scholarly journals A Study of Coordinated Vehicle Traction Control System Based on Optimal Slip Ratio Algorithm

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Gang Liu ◽  
LiQiang Jin
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Control Method ◽  
Road Surface ◽  
Vehicle Model ◽  
Slip Ratio ◽  
Traction Control ◽  
Traction Control System ◽  
Optimal Slip Ratio ◽  
Vehicle Acceleration

Under complicated situations, such as the low slippery road surface and split-μroad surface, traction control system is the key issue to improve the performance of vehicle acceleration and stability. In this paper, a novel control strategy with engine controller and active pressure controller is presented. First and foremost, an ideal vehicle model is proposed for simulation; then a method for the calculation of optimal slip ratio is also brought. Finally, the scheme of control method with engine controller and active brake controller is presented. From the results of simulation and road tests, it can be concluded that the acceleration performance and stability of a vehicle equipped with traction control system (TCS) can be improved.

The Sliding Mode Control for Traction Control System Based on Variable Optimal Slip Ratio

2013 ◽  
Vol 380-384 ◽  
pp. 485-490
Author(s):  
Jian Zhao ◽  
Jin Zhang ◽  
Bing Zhu
Keyword(s):  
Control System ◽  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Road Surface ◽  
Information Measurement ◽  
Slip Ratio ◽  
Traction Control ◽  
Traction Control System ◽  
Mode Control

In this paper, the concept of intelligent tire and road surface information measurement methods are introduced, and the sliding mode algorithm for traction control system based on intelligent tire is proposed. By applying braking torque onto the driving wheels, the slip rates are adjusted to maintain within the optimal region on different road surface, and the optimal longitudinal traction is achieved. According to the simulation results on the CARSIM and MATLAB co-simulation platform of several working conditions, the TCS based on sliding mode control method improves the traction performance on different road surface effectively.

scholarly journals Design and Analysis of DYC and Torque Vectoring using Multiple-Frequency Control Electronic Differential in an Independent Rear Wheel Driven Electric Vehicle

2019 ◽  
Vol 9 (2) ◽  
pp. 307-315
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Control Method ◽  
Sliding Mode ◽  
Control Strategies ◽  
Frequency Control ◽  
Multiple Frequency ◽  
Traction Control ◽  
Traction Control System ◽  
Torque Vectoring

Electric vehicle (EV) are being embraced in recent times as they run on clean fuel, zero tail emission and are environment-friendly. Recent advancements in the field of power electronics and control strategies have made it possible to the advent in the vehicle dynamics, efficiency and range. This paper presents a design for traction control system (TCS) for longitudinal stability and Direct Yaw Control (DYC) for lateral stability simultaneous. The TCS and DYC is based on multiple frequency controlled electronic differential with a simple and effective approach. Along with it, some overviews have been presented on some state of the art in traction control system (TCS) and torque vectoring. The developed technique reduces nonlinearity, multisensory interfacing complexity and response time of the system. This torque and yaw correction strategy can be implemented alongside fuzzy control, sliding mode or neural network based controller. The effectiveness of the control method has been validated using a lightweight neighbourhood electric vehicle as a test platform. The acquired results confirm the versatility of proposed design and can be implemented in any DC motor based TCS/DYC.

A Novel Traction Control Strategy Based on Optimal Slip Ratio Control for Electric Vehicle

2014 ◽  
Vol 705 ◽  
pp. 355-359
Author(s):  
Ling Fei Wu ◽  
Li Fang Wang ◽  
Jun Zhi Zhang
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Pid Control ◽  
Optimal Point ◽  
Slip Ratio ◽  
Traction Control ◽  
Optimal Slip Ratio ◽  
Simulation Based ◽  
Hardware In Loop ◽  
Driving Torque

A novel traction control strategy based on slip ratio gradient PID control is proposed. The gradient of slip ratio can be controlled accurately through adapting the driving torque by analyzing the dynamic process of the wheel. The optimal slip ratio for traction control is found through the analysis of the characteristic of the tire. The slip ratio of the driving wheels can be control at the optimal point through slip ratio gradient PID control. An electric vehicle model for simulation based on MATLAB/SIMULINK has been built and simulations have been carried out. A hardware-in-loop test bench has been built and experiment has been carried out. Results show that the strategy can achieve better driving performance than motor torque PID control strategy.

scholarly journals Model Predictive Controller-Based Optimal Slip Ratio Control System for Distributed Driver Electric Vehicle

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qingxian Li ◽  
Liangjiang Liu ◽  
Xiaofang Yuan
Keyword(s):  
Control System ◽  
Operation Mode ◽  
Road Surface ◽  
Surface Adhesion ◽  
Model Predictive Controller ◽  
Slip Ratio ◽  
Optimal Slip Ratio ◽  
Road Surfaces ◽  
Predictive Controller ◽  
Matching Degree

The slip ratio control is an important research topic in in-wheel-motored electric vehicles (EVs). Traditional control methods are usually designed for some specified modes. Therefore, the optimal slip ratio control cannot be achieved while vehicles work under various modes. In order to achieve the optimal slip ratio control, a novel model predictive controller-based optimal slip ratio control system (MPC-OSRCS) is proposed. The MPC-OSRCS includes three parts, a road surface adhesion coefficient identifier, an operation mode recognizer, and an MPC based-optimal slip ratio control. The current working road surface is identified by the road surface adhesion coefficient identifier, and a modified recursive Bayes theorem is used to compute the matching degree between current road surfaces and reference road surfaces. The current operation state is recognized by the operation mode recognizer, and a fuzzy logic method is applied to compute the matching degree between actual operation state and reference operation modes. Then, a parallel chaos optimization algorithm (PCOA)-based MPC is used to achieve the optimal control under various operation modes and different road surfaces. The MPC-OSRCS for EV is verified on simulation platform and simulation results under various conditions to show the significant performance.

Sign in / Sign up

Export Citation Format

Share Document