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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.

Electronically controlled air suspension (ECAS) systems have been widely used in commercial vehicles to improve the ride comfort and handling stability of vehicles, as it can adjust vehicle height according to the driving conditions and the driver's intent. In this paper, the vehicle height adjustment process of ECAS system is studied. A mathematical model of vehicle height adjustment is derived by combining vehicle dynamics theory and thermodynamics theory of variable mass system. Reasons lead to the problems of “over-charging”, “over-discharging” and oscillation during the process of height adjustment are analyzed. In order to solve these problems, a single neuron proportional-integral-derivative (PID) controller is proposed to realize the accurate control of vehicle height. By simulation and semi-physical rig test, the effectiveness and performance of the proposed control algorithm are verified.

The rapid development of city traffic makes the driving conditions faced by vehicles increasingly complex. The drive-by-wire chassis vehicle has the characteristics of four-wheel independent steering, four-wheel independent drive and four-wheel independent braking, which has become a current research hotspot because that can meet various complex working conditions. However, it is precisely because of the high degree of controllability of the drive-by-wire chassis that the research on the control strategy has become difficult. In this paper, an integrated control strategy based on the hierarchical algorithm framework is designed for the drive-by-wire chassis vehicle, which includes a centralized control layer, a tire force distribution layer and an actuator control layer.

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 paper describes an algorithm, which estimates the mass of large buses and axle load distribution using pedal position, wheel speed and the wheel cylinder pressure sensors. This algorithm is allowed to achieve the purpose without additional sensors by using the rotational speed sensors from ABS system and air pressure sensors in brake cylinders form ESP system. The axle load distribution algorithm mainly consists of three steps. Firstly, deceleration of the bus is estimated and then the mass of the bus is estimated. After that, the position of the mass centre is estimated. Taking account of the tire nonlinear characteristics under longitudinal forces and vertical forces, mass estimation, deceleration and the position of the mass centre of buses is corrected by the coefficient, which is determined by the wheel cylinder pressure, the wheel speed and mass estimation.

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.

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.

A fault tolerant control (FTC) approach based on reconfigurable control allocation for four-wheel independently driven and steered (4WID/4WIS) electric vehicles against driving motor failures is proposed in order to improve vehicle safety, performance and maneuverability after the driving motor failures. 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; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using model predictive control method; 3) a reconfigurable control allocator that optimally distributes the generalized forces/moments to four wheels aiming at minimizing the total tire usage. The FTC approach is based on the reconfigurable control allocation which reallocates the generalized forces/moments among healthy actuators once the actuator failures is detected.

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.

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.

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.

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.

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 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.

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.

An integrated control strategy for vehicle active suspension system which combines linear quadratic optimum control law with fuzzy control algorithm is designed to improve both ride and handling. The performance of this control strategy is then examined and assessed in an open-loop J-turn driving scenario on a random-rough road by means of computer simulation. Comparisons to a passive suspension system in terms of vehicle sprung mass vertical acceleration, body roll angle and yaw rate is conducted. Simulation results indicate that the integrated control strategy proposed in this paper could effectively enhance vehicle ride comfort meanwhile benefit handling quality and driving safety.

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.

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.