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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.

A new electric power steering system (EPS) dynamic friction model based on normalized Bouc-Wen model is given, as well as its structure form and model features. In addition, experimental method is used to identify corresponding parameters. In order to improve road feel feedback, this paper analyzes the shortcoming of traditional constant friction compensation control method and proposes a variable friction compensation control method which the friction compensation current changes according to the assist characteristic gain. Through simulation and real vehicle test verification, variable friction compensation control method eliminates the effect of basic assist characteristic, and improves the driver’s road feel under high speed.

For the vehicles equipped with Electric Power Steering (EPS) system, the friction and damping effect brought by assisted motor and worm gear mechanism influence the return ability and handing stability. In order to eliminate the impacts, it is necessary to add return-to-center control in EPS control strategy. This paper proposes a practical active return-to-center control strategy with steering wheel angle signals based on return state identification. In the strategy, the return state of the steering system is identified quickly according to the two signals steering wheel angle velocity and steering wheel torque. Only under return state, a double closed-loop PID control strategy is carried out to calculate a compensation current to improve the return ability. For validating the proposed strategy, a fine EPS model including BLDC assisted motor is built based on carsim and simulink co-simulation platform.

This paper presents an integrated chassis controller with multiple hierarchical layers for 4WID/4WIS electric vehicle. The proposed systematic design consists of the following four parts: 1) a reference model is in the driver control layer, which maps the relationship between the driver's inputs and the desired vehicle motion. 2) a sliding mode controller is in the vehicle motion control layer, whose objective is to keep the vehicle following the desired motion commands generated in the driver control layer. 3) By considering the tire adhesive limits, a tire force allocator is in the control allocation layer, which optimally distributes the generalized forces/moments to the four wheels so as to minimize the tire workloads during normal driving. 4) an actuator controller is in the executive layer, which calculates the driving torques of the in-wheel motors and steering angles of the four wheels in order to finally achieve the distributed tire forces.

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.

As a new form of electric vehicle, Four-wheel-independent electric vehicle with X-By-Wire (XBW) inherits all the advantages of in-wheel motor drive electric vehicles. The vehicle steering system is liberated from traditional mechanical steering mechanism and forms an advanced vehicle with all- wheel independent driving, braking and steering. Compared with conventional vehicles, it has more controllable degrees of freedom. The design of the integrated vehicle dynamics control systems helps to achieve the steering, driving and braking coordinated control and improves the vehicle's handling stability. In order to solve the problem of lacking of vehicle state information in the integrated control, some methods are used to estimate the vehicle state of four-wheel-independent electric vehicles with XBW. In order to improve the estimation accuracy, unscented Kalman filter (UKF) is used to estimate the vehicle state variables in this paper.

Four-wheel independent control electric vehicle is a new type of x-by-wire EV with four wheels independent steering and four wheels independent drive/brake systems. In order to take full advantage of the vehicle's performance potential, this paper presents a novel integrated chassis control strategy. In the paper, the strategy is designed by the hierarchical control structure and divided into integrated control layer and allocation layer. By this method, the control logical can be modularized and simplified. In the integrated control layer, Model Prediction Control (MPC) is adopted to design the integrated control unit, which belongs to be a kind of local optimization algorithm with feedback correction features. Using this method could avoid the system performance degradation caused by the control model mismatch. The control allocation layer is to optimally distribute the vehicle control forces to the steering/driving/brake actuators on each wheel.

Impact torque will be generated on the steering wheel when one tire suddenly blows out on high way, which may cause driver's psychological stress and result in driver's certain misoperations on the car. In this paper, the model of tire blowout vehicle was established; the tire blowout was detected based on the change rate of tire pressure, meanwhile, the rack force caused by tire blowout was estimated through a reduce observer; finally the compensation current was figured out to reduce the impact torque on the steering wheel. Results of simulation tests showed that the control strategy proposed in this paper can effectively reduce the impact torque on the steering wheel and reduce the driver's discomfort caused by tire blowout.