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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 research of driver behavior characteristics has been a focus of vehicle handling and stability performance. With the driver preview effort, many different driver preview models of direction control have been proposed and the simulations of driver-vehicle-road closed-loop system made. But in the simulation, most of the conventional models have the same precondition that the road was simply described as a pre-given preview course. How to simulate the driver dynamically deciding vehicle preview course based on the real road circumstance is the key to the further research of the driver model. In this paper, a new driver direction control model is established, which is called the Optimal Preview Lateral Acceleration (OPLA) Model and divided into three sub-models: driver’s information identification model, driver’s fuzzy decision model of vehicle preview course and driver’s performance first-order correction model.

To address the current situation of the limited driver-vehicle cooperative steering actuation structure, this paper proposes a feasible driver-vehicle shared steering control actuation architecture based on the differential steering. Firstly, a shared steering execution architecture is established, which contains traditional steering system controlled by human driver and differential steering system acting as the automatic execution system. In this paper, a specific driver-vehicle shared control architecture is established with the front-wheel hub motor-based differential steering system and a single-view angle based human driver model. Then, an upper-level sliding mode controller for path tracking is developed and implemented as the automatic steering system, and the driver-vehicle shared control is achieved by the proposed non-cooperative game model.

A unified tire model with non-isotropy of friction and arbitrary contact pressure distribution is presented as a foundation to study the key features of a reasonable expression of tire shear force and alignment torque under combined slip conditions. The effects of contact pressure distribution on tire mechanical characteristics are analyzed. A unified semi-empirical tire model with convenience in dynamics simulation is recommended. For determining the model parameters, a series of simple expressions that satisfy the boundary conditions are proposed and a new global fitting method for tire data processing is employed. Based on the improved semi empirical model, the USPA software is developed. This software reduces the modeling time from the tire data to a practical tire model and allows various tire characteristics analyses. Some experimental validations are shown.

A fault detection and diagnosis (FDD) algorithm of 4WID/4WIS Electric Vehicles has been proposed in this study aiming to find the actuator faults. The 4WID/4WIS EV is one of the promising architectures for electric vehicle designs which is driven independently by four in-wheel motors and steered independently by four steering motors. The 4WID/4WIS EVs have many potential abilities in advanced vehicle control technologies, but diagnosis and accommodation of the actuator faults becomes a significant issue. The proposed FDD approach is an important part of the active fault tolerant control (AFTC) algorithm. The main objective of the FDD approach is to monitor vehicle states, find the faulty driving motor and then feedback fault information to the controller which would adopt appropriate control laws to accommodate the post-fault vehicle control system.

With the development of the advanced driver assistance system and autonomous vehicle techniques, a precise description of the driver’s steering behavior with mathematical models has attracted a great attention. However, the driver’s steering maneuver demonstrates the stochastic characteristic due to a series of complex and uncertain factors, such as the weather, road, and driver’s physiological and psychological limits, generating negative effects on the performance of the vehicle or the driver assistance system. Hence, this paper explores the stochastic characteristic of driver’s steering behavior and a novel steering controller considering this stochastic characteristic is proposed based on stochastic model predictive control (SMPC). Firstly, a search algorithm is derived to describe the driver’s road preview behavior.

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.

Steer-by-Wire system is capable of improving the performance of vehicle handling and stability, and assisting driving. It becomes a key technique to control front wheel angle and simulate the steering resistance delivered to the driver because of removing mechanical linkages between the steering wheel and the front wheels. This paper proposes a bilateral control method of steering wheel torque drive/pinion angle feedback, which is disaccustomed of controlling steering wheel block and steering actuator as master-slave plants. The pinion angle, steering wheel angle and its torque signals are used in the control logic without estimating or measuring the tire/road force. Simulations and vehicle experiments proceeded with this proposed method and the results confirmed that it achieves the bilateral control of the position and torque between the two plants.

This paper presents an adaptive observer-based approach for the combined state estimation and active fault detection and isolation (FDI) of the individual-wheel-drive (IWD) vehicles. A 3-DOF vehicle model coupled with the Highway Safety Research Institute (HSRI) tire model is established and used as the observation model. Based on this model, the dual unscented Kalman filter (DUKF) technique is employed for the observer design to give fusion results of the interdependent state and parameter variables, which undergo nonlinear transformations, with the minimum square errors. Effectiveness of the proposed algorithm is examined and validated through co-simulation between MATLAB/Simulink and CarSim. The results demonstrate that the DUKF-based observer effectively filters the sensor signals, accurately obtains the longitudinal and lateral velocities, explicitly isolates the faulty wheel(s) and accurately estimates the actual torque(s) even with the presence of noise.

Driver steering feature clustering aims to understand driver behavior and the decision-making process through the analysis of driver steering data. It seeks to comprehend various steering characteristics exhibited by drivers, providing valuable insights into road safety, driver assistance systems, and traffic management. The primary objective of this study is to thoroughly explore the practical applications of various clustering algorithms in processing driver steering data and to compare their performance and applicability. In this paper, principal component analysis was employed to reduce the dimension of the selected steering feature parameters. Subsequently, K-means, fuzzy C-means, the density-based spatial clustering algorithm, and other algorithms were used for clustering analysis, and finally, the Calinski-Harabasz index was employed to evaluate the clustering results. Furthermore, the driver steering features were categorized into lateral and longitudinal categories.

This essay aims to develop an electrically controlled steering test bench and lay a solid foundation for the development of steering system. The first part mainly introduces the function, structure and working principle of the test bench. For the hardware system, it includes the steering system, fixture, sensors as well as a frameless disk motor for carrying out automatic motor input, and a dual linear motor system selected as the road resistance simulation actuator. As for the software, MATLAB/Simulink, CarSim, RTI and ControlDesk are used. Therefore, with the help of real-time simulation platform, researchers can not only build control strategy and dynamic model but also control the experiment and tune parameters in real-time. The second part of the essay aims to identify both electric and mechanical parameters of R-EPS system by carrying out tests on the proposed test bench. As parameters are successfully identified, the feasibility of the test bench is also verified.

Nowadays active collision avoidance has become a major focus of research, and a variety of detection and tracking methods of obstacles in front of host vehicle have been applied to it. In this paper, laser radars are chosen as sensors to obtain relevant information, after which an algorithm used to detect and track vehicles in front is provided. The algorithm determines radar's ROI (Region of Interest), then uses a laser radar to scan the 2D space so as to obtain the information of the position and the distance of the targets which could be determined as obstacles. The information obtained will be filtered and then be transformed into cartesian coordinates, after that the coordinate point will be clustered so that the profile of the targets can be determined. A threshold will be set to judge whether the targets are obstacles or not. Last Kalman filter will be used for target tracking. To verify the presented algorithm, related experiments have been designed and carried out.

Electronic braking system (EBS) of commercial vehicle is developed from ABS to enhance the brake performance. Based on the early development of controller hardware, this paper starts with an analysis of the definition of EBS. It aims at the software design of electronic control unit, and makes it compiled into the controller in the form of C language by the in-depth study about control strategy of EBS in different braking conditions. Designed controller software is divided into two layers. The upper control strategy includes the recognition algorithm of driver's braking intention, estimation algorithm of the vehicle state, conventional braking strategy which consists of the algorithm of deceleration control and braking force distribution, and emergency braking strategy which consists of the algorithm of brake assist control and ABS control.

This paper first presents an algorithm to detect tire blowout based on wheel speed sensor signals, which either reduces the cost for a TPMS or provides a backup in case it fails, and a tire blowout model considering different tire pressure is also built based on the UniTire model. The vehicle dynamic model uses commercial software CarSim. After detecting tire blowout, the active braking control, based on a 2DOF reference model, determines an optimal correcting yaw moment and the braking forces that slow down and stop the vehicle, based on a linear quadratic regulator. Then the braking force commands are further translated into target pressure command for each wheel cylinder to ensure the target braking forces are generated. Some simulations are conducted to verify the active control strategy.

This paper presents a general kinematical model for all variety of leaf springs, including traditional laminated, asymmetrical, and tapered leaf springs, to calculate the longitudinal and winding deformations of axles during bouncing, braking and traction, which may introduce additional steering effects or variations of roll-steer property of a vehicle. Some experiments were introduced to verify the model. Accordingly, braking performance of a light truck has been improved.

Pneumatic Electric Braking System (EBS) is getting widely spread for commercial vehicles. Pneumatic EBS improves the problem of slow response of traditional pneumatic braking system by implementing brake-by-wire. However, the time-delay response and hysteresis of some electro-pneumatic components and some other issues decrease the response and control accuracy of the pneumatic EBS.

A long vehicle is more difficult to drive than a short one, but the mechanism of this phenomenon is still ambiguous. This paper will devote main effort to elaborate this phenomenon based on the theory of preview-follower driver model. Drivers always hope that the vehicle center can travel according to a predetermined trajectory. However, there is often a deviation between the vehicle center predicted by the driver and the actual center. As for this phenomenon, a conception of driver preview eccentricity is proposed. In order to analyze the influence of the proposed conception on vehicle driving track, a multi-axle steering vehicle model is built and some basic expressions of important parameters are deduced from this model firstly. Then, the developmental driver model with the factor of preview eccentricity based on preview-follower theory is established in the state of low velocity quasi-static. Subsequently, this model for long vehicles is extended to a dynamic driver model.

The behavior of driver course decision making is analyzed with the theory of system fuzzy decision making, and some factors that influence this behavior are studied also. Based on these, a fuzzy decision making model of driver dynamically determining vehicle preview course is given. This model can simulate the driver's control behavior of deciding the vehicle preview course in the process of driver handling the vehicle, based on the feasible region of front road. Taking advantage of fuzzy decision making theory's character, the model can describe many decision criteria such as driving safety, driving handiness and driving legality. The simulation results show that the model can be directly applied into the simulation of driver-vehicle-road closed-loop system and the research of intelligent vehicle.

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.

This study investigates the fundamental stiffness and damping properties of a self-damped pneumatic suspension system, based on both the experimental and analytical analyses. The pneumatic suspension system consists of a pneumatic cylinder and an accumulator that are connected by an orifice, where damping is realized by the gas flow resistance through the orifice. The nonlinear suspension system model is derived and also linearized for facilitating the properties characterization. An experimental setup is also developed for validating both the formulated nonlinear and linearized models. The comparisons between the measured data and simulation results demonstrate the validity of the models under the operating conditions considered. Two suspension property measures, namely equivalent stiffness coefficient and loss factor, are further formulated.