scholarly journals Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guodong Yin ◽  
Shanbao Wang ◽  
Xianjian Jin
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Angular Acceleration ◽  
Slip Rate ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Logic Control

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.

Applying fuzzy logic control to analyze real-time control for charging and discharging power of electric vehicles

2021 ◽  
pp. 1-7
Author(s):  
Feng Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Power Grid ◽  
Regional Distribution ◽  
Real Time Control ◽  
Time Control ◽  
Logic Control

The disorderly charging of large-scale electric vehicles will aggravate the peak-valley difference of the power grid, and affect the power quality and life of the transformer. The fuzzy logic control strategy for charging and discharging optimization of charging vehicles under the framework of fuzzy logic control from the perspective of the group is considered in this article. A real-time control method based on the clustering characteristics of the charging end time is proposed according to the different charging requirements of the connected electric vehicles and fuzzy logic control is adopted to solve the problem of optimal charging and discharging power of the entire cluster and a single electric vehicle. A fuzzy logic control model considering the charging and discharging of electric vehicles is established orienting at minimize daily load fluctuations and control penalties in the upper layer. The charging and discharging cost of electric vehicle owners is considered to solve the optimal control problem of the charging and discharging power of a single electric vehicle. Taking the data of the typical regional distribution network load as an example, it is verified that the real-time charging optimization strategy under fuzzy logic control through simulation can ensure the reliable operation of the power grid while considering the interests of all parties.

scholarly journals Energy Management of Parallel-Connected Cells in Electric Vehicles Based on Fuzzy Logic Control

Energies ◽  
2017 ◽  
Vol 10 (3) ◽  
pp. 404 ◽  
Author(s):  
Chuanxue Song ◽  
Yulong Shao ◽  
Shixin Song ◽  
Cheng Chang ◽  
Fang Zhou ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Logic Control

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.

Decentralized Fuzzy Logic Control of Microgrid for Electric Vehicle Charging Station

2018 ◽  
Vol 6 (2) ◽  
pp. 726-737 ◽  
Author(s):  
Pablo Garcia-Trivino ◽  
Juan P. Torreglosa ◽  
Luis M. Fernandez-Ramirez ◽  
Francisco Jurado
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Logic Control ◽  
Vehicle Charging

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

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