wheel independently driven and steered (4WIS/4WID) electric vehicles based on a reconfigurable control allocation to increase the flexibility for vehicle control and improve the safety of vehicle after the steering actuator fails. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle steering condition, detects and diagnoses actuator failures; 2) an upper controller that computes the generalized forces/moments to track the desired vehicle motion and trajectory; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels. The FTC approach based on the reconfigurable control allocation reallocates the generalized forces/moments among healthy steering actuators and driving motors once the actuator failures is detected.

The tire mechanics characteristics are essential for analysis and control of vehicle dynamics. Basically, the effects of sideslip, longitudinal slip, camber angle and vertical load are able to be represented accurately by current existing tire models. However, the research of velocity effects for tire forces and moments are still insufficient. Some experiments have demonstrated that the tire properties actually vary with the traveling velocity especially when the force and moment are nearly saturated. This paper develops an enhanced brush tire model and the UniTire semi-physical model for tire forces and moments under different traveling velocities for raising need of advanced tire model. The primary effects of velocity on tire performances are the rubber friction distribution characteristics at the tire-road interface.

Distributed steering vehicle uses four steering motors to achieve four wheel independent steering. The steering angle of each wheel can be distributed respectively. The tire cornering characteristics are added to traditional steering model to study the angle allocation control algorithm. Using the constraint relation between tire slip angle, vehicle speed, yaw rate and front steering angle, and connecting with the ideal ackermann steering relationship, steering angle allocation of front wheel independent steering and four wheel independent steering is derived. Then simulated analysis is carried out to demonstrate the efficiency of the algorithm. Improvements in tire wear condition are determined by evaluating the optimization in tire lateral force, and the vehicle stability is determined by vehicle slip angle. The simulation results show that the angle allocation control algorithm has a good effect on improving tire wear condition and enhancing the stability of vehicle.

This paper presents a fault-tolerant control (FTC) algorithm for four-wheel independently driven and steered (4WID/4WIS) electric vehicle. The Extended Kalman Filter (EKF) algorithm is utilized in the fault detection (FD) module so as to estimate the in-wheel motor parameters, which could detect parameter variations caused by in-wheel motor fault. A motion controller based on sliding mode control (SMC) is able to compute the generalized forces/moments to follow the desired vehicle motion. By considering the tire adhesive limits, a reconfigurable control allocator optimally distributes the generalized forces/moments among healthy actuators so as to minimize the tire workloads once the actuator fault is detected. An actuator controller calculates the driving torques of the in-wheel motors and steering angles of the wheels in order to finally achieve the distributed tire forces. If one or more in-wheel motors lose efficacy, the FD module diagnoses the actuator failures first.

Heavy vehicles have the characteristics of with high center of gravity position, large weight and volume, wheelbase is too narrow relative to the body height and so on, so that they always prone to rollover. In response to the above heavy security problems of heavy vehicle in running process, this paper mainly analyzes roll stability and yaw stability mechanism of heavy vehicles and studies the influence of vehicle parameters on stability by establishing the vehicle dynamics model. At the same time, this paper focuses on heavy vehicles stability control methods based on simulation and differential braking technology. At last, verify the effect of heavy vehicle stability control by computer simulation. The results shows that self-developed stability control algorithm can control vehicle stability effectively, so that the heavy vehicles instability can be avoided, the vehicle driving safety and braking stability are improved.

Electric Power Steering System (EPS) can directly provide auxiliary steering torque via a motor. The motor and the reducer in mechanical system will make the friction torque in steering system larger, as a result, the ability of steering returning will be reduced. Therefore, during the design of EPS system control strategy, an extra active return-to-middle control strategy is needed. For the fact that most of the low-end vehicles equipped with EPS system do not have a steering wheel angle sensor, a control strategy has to work without the datum of steering wheel angle. This paper proposes an active return-to-middle control method without steering wheel angle sensor, based on the estimated aligning torque which is converted to the pinion, and expounds how to determine the steering system current motion state in detail. This control method will work just during the turning condition, so it has no effect on the EPS basic assist characteristics.

Aiming at estimating the vehicle mass and the position of center of gravity, an on-line two-stage estimator, based on the recursive least square method, is proposed for buses in this paper. Accurate information of the center of gravity position is crucial to vehicle control, especially for buses whose center of gravity position can be varied substantially because of the payload onboard. Considering that the buses start and stop frequently, the first stage of the estimator determines the bus total mass during acceleration, and the second stage utilizes the recursive least-square methods to estimate the position of the center of gravity during braking. The proposed estimator can be validated by the co-simulation with MATLAB/Simulink and TruckSim software, simulation results exhibit good convergence and stability, so the center of gravity position can be estimated through the proposed method in a certain accuracy range.

Four-wheel independent drive EV is driven by four brushless DC motors which are embedded in the wheel hubs. It enables each wheel's driving torque to be controlled independently. Due to the motors' torque and rotational speed easily measured, as well as the features of fast response and precise control, the EV enjoys obvious advantages over traditional vehicles in acceleration slip regulation. In this paper a novel acceleration slip regulation strategy for four-wheel independent drive EV is studied. The strategy includes a road identification module for the peak value of road adhesion coefficient and a slip regulation logic based on PID algorithm. Through comparing the current wheel slip ratio and the utilized adhesion coefficient with the typical roads' value, the identification module adopts the fuzzy control algorithm to recognize the similarity between the current road and the typical roads. Utilizing the similarity we can calculate the optimal slip ratio of the current road.