Design of an Integrated AFS/ACD Control System to Enhance 4WD Vehicles Dynamics and Stability

2010 ◽  
Author(s):  
Avesta Goodarzi ◽  
Samaneh Arabi ◽  
Ebrahim Esmailzadeh
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Traction Force ◽  
Slip Angle ◽  
Force Distribution ◽  
Vehicle Stability ◽  
Handling Performance ◽  
Yaw Rate ◽  
The Ideal

An integrated vehicle dynamic control system for a four-wheel drive vehicle with an active front steering (AFS) and active centre differential (ACD), based on fuzzy logic control, is developed to improve the vehicle stability and its handling performance. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer to keep the yaw rate in its desired value. The yaw rate error and the side slip angle are applied to the upper controlling layer as the inputs, where the desired traction torque transfer ratio and the steering angle correction of the front wheels are the outputs. However, the ideal control effectors could not directly be the control inputs for the centre differential. Therefore, in the lower control loop, one should map the ideal control effectors to the physical control inputs for the centre differential by optimum dynamic traction force distribution. A nonlinear eight degree-of-freedom (DOF) vehicle model with the traction force distribution being utilized by a PI controller is considered. The simulation results illustrate considerable improvements have been achieved for the vehicle stability and handling performance through the integrated AFS/ACD control system.

A Torque Vectoring Control System for Maneuverability Improvement of 4WD EV

2013 ◽  
Vol 347-350 ◽  
pp. 899-903
Author(s):  
Yi He Gan ◽  
Lu Xiong ◽  
Yuan Feng ◽  
Felix Martinez
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Lower Layer ◽  
Lateral Acceleration ◽  
Slip Angle ◽  
Torque Distribution ◽  
Handling Performance ◽  
Yaw Rate ◽  
Model Following ◽  
Torque Vectoring

This paper studies the improvement of the handling performance of 4WD EV driven by in-wheel motors under regular driving conditions. Fundamentally the structure of torque vectoring control (TVC) system for handling control consists of two control layers. The upper layer is a model following controller which makes the vehicle follow the desired yaw rate limited by the side slip angle and lateral acceleration. The torque distribution constitutes the lower layer. Several simulations based on veDYNA/Simulink are conducted to verify the effectiveness of the control system. It is clarified that the control system exhibits satisfactory performance in both open and closed loop maneuvers and the agility of the electric vehicle is improved.

scholarly journals Control of Yaw Disturbance Using Fuzzy Logic Based Yaw Stability Controller

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
S. Krishna ◽  
S. Narayanan ◽  
S. Denis Ashok
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Degrees Of Freedom ◽  
Slip Angle ◽  
Steering Angle ◽  
Side Slip Angle ◽  
Yaw Rate ◽  
Steer By Wire ◽  
Yaw Stability ◽  
Wire System

Yaw stability is an important consideration for the vehicle directional stability and handling behavior during emergency maneuvers. In order to maintain the desired path of the vehicle, in presence of disturbances due to cross wind, different road conditions, and tire deflections, a fuzzy logic based yaw stability controller is proposed in this paper. Proposed control system receives yaw rate error, steering angle given by the driver, and side slip angle as inputs, for calculating the additional steering angle as output, for maintaining the yaw stability of the vehicle. As the side slip angle cannot be measured directly in a vehicle, it was estimated using a model based Kalman observer. A two-degrees-of-freedom vehicle model is considered in the present work. The effect of disturbance on yaw rate and yaw rate error of the vehicle is simulated for sinusoidal, step maneuver and compared with the existing fuzzy control system which uses two inputs such as steering angle and yaw rate. The simulation results show better performance of the proposed fuzzy based yaw controller as compared with existing control system. Proposed fuzzy based yaw stability controller can be implemented in steer-by-wire system for an active front steering of a road vehicle.

Design of Direct Yaw Moment Control System to Enhance Vehicle Stability Based on Fuzzy Logic

2011 ◽  
Vol 383-390 ◽  
pp. 1326-1332 ◽  
Author(s):  
Zhe Xu ◽  
Min Xiang Wei ◽  
Yang Wang ◽  
Jian Wei Wei
Keyword(s):  
Control System ◽  
High Speed ◽  
Control Method ◽  
Reference Value ◽  
Stability Control ◽  
Slip Angle ◽  
Vehicle Stability ◽  
Handling Performance ◽  
Model Following Control ◽  
Yaw Moment

Vehicle running at high speed if affected by crosswind or steering handling may spin or drift out since the yaw moment produced is not big enough to stabilize it. In order to prevent these dangerous situations, a fuzzy direct yaw moment controller is designed in this paper, since it is simple and suitable for nonlinear system. This vehicle stability control system is based on model following control method. The side slip angle and yaw rate which indicate the vehicle’s stability and handling performance are chosen as the control variables. The response of the bicycle model is selected as the reference value. In order to evaluate the performance of the controller, simulations of lane change and J-turn maneuver are carried out. The results show that the stability and handling performance of the vehicle are improved.

scholarly journals RESEARCH OF LIQUID LEVEL CONTROL SYSTEM / SKYSČIO LYGIO VALDYMO SISTEMOS TYRIMAS

2015 ◽  
Vol 7 (3) ◽  
pp. 317-322
Author(s):  
Dominykas Beištaras
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Liquid Level ◽  
Water Tank ◽  
Level Control ◽  
Level Control System ◽  
Filling Time ◽  
Control System Model ◽  
Liquid Level Control

This paper presents liquid level control system model and analysis of dynamic characteristics. The system consists of scalar controlled induction motor drive, fuzzy logic controller, water tank and centrifugal pump. Simulink models of water tank, pump and controller are presented. The simulation of the system shows that the use of fuzzy logic controller reduces valve opening time and reservoir filling time. Nagrinėjamas skysčio lygio valdymo sistemos imitacinių modelių sudarymas, analizuojamos dinaminės charakteristikos. Valdymo sistema sudaryta iš skaliariniu būdu valdomos dažninės elektros pavaros su neraiškiosios logikos reguliatoriumi, vandens rezervuaro ir išcentrinio siurblio. Sudaryti rezervuaro, siurblio ir reguliatoriaus Simulink modeliai. Atlikus imitacijas gauta nedimensinė siurblio charakteristika, apibūdinanti siurblio veikimą, esant bet kokiam sukimosi greičiui. Nustatyta, kad sistemoje su neraiškiosios logikos reguliatoriumi vožtuvas yra atidaromas greičiau nei sistemoje su proporcinguoju integraliniu (PI) reguliatoriumi, ir todėl sumažinama rezervuaro pripildymo trukmė.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

scholarly journals Online Position Control Performance Improving Applying Incremental Fuzzy Logic Controller

2018 ◽  
Vol 248 ◽  
pp. 02005
Author(s):  
Dirman Hanafi ◽  
Mohamed Najib Ribuan ◽  
Wan HamidahWan Abas ◽  
Hidayat ◽  
Elmy Johana ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Motor Performance ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Peak Time ◽  
Control Performance ◽  
Position Control System

This paper presents the online control system application for improving the DC motor performance. DC motor widely used in industries and many appliances. For this aim fuzzy logic controller is applied. The type of fuzzy controller use is an incremental fuzzy logic controller (IFLC). The IFLC is developed by using MATLAB Simulink Software and implemented in online position control system applying RAPCON board as a platform. The experimental results produced the best gains of the IFLC are 1.785, 0.0056955 and 0.01 for error gain (GE), gain of change error (GCE) and gain of output (GCU) respectively. Its produce smaller rise time, peak time, 0% overshoot and smaller settling time. Beside that the IFLC response also able to follow the set point. The controller response parameters values are also acceptable. It means that the IFLC suitable to be use for improving the position control system performance.

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