The Experts below are selected from a list of 297 Experts worldwide ranked by ideXlab platform

Hong Chen - One of the best experts on this subject based on the ideXlab platform.

  • Simulation Analysis of Traction Control System for Four-Wheel-Drive Vehicle Using Fuzzy-PID Control Method
    Communications in Computer and Information Science, 2020
    Co-Authors: Hong Chen
    Abstract:

    A dynamic model of Four-Wheel-Drive vehicle was established and the Traction Control System (TCS) algorithm based on fuzzy-PID control was realized through rectifying the output torque of engine in real time and then switching parameter of fuzzy-PID controller was studied. The fuzzy logic controller was designed with MATLAB fuzzy control toolbox. Contrastive simulation has been carried out with SIMULINK, which has the better results than those based on common fuzzy control in controlling effect.

  • Estimation Road Slope and Longitudinal Velocity for Four-Wheel Drive Vehicle
    IFAC-PapersOnLine, 2018
    Co-Authors: Hong Chen, Li Chao
    Abstract:

    Abstract A method for estimating the velocity and road slope of a Four-Wheel Drive vehicle based on full-order observer is proposed. First, we set up a simplified dynamic model of ramp driving which use the longitudinal acceleration as input. This paper use the longitudinal velocity and the longitudinal acceleration as the correction term respectively and design the nonlinear full-order observer of vehicle velocity; Secondly, design the estimation observer for road slope which used the estimation value of longitudinal velocity and longitudinal acceleration as inputs. Finally, we experimentally evaluate the recommended velocity and road slope estimation method on the high-precision vehicle dynamic software-veDYNA to verify the validity of the proposed observer. Then two ways of selecting correction terms are compared and analysed. The results show that the observer which uses the longitudinal velocity as the correction term has relatively higher accuracy.

  • An modular sideslip angle and road grade estimation scheme for Four-Wheel Drive vehicles
    2016 35th Chinese Control Conference (CCC), 2016
    Co-Authors: Fei Wang, Hong Chen
    Abstract:

    In this manuscript, a modular sideslip angle and road grade estimation scheme for Four-Wheel Drive (4WD) vehicles is proposed. The longitudinal tire forces are estimated based on disturbance observer, then the lateral tire forces are computed using the estimation of longitudinal tire forces as inputs based on the dugoff tire model. In the following, the full-dimensional nonlinear observer is designed to estimate the vehicle velocities, which fits for different road grade. In the following, the sideslip angle is obtained. In order to specify the effectiveness of the proposed modular estimation scheme, simulations of double lane change maneuver on low friction coefficient road for 4WD vehicle running are carried out. The simulation results verify that the proposed integrated observer could obtain accurate estimation results of sideslip angle, vehicle velocities, and road grade.

  • The Four-Wheel-Drive electric-vehicle model development based on AMESim
    Proceedings of the 32nd Chinese Control Conference, 2013
    Co-Authors: Hong Chen, Haiyan Zhao
    Abstract:

    For needs of verifying the control algorithm, based on the commercial software AMESim, the Four-Wheel-Drive electric-vehicle model with hub motor is developed. And for the 8 DOF dynamics equation of Four-Wheel-Drive electric-vehicle, the simulation model is developed in Matlab/Simulink. In different conditions, compare the simulation results between AMESim model and the traditional mathematical model with the co-simulation technology. The result shows that curve basically is the same, and the AMESim model is of high accuracy and closer to the real car, which can be used for verifying the control algorithm.

  • Modeling and simulation of fuzzy control to traction control system of the Four-Wheel-Drive vehicle
    2010 2nd International Conference on Future Computer and Communication, 2010
    Co-Authors: Hong Chen, Xiaolong Zhang
    Abstract:

    A mathematical model of the acceleration process of Four-Wheel-Drive vehicle was established and a Traction Control System (TCS) which takes driving slip ratio as the control object was realized with fuzzy control method. The fuzzy controller was designed with Fuzzy Logic Toolbox of MATLAB, and dynamic simulation has been carried out with SIMULINK. The result showed that TCS based on fuzzy control could control driving slip round the optimal value, improve the performance of traction and kinetics effectively, and prevent driving Wheel from excessive spinning.

Chih-ming Chang - One of the best experts on this subject based on the ideXlab platform.

  • Study on power train of two axles Four Wheel Drive electric vehicle
    Energy Procedia, 2012
    Co-Authors: Chih Hsien Yu, Chyuan Yow Tseng, Chih-ming Chang
    Abstract:

    This paper is focused on design of a power train for two-axle Four-Wheel-Drive (4WD) electric vehicle (EV). The purpose is to improve the energy efficiency, driving stability for an Utility Vehicle (UV) that is original equipped with a 500cc internal combustion engine. The designed power train is consisted of two 5kw brushless DC motors (BLDC) with the associated motor Drivers, automatic manual transmission (AMT), AMT controllers, and 288V16AH Lithium-ion battery pack. The works include power train specification design, mechanism and controller design for the clutchless AMT, optimal transmissions gear-shifting strategy design, and finally, power split strategy design for the 4WD in terms of Wheel slip ratio control. To guarantee AMT gear-shifting quality, the gear-shifting maps was applied in gear change process. The power split strategy design for the 4WD EV was based on sliding mode algorithm, it was shown through numerical simulation that slip ratio on each Wheel can be controlled within an optimal value in ECE40 Drive pattern. ?? 2011 Published by Elsevier Ltd.

Jun Wang - One of the best experts on this subject based on the ideXlab platform.

  • motor torque based vehicle stability control for Four Wheel Drive electric vehicle
    Vehicle Power and Propulsion Conference, 2009
    Co-Authors: Feiqiang Li, Jun Wang
    Abstract:

    Motor torque based active yaw moment control law is investigated in this paper, based on which vehicle stability control algorithm for Four-Wheel-Drive electric vehicle is proposed using fuzzy logic control method. As Four motors are mounted in the Four Wheels individually to Drive the vehicle, it has great advantage to use the advanced motion control technique to enhance vehicle stability. The Four driving and braking forces can be controlled independently to generate active yaw moment. However it is more complex to allocate the desired yaw moment to over-actuators. So the control law for fuzzy logic control algorithm is designed based on the dynamic analysis of vehicle instability. The electric vehicle models including motor model, dynamic battery model, tire model and vehicle dynamics model are built in MATLAB/Simulink®. Simulation performance is evaluated in the Simulink®, and the results have shown that the design control law and fuzzy logic controller can enhance the yaw stability and improve the maneuverability of the vehicle significantly.

Zhaodu Liu - One of the best experts on this subject based on the ideXlab platform.

  • Motor torque based vehicle stability control for Four-Wheel-Drive electric vehicle
    5th IEEE Vehicle Power and Propulsion Conference, VPPC '09, 2009
    Co-Authors: Fei Li, J.-X.b Wang, Zhaodu Liu
    Abstract:

    Motor torque based active yaw moment control law is investigated in this paper, based on which vehicle stability control algorithm for Four-Wheel-Drive electric vehicle is proposed using fuzzy logic control method. As Four motors are mounted in the Four Wheels individually to Drive the vehicle, it has great advantage to use the advanced motion control technique to enhance vehicle stability. The Four driving and braking forces can be controlled independently to generate active yaw moment. However it is more complex to allocate the desired yaw moment to over-actuators. So the control law for fuzzy logic control algorithm is designed based on the dynamic analysis of vehicle instability. The electric vehicle models including motor model, dynamic battery model, tire model and vehicle dynamics model are built in MATLAB/Simulinkreg. Simulation performance is evaluated in the Simulinkreg, and the results have shown that the design control law and fuzzy logic controller can enhance the yaw stability and improve the maneuverability of the vehicle significantly.

Li Feiqiang - One of the best experts on this subject based on the ideXlab platform.

  • FSKD (4) - Fuzzy-Logic-Based Controller Design for Four-Wheel-Drive Electric Vehicle Yaw Stability Enhancement
    2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
    Co-Authors: Li Feiqiang, Liu Zhao
    Abstract:

    Vehicle yaw stability enhancement controller for Four-Wheel-Drive electric vehicle is proposed in this paper based on the fuzzy logic control technique. Brake differential control is used to stabilize vehicle yaw motion significantly. However, the forces between road and tires are not utilized effectively enough. As Four motors are mounted in the Four Wheels individually to Drive the vehicle, the Four-Wheel-Drive electric vehicle has great advantage to use the tire traction and braking forces to generate active yaw moment for stabilizing vehicle motion. However it is more complex to allocate the desired yaw moment to over-actuators. So the control law for fuzzy logic controller is investigated based on the vehicle dynamic analysis. Simulation performance is evaluated in the CarMaker® virtual environment including Driver model and road model. And the simulation results have shown that the design control law and fuzzy logic controller can enhance the yaw stability of the vehicle significantly, especially on the low friction road.

  • Fuzzy-Logic-Based Controller Design for Four-Wheel-Drive Electric Vehicle Yaw Stability Enhancement
    2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009
    Co-Authors: Li Feiqiang, Liu Zhaodu
    Abstract:

    Vehicle yaw stability enhancement controller for Four-Wheel-Drive electric vehicle is proposed in this paper based on the fuzzy logic control technique. Brake differential control is used to stabilize vehicle yaw motion significantly. However, the forces between road and tires are not utilized effectively enough. As Four motors are mounted in the Four Wheels individually to Drive the vehicle, the Four-Wheel-Drive electric vehicle has great advantage to use the tire traction and braking forces to generate active yaw moment for stabilizing vehicle motion. However it is more complex to allocate the desired yaw moment to over-actuators. So the control law for fuzzy logic controller is investigated based on the vehicle dynamic analysis. Simulation performance is evaluated in the CarMaker® virtual environment including Driver model and road model. And the simulation results have shown that the design control law and fuzzy logic controller can enhance the yaw stability of the vehicle significantly, especially on the low friction road.