Search Results

Heavy commercial vehicles have large variations in load and high centroid positions, so it is particularly important to obtain timely and accurate load information during driving. If the load information can be accurately obtained and the braking force of each axle can be distributed on this basis, the braking performance and safety of the entire vehicle can be improved. Heavy commercial vehicle load information is different from passenger vehicles, so it is particularly important to study commercial vehicles engaged in freight and passenger transportation. Presently, numerous research endeavors focus on evaluating the quality of passenger vehicles. However, heavy commercial vehicles exhibit notable distinctions compared to their passenger counterparts. Due to substantial variations in vehicle mass pre and post-loading, coupled with notable suspension deformations, significant changes are observed.

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.

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.

It aims to study the unsteady flow characteristic of the side-view mirror wake field, and reduce the wind noise by means of unsteady flow control. In this paper, the PIV test in a wind tunnel is used to capture the unsteady flow in the wake field of the side-view mirror, which is used to verify the accuracy of the steady simulation method with RANS after being averaged. Then LES turbulence model is used to obtain the wind noise, and the unsteady flow characteristic like vortex shedding of the side-view mirror is studied. The results show that, in the wake of the side-view mirror, there is a vortex pair similar to Karman Vortex Street. In both horizontal and vertical sections, these two vortexes are respectively separated from the upper and lower edges of the side-view mirror. Accompanied by a significantly uncertain periodic shedding, they continue to extend back until dissipating.

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.

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.

As one of the key technologies for EVs and HEVs, the design of their motors has been researched extensively, and some novel rotors of permanent magnet motor were proposed in order to improve torque capability, including average torque and torque ripple. Rotor structure selection of drive motor for various electric vehicles has been one of the key issues in matching of electric vehicle power system. Three motors are analyzed for providing visible insights to the contribution of different rotor structures to the torque characteristics, efficiency and extended speed range. First, an iterative comparative analysis of torque-speed characteristics with different flux linkage, d-axis inductance and rotor saliency ratio is performed for demonstrating the design principle. Then, the three motors are optimized by a genetic algorithm (GA) for further improving the torque characteristics.

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.

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.

LiDAR sensors have played more and more important role on Intelligent and Connected Vehicles (ICV) and Advanced Driver Assistance Systems (ADAS) .However, the development and testing of LiDAR sensors under real driving environment for ADAS applications are greatly limited by various factors, and often are impossible due to safety concerns. This paper proposed a novel functional LiDAR model under virtual driving environment to support development of LiDAR-based ADAS applications under early stage. Unlike traditional approaches on LiDAR sensor modeling, the proposed method includes both geometrical modeling approach and physical modeling approach. While geometric model mainly produces ideal scanning results based on computer graphics, the physical model further brings physical influences on top of the geometric model. The range detection is derived and optimized based on its physical detection and measurement mechanism.

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.

The driving range of the electric vehicle (EV) greatly restricts the development of EVs. The vehicles waste plenty of energy on account of automobiles frequently braking under the city cycle. The regenerative braking system can convert the braking kinetic energy into the electrical energy and then returns to the battery, so the energy regeneration could prolong theregenerative braking system. According to the characteristics of robustness in regenerative braking, both regenerative braking and friction braking based on fuzzy logic are assigned after the front-rear axle’s braking force is distributed to meet the requirement of braking security and high-efficient braking energy regeneration. Among the model, the vehicle model and the mechanical braking system is built by the CRUISE software. The paper applies the MATLAB/SIMULINK to establish a regenerative braking model, and then selects the UEDC city cycle for model co-simulation analysis.

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.

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.

This paper establishes a brake pedal model for braking intention identification, using the structural features of electronic braking system and selecting the proper parameters. A three-dimensional model is built that the input parameters are pedal displacement and pedal displacement change rate, and the output parameter is braking intensity. The relationship between the driver braking operation and braking intention are designed. A hardware-in-the-loop test bench experiment has been taken under several skilled drivers to practice the established the brake pedal model with the operation data during the braking. Thus, it results a model indicating the braking intention by braking operation that means effectively improve the braking comfort and applies to the research of electronic braking system of commercial vehicle.

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.

Electro-hydraulic power steering system (EHPS) maintains the advantages of Hydraulic power steering system (HPS) and Electric power steering system (EPS).It is even more superior than this two. In the foreseeable future, this system will have a certain development space. Assistant characters analysis was carried out in this paper. Control strategy based on steering states and feedback control strategy were designed too. Besides, aiming at the emergency steering conditions, steering angular velocity additional controlling strategy was brought out. Under emergency steering conditions, steering angular velocity additional controlling strategy will be applied. Additional steering moment will be calculated to ensure the assistant follow steering rapidly.

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.

This paper proposes a novel allocation-based control method for four-wheel independently actuated electric vehicles. In the proposed method, both actuator dynamics and input/output constraints are fully taken into consideration in the control design. First, the actuators are modeled as first-order dynamic systems with delay. Then, the control allocation is formulated as an optimization problem, with the primary objective of minimizing errors between the actual and desired control outputs. Other objectives include minimizing the power consumption and the slew rate of the actuator outputs. As a result, this leads to frequency-dependent allocation that reflects the bandwidth of each actuator. To solve the optimization problem, an efficient numerical algorithm is employed. Finally the proposed control allocation method is implemented to control a four-wheel independently actuated electric vehicle.