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With rapid increase of vehicles on the road, safety concerns have become increasingly prominent. Since the leading cause of many traffic accidents is known to be by human drivers, developing autonomous vehicles is considered to be an effective approach to solve the problems above. Although trajectory tracking plays one of the most important roles on autonomous driving, handling the coupling between trajectory-tracking control and ESP under certain driving scenarios remains to be challenging. This paper focuses on trajectory-tracking control considering the role of ESP. A vehicle model is developed with two degrees of freedom, including vehicle lateral, and yaw motions. Based on the proposed model, the vehicle trajectory is separated into both longitudinal and lateral motion. The coupling effect of the vehicle and ESP is analyzed in the paper. The lateral trajectory-tracking algorithm is developed based on the preview follower theory.

Vehicle detection has been a fundamental problem in the research of Intelligent Traffic System (ITS), especially in urban driving environment. Over the past decades, vision-based vehicle detection has got a considerable attention. In addition to the rich appearance information, the stereo vision method also provides depth information, which could achieve higher accuracy and precision. In this paper, a hybrid method for stereo vision-based real-time vehicle detection in urban environment is proposed. Firstly, we extract vehicle features and generate the Region of Interest (ROI). Semi-global Matching (SGM) algorithm is then utilized on the ROIs to generate disparity maps and get the depth information, which could be used to compute the width of each ROI. The noise regions, always with obvious depth variation in the disparity maps are excluded by the clustering approach.

Steering-by-wire(SBW) system makes the vehicle not constrained by the steering wheel control. Joystick, button and touch screen can all be used for automobile steering control. Using joystick to achieve steering operations has its unique advantages and many problems which are needed to be resolved at the same time. This paper firstly introduced the components of traditional steering wheel steer-by-wire system, then came up with the difference between joystick steer-by-wire system and traditional steer-by-wire system about transmission ratio, transmission ratio control strategy of joystick steer-by-wire system is proposed at the same time. At last, this paper studied driver’s busy degree when the vehicle running with a big turning radius at low speed and the effect of different angle transmission ratio on vehicle handing stability when the vehicle running at intermediate speed.

Electric power steering (EPS), active front wheel steering (AFS) and steer by wire systems (SBW) can enhance the handling stability and safety of the vehicle, even in dangerous working conditions. Now, the development of the electric control steering system (ECS) is mainly based on the way that combines the test of the electric steering hardware-in-loop (HIL) test bench with real vehicle tests. However, the real vehicle tests with higher cost, long cycle and vulnerable to space weather have the potential safety problems at early development. On contrast, electronic control steering HIL test bench can replace real vehicle tests under various working conditions and make previous preparations for real vehicle road tests, so as to reduce the number of real vehicle test, shorten the development cycle, lower development costs, which has gradually become the important link of research and development of electronic steering system.

This paper presents a simultaneous longitudinal and lateral motion control strategy for a full drive-by-wire autonomous vehicle. A nonlinear model predictive control (NMPC) problem is formulated in which the nonlinear prediction model utilizes a spatial transformation to derive the dynamics of the vehicle about the reference trajectory, which facilitates the acquisition of the tracking errors at varying speeds. A reference speed profile generator is adopted by taking account of the road geometry information, such that the lateral stability is guaranteed and the lane guidance performance is improved. Finally, the nonlinear multi-variable optimization problem is simplified by considering only three motion control efforts, which are strictly confined within a convex set and are readily distributed to the four tires of a full drive-by-wire vehicle.

The passive fault-tolerant approach for four-wheel independently driven and steered (4WID/4WIS) electric vehicles has been investigated in this study. An adaptive control based passive fault-tolerant controller is designed to improve vehicle safety, performance and maneuverability when an actuator fault happens. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle driving condition, detects and diagnoses actuator failures with the inequality constraints; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using Model Predictive Control (MPC); 3) a reconfigurable control allocator that redistributes the generalized forces/moments to four wheels with equality constrained optimization.

In this paper, the predictive control strategy is employed to improve the current tracking performance of hub motor in 4WD electric vehicle due to its fast dynamic response. But the performance of the conventional predictive deadbeat current control suffers greatly from the parameter variations and other disturbances. Toward this, this paper presents a new predictive control strategy for hub motor; this control scheme combines an improved predictive control law with a state-observer to estimate the future motor currents and system disturbances based on a decoupled model. It provides a decoupled control of hub motor and offers stability against the variations in motor inductance and robustness against system uncertainties. The feasibility and validity of the proposed predictive current control strategy is verified through the simulation results.

To research the torsional vibration damping characteristic of magneto-rheological fluid dual mass flywheel (MRF-DMF) and the control system in power train, the multi-degree power train torsional vibration model which contains MRF-DMF and semi-active fuzzy control model are built, then the damping characteristic of MRF-DMF in several conditions are gained and compared with MRF-DMF when no control system. The result indicates: the damping characteristic of MRF-DMF effect on power train when using control is better than without control in idle, speed up, slow down, ignition and stalling, while the damping characteristic is less obvious in constant speed because the simulation condition and damping moment relatively stable.

In order to improve structure and performance of magneto-rheological dual mass flywheel (MRF-DMF), some parameters effects on dynamic characteristics are acquired by parameters analysis. The dynamic stiffness and loss angle in different current and different frequency are gained through dynamic characteristic test. The fluid-structure interaction finite element model of MRF-DMF is built and the accuracy is verified by comparison between test and simulation. Based on the model, the parameters analysis is done and the law of MRF viscosity, arc spring stiffness, working clearance, rotor radius and axial width effect on dynamic characteristics are gained, it will prove some guidance for the structure and performance improvement.

This paper presents an ideal force distribution control method for the electric vehicle, which is equipped with four independently in-wheel motors, in order to improve the lateral stability of the vehicle. According to the friction circle of tyre force, the ideal distribution control method can be obtained to make the front and rear wheels reach the adhesion limit at the same time in different conditions. Based on this, the force re-distributed control is applied to enhance the security of vehicle when the in-wheel motor is in the failure mode. The simulation result shows that: the force distributed method can not only improves the lateral stability of the vehicle but also enhances the vehicle safety.

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.

This paper presents a torque distribution algorithm to improve the energy efficiency of four-wheel-drive (4WD) electric vehicles with PMSM hub motors. In order to optimize the torque distribution method, at first the motor model considering the affect of iron loss and the loss model of multi-motors drive system of 4WD electric vehicle with PMSM hub motors, which operate at straight-line condition, are established. Besides, realize the online identification of motor parameters based on the MARS, which is important for updating the loss model parameters of the motor drive system. By doing this, the ideal torque distribution ratio can be obtained from the loss model in real-time. The simulation result using different distribution algorithms shows that the optimized torque distribution algorithm based on the loss model can be useful for improving the energy efficiency.

Four-wheel-drive electric vehicles (4WD Evs) utilize in-wheel electric motors and Electro-Hydraulic Braking system (EHB). Then, all wheels torque can be controlled independently, and the braking pressure can be controlled more accurately and more fast than conventional braking system. Because of these advantages, 4WD Evs have potential applications in control engineering. In this paper, the in-wheel electric motors and EHB are applied as actuators in the vehicle stability control system. Based on the Direct Yaw-moment Control (DYC), the optimized wheel force distribution is given, and the coordination control of the hydraulic braking and the motor braking torque is considered. Then the EHB hardware-in-the-loop test bench is established in order to verify the effectiveness of the vehicle stability control algorithm through experiments.

For high torque permanent magnet wheel motor, this paper describes an experimental research method to optimize and identify the motor parameters based on the results of offline calculation. In order to improve the accuracy of motor parameters identification, the motor model considering the affect of iron loss was established, and the motor parameters were identified using genetic algorithm (GA). Based on this, parameters validation experiment was performed. The results show that: parameters obtained by this method can be used to describe the steady-state and transient-state response of permanent magnet synchronous motors accurately.

In order to improve the braking energy recovery and ensure the braking comfort, a new type of regenerative braking coordinated control algorithm is designed in this paper. The hierarchical control theory is used to the regenerative braking control algorithm. First, the front axle braking force and rear axle braking force are distributed. Then the rear axle motor braking force and mechanical braking force are distributed. Finally, the dynamic coordinated control strategy is designed to control pneumatic braking system and motor braking system. Aimed at keeping the fluctuation of the total braking force of friction and the regenerative braking force small during braking modes switch, a coordinated controller was designed to control the pneumatic braking system to compensate the error of the motor braking force. Based on Matlab/Simulink platform, a parallel hybrid electric bus simulation model with electric braking system (EBS) was established.

Pressure following control is the basic function of Electro-Hydraulic Braking system (EHB), which is also the key technology of stability control system and regenerative braking system for hybrid and electric vehicles. Experimental research is an important method for the control and application of EHB. This paper describes a method to test and control the EHB system through experiment on the Hardware-in-the-loop (HIL) test bench and wheel motor electric vehicle. First, the HIL test bench was established, in which the EHB was tested, including the characteristics of solenoid valves and motor. Then the wheel cylinder pressure was controlled to follow the specific signal input and the master cylinder pressure. Based on this, EHB and the pressure following control method were applied to the wheel motor electric vehicle. The results show that the braking pressure can follow the driver's braking intention to realize the conventional braking function of electric vehicles.

In order to reasonably match the variable stiffness suspension and optimize the ride comfort and stability of a light bus, a virtual prototype model of the light bus was established in Adams-Car. Before the optimization, the tyre mechanical characteristics were tested by using a plate-type tyre tester, then the magic formula model of the tyre (Pac2002) was obtained by means of the global parameter identification method. The vertical vibration of the virtual model was simulated with the simulated B-class road profile, and its handling stability performance was also studied by simulation of the pylon course slalom test and steady static circular test. After that, an optimal method of the variable stiffness suspension was put forward. In the proposed method, the two-level stiffness (k1, k2) and the damping of the rear suspension and the torsional stiffness of the pre and post stabilizer bars were taken as the optimal variables.

Automobile industry is facing the great challenge of energy conservation and emission reduction. It's necessary to do some researches on some surface components of a car body to find out which of them may affect aerodynamic drag remarkably. This will help an aerodynamic engineer modify an initial car model more clearly. We also hope to reduce the cost during the process, including time and resources. In this paper, with the purpose of developing an aerodynamic shape optimization process and realizing its automation, a MIRA reference car model was studied and three commercial softwares were integrated-Altair HyperStudy, HyperMesh and CD-adapco STAR-CCM+. The optimization strategy in this paper was: firstly, a DOE (design of experiment) matrix, which contained four design factors and thirty levels was created. The baseline model was morphed according to the DOE matrix. Then the morphed model's aerodynamic drag coefficient (Cd) and lift coefficient (Cl) were calculated via CFD software.

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.

The properties of contact patch are key factors for tire modeling. Researchers have paid more attention to the contact patch shape and vertical pressure distribution. Some innovative concepts, such as Local Carcass Camber, have been presented to explain special tire modeling phenomena. For a pragmatic tire model, a concise model structure and fewer parameters are considered as the primary tasks for the modeling. Many empirical tire models, such as the well-known Magic Formula model, would become more complex to achieve satisfactory modeling accuracy, due to increasing number of input variables, so the semi-empirical or semi-physical modeling method becomes more attractive. In this paper, the concept of Tire Carcass Camber is introduced first. Different from Local Carcass Camber, Tire Carcass Camber is an imaginary camber angle caused only by lateral force on the unloaded tire.