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According to the vehicle’s driving conditions, electronically controlled air suspension (ECAS) systems can actively adjust the height of vehicle body, so that better ride comfort and handling stability will be achieved, which can’t be realized by traditional passive suspension. This paper presents a design and implementation of ECAS controller for vehicle. The controller is aimed at adjusting the static and dynamic height of the vehicle. To exactly track the height of the vehicle and satisfy the control demand of air suspension, a height sensor decoding circuit based on the inductance sensor is designed. Based on it, a new height control algorithm is adopted to achieve rapid and precise control of vehicle height. To verify the function of the designed controller and the proposed height control algorithm, an air spring loading test bench and an ECU-in-loop simulation test bench are respectively established.

The commercial vehicle is widely used in the overland transport. A prediction is given on the 9th annual China automotive industry forum that the number of the global commercial vehicles will reach eight million by the year of 2016. However, since the distance between its gravity centre and the ground is larger than that of the passenger vehicle, considering its comparatively short wheelbase, the rollover accident, which is fatal to the drivers and always makes enormous loss of merchandises, easily occurs in the case of commercial vehicles. As the number of the commercial vehicle is increasing fast, the accidents will occur more frequently, the losses will be increasingly enormous. To solve the problem, many researches about rollover early warning systems have been done. In most cases, it is assumed that the references of the vehicle are given.

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.

At present, the active safety and stability of heavy vehicles have becoming big concern among the road transportation industry. The purpose of this paper is to specify the research stability and safety of heavy vehicles those set up the accurate and reliable dynamic vehicle reference model and search the method to improve the stability and safety of tractor and semitrailer. A Multi-objective control algorithm was studied to differential braking based on linear quadratic regulator (LQR) control method. Simulation results show that the multi-objective control algorithm can effectively improve the vehicle driving stability and safety.

The active safety and stability of tractor and trailer (heavy-duty vehicle) have becoming big concern among the road transportation industry. The purpose of this paper is to specify the research differential braking force distribution control algorithm to improve braking safety of heavy-duty vehicle. The ideal braking force of each wheel axle should be proportional to vertical load of vehicle that is also related to the road adhesion coefficient, the load and the braking intensity. Reasonable braking force distribution can enhance its braking stability and shorten the braking distance by making full use of the road adhesion condition of each wheel. A braking force distribution algorithm is proposed, in which the objective braking force change with the axle load 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.

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.