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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.

Electro-Hydraulic Brake (EHB) system is a kind of active control brake systems of automobile, the pedal from the calipers actuation separated and no longer limited by conventional hardware. The system may come together with ABS, ESP, and ASR function, also the communication with other systems is done via the CAN network. EHB system may be classified a “stepping stone” technology to full brake-by-wire and brings huge transform for the performance of braking system. In this paper, vehicle dynamic models were established and accomplished the control strategy for vehicle stability control with EHB system which can adjust wheel and vehicle motion, improve the lateral and longitudinal vehicle stability. This result was verified by simulation which shows that the controller is effective on improving the vehicle stability.

This paper sets up a simplified dynamic model for simulating the yaw/roll stability of heavy tractor-semitrailer using Matlab/Simulink. A linear quadratic regulator (LQR) based on partial-state feedback controller is used to optimize the roll stability of the vehicle. The control objective for optimizing roll stability is to be reducing the lateral load transfer rate while keeping the suspension angle less than the maximum allowable angle. The simulation result shows that the LQR controller is effective in the active roll stability control of the heavy tractor-semitrailer.

It is difficult to obtain state variables accurately or economically while vehicle is moving, however these state variables are significant for chassis control. Although many researches have been done, a complex model always leads to a control system with poor real-time performance, while simple model cannot show the real characteristics. So, in order to estimate the value of yaw rate and side slip angle accurately and sententiously, an Extended Kalman Filter (EKF) observer is proposed, which is based on an ameliorated 2-DOF “bicycle model”. The EKF algorithm is achieved numerically and verified by the results from the real field test.

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.

Omni-directional electric vehicle built by our research group is an advanced electric vehicle whose four wheels can drive, steer and brake independently. The vehicle chassis system is composed of four in-wheel motors, four independent steer motors and electromagnetic brake system, and its control system is divided into logical control layer and underlying execution layer. The information exchange between these two layers is implemented by CAN bus. In this paper, the traction control logic for Omni-directional electric vehicle is developed. The study mainly involves two aspects: the vehicle states estimation and the traction control logic design. The vehicle states, including vehicle longitudinal velocity, lateral speed, side slip angle and yaw rate, etc, are estimated based on Extended Kalman Estimation and multiple degrees of freedom vehicle model.

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.

In order to accurately characterize the dynamic characteristics of articulated heavy vehicles, 3-dof (degree of freedom) model and 5-dof simplified model of articulated heavy vehicle are established and key parameters of models are identified by the method which is to combine double models with genetic algorithm and by using Trucksim data. Simulation study, which combines 5-dof simplified model with the MAPs of key identified parameters, is carried out. Comparison, which is between simulation results and Trucksim data, indicates that the key parameters of simplified model can be accurately identified, the MAPs of key identified parameters can satisfy the demand of characterizing the actual state of vehicle and lay a foundation for vehicle stability control.

The passive fault-tolerant performance of the integrated vehicle controller (IVC) applied on 4WID/4WIS Electric Vehicles has been investigated in this study. The 4WID/4WIS EV is driven independently by four in-wheel motors and steered independently by four steering motors. Thanks to increased control flexibility of the over-actuated architecture, Control Allocation (CA) can be applied to control the 4WID/4WIS EVs so as to improve the handling and stability. Another benefit of the over-actuated architecture is that the 4WID/4WIS Electric Vehicle has sufficient redundant actuators to fight against the safety critical situation when one or more actuators fail.

In order to improve the braking energy recovery, a parallel hybrid electric bus simulation model with electric braking system (EBS) was established by co-simulation platform for the TruckSim and Matlab/Simulink in this paper. EBS makes the front and rear shaft braking force arbitrarily distributed, which is more effective to improve the rate of energy recovery and the braking stability. A braking force distribution algorithm for hybrid electric bus based on EBS was designed in this paper. Under the premise to meet the driver's needs and the ECE regulations, this braking force distribution method focuses on making the braking force distribute to the drive shaft to a maximum extent, so as to obtain the maximum energy recovery rate by the utilization of the motor regenerative braking. At last, the simulation in different operating conditions was used to analyze the braking energy utilization and the braking performance based on the simulation model.

Steering-By-Wire (SBW) system has advantages of advanced vehicle control system, which has no mechanical linkage to control the steering wheel and front wheels. It is possible to control the steering wheel actuator and front wheels actuator steering independently. The goal of this paper is to use a joystick to substitute the conventional steering wheel with typical vehicle SBW system and to study a variable steering ratio design method. A 2-DOF vehicle dynamic reference model is built and focused on the vehicle steering performance of drivers control joystick. By verifying the results with a hardware-in-the-loop simulation test bench, it shows this proposed strategy can improve vehicle maneuverability and comfort.

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.

A full drive-by-wire electric vehicle, named Urban Future Electric Vehicle (UFEV) is developed, where the four wheels' traction and braking torques, four wheels' steering angles, and four active suspensions (in the future) are controlled independently. It is an ideal platform to realize the optimal vehicle dynamics, the marginal-stability and the energy-efficient control, it is also a platform for studying the advanced chassis control methods and their applications. A centralized control system of hierarchical structure for UFEV is proposed, which consist of Sensor Layer, Identification and Estimation Layer, Objective Control Layer, Forces and Motion Distribution Layer, Executive Layer. In the Identification and Estimation Layer, identification model is established by utilizing neural network algorithms to identify the driver characteristics. Vehicle state estimation and road identification of UFEV based on EKF and Fuzzy Logic Control methods is also conducted in this layer.

Electronic braking system (EBS) of commercial vehicle is developed based on Anti-lock Braking System (ABS), for the purpose of enhancing the braking performance. Based on the previous study, this paper aims at the development and research on the control strategy of advanced electronic braking system for commercial vehicle, which mainly includes braking force distribution and multiple targets control strategy. In the study of braking force distribution control strategy, the mass of vehicle and the axle loads will be calculated dynamically and the braking force of each wheel will be distributed regarding to the axle loads. The braking intention recognition takes the brake pad wear into account when braking uncritically, so it can detect a difference in the pads between the front and the rear axles. The brake assist strategy supports the driver during emergency braking and the braking distance is shortened by the reduction of the braking system response time.

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.

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.

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.