Anti Slippage Traction Control System based on Fuzzy Control to Improve Longitudinal Dynamic Performance

2011 ◽  
Author(s):  
Mohammad S. Ghafouri ◽  
Kourosh H. Shirazi ◽  
Amir Riahi
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Dynamic Performance ◽  
Traction Control ◽  
Traction Control System ◽  
Longitudinal Dynamic

Research on Control Strategy of Traction Control for Four Wheel Drive Vehicle

2011 ◽  
Vol 230-232 ◽  
pp. 1242-1249
Author(s):  
Jian Jun Hu ◽  
Zheng Bin He ◽  
Peng Ge ◽  
Da Tong Qin
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Structural Characteristics ◽  
Dynamic Performance ◽  
Synthetic Control ◽  
Traction Control ◽  
Torque Distribution ◽  
Traction Control System ◽  
Wheel Drive ◽  
Four Wheel Drive

In order to improve the performance of four wheel driver vehicle, structural characteristics of inter-axle torque distribution with planetary gear are analyzed, and a dynamic model of four wheel drive vehicle is established. A synthetic control strategy was proposed to achieve the engine throttle control, inter-axle torque distribution control and drive wheel brake control. Traction control system based on fuzzy logic control is designed. The simulation of traction control on split-µ road and low-µ road are carried out. The results show that, the traction control system for four wheel drive vehicle based on fuzzy control can prevent excessive slip of driving wheels, and vehicle traction property and dynamic performance are improved obviously.

Design and Simulation of Temperature Control System in Intermittent Reaction Kettles Based on Intelligent Fuzzy Control

2013 ◽  
Vol 380-384 ◽  
pp. 294-297 ◽  
Author(s):  
Xin Wei Li
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Pid Control ◽  
Elevated Temperatures ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Temperature Curve ◽  
Time Variable ◽  
Temperature Control System ◽  
New Type

A temperature rising control system and temperature maintaining control system were designed in according to time-variable and hysteretic nature of temperature change and limitation when traditional PID control deals with nonlinear systems. A new type of intelligent fuzzy controller combination of traditional PID control and fuzzy control was designed and applied in temperature maintaining control system. The simulation results show that the holding phase at elevated temperatures and temperature, the temperature curve has a high steady-state accuracy and dynamic performance in the period of temperature rising and maintaining, and the system and controller cause a better result.

Development of Active-Traction Control System

2000 ◽  
Author(s):  
Kazushi Hosomi ◽  
Akira Nagae ◽  
Shinsuke Yamamoto ◽  
Yosuke Takahira ◽  
Masamichi Koizumi ◽  
...  
Keyword(s):  
Control System ◽  
Traction Control ◽  
Traction Control System

Conceptual Design and Simulation of the Traction Control System of a High Performance Electric Vehicle

2013 ◽  
Author(s):  
Juan Sebastián Núñez ◽  
Luis Ernesto Muñoz
Keyword(s):  
Control System ◽  
Electric Vehicle ◽  
Conceptual Design ◽  
High Performance ◽  
Control Strategies ◽  
Traction Force ◽  
Traction Control ◽  
The Road ◽  
Traction Control System ◽  
Low Discrepancy Sequences

This paper presents the conceptual design of the traction control system of a high performance electric vehicle with four driven wheels, intended to be used in quarter mile competitions. Different models of the longitudinal and vertical vehicle’s dynamics are presented, in order to consider the coupling dynamics of front and rear wheels. Two slip control strategies are proposed so as to maximize the traction forces of the wheels. The first one consists of a traditional control scheme applied to each wheel of the vehicle. Since the interaction between the tire and the road is often poorly known, the second controller proposed consists of a perturbation based extremum seeking control (PBESC), in order to maximize the traction force without knowledge of the road and the tire characteristics. Finally an auto tuning process based on low discrepancy sequences for both control systems is presented.

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