scholarly journals Power Supply Management for an Electric Vehicle Using Fuzzy Logic

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yolanda Pérez-Pimentel ◽  
Ismael Osuna-Galán ◽  
Carlos Avilés-Cruz ◽  
Juan Villegas-Cortez
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Electric Vehicle ◽  
Power Supply ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Supply Management ◽  
Experimental Result ◽  
Mechatronic Systems ◽  
Battery Bank

The technology of power electronic systems has diversified into industrial, commercial, and residential areas. Developing a strategy to improve the performance of the electrical energy of an electric vehicle (EV) requires an analysis of the model that describes it. EVs are complex mechatronic systems described by nonlinear models and, therefore, its study is not an easy task. It can improve the performance of a battery bank by creating new batteries that allow for greater storage or by developing a management energy system. This article shows the development of a power supply management system based on fuzzy logic for an electric vehicle, in order to minimize the total energy consumption and optimize the battery bank. The experimental result is shown using the fuzzy controller under standard operating conditions. An increase in battery performance and overall performance of energy consumption is shown. Speed signals acquired show improvements in some dynamic, such as overshoot, settling time, and steady-state error parameters. It is shown that this fuzzy controller increases the overall energy efficiency of the vehicle.

Probabilistic and Fuzzy based Efficient Routing Protocol for Mobile Ad Hoc Networks

2020 ◽  
Vol 13 (3) ◽  
pp. 422-432
Author(s):  
Madan Mohan Agarwal ◽  
Hemraj Saini ◽  
Mahesh Chandra Govil
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Routing Protocol ◽  
Queue Length ◽  
Ad Hoc ◽  
Fuzzy Controller ◽  
Second Phase ◽  
Path Distance ◽  
Fixed Threshold ◽  
Multiple Paths

Background: The performance of the network protocol depends on number of parameters like re-broadcast probability, mobility, the distance between source and destination, hop count, queue length and residual energy, etc. Objective: In this paper, a new energy efficient routing protocol IAOMDV-PF is developed based on the fixed threshold re-broadcast probability determination and best route selection using fuzzy logic from multiple routes. Methods: In the first phase, the proposed protocol determines fixed threshold rebroadcast probability. It is used for discovering multiple paths between the source and the destination. The threshold probability at each node decides the rebroadcasting of received control packets to its neighbors thereby reducing routing overheads and energy consumption. The multiple paths list received from the first phase and supply to the second phase that is the fuzzy controller selects the best path. This fuzzy controller has been named as Fuzzy Best Route Selector (FBRS). FBRS determines the best path based on function of queue length, the distance between nodes and mobility of nodes. Results: Comparative analysis of the proposed protocol named as "Improved Ad-Hoc On-demand Multiple Path Distance Vector based on Probabilistic and Fuzzy logic" (IAOMDV-PF) shows that it is more efficient in terms of overheads and energy consumption. Conclusion: The proposed protocol reduced energy consumption by about 61%, 58% and 30% with respect to FF-AOMDV, IAOMDV-F and FPAOMDV routing protocols, respectively. The proposed protocol has been simulated and analyzed by using NS-2.

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2001 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines

Abstract Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them became difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control preferable. In this work a fuzzy logic controller is introduced with the idea of split-horizon; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FTEs). Computer simulations are used to verify the performance of the controller. Three simulation cases are introduced: radial, compound, and damping. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing them in a relatively reasonable time.

Hybrid Anti-Windup Fuzzy PI Controller Based Direct Torque Control of Three Phase Induction Motor

2014 ◽  
Vol 573 ◽  
pp. 155-160
Author(s):  
A. Pandian ◽  
R. Dhanasekaran
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Direct Torque Control ◽  
Operating Conditions ◽  
Torque Control ◽  
Constant Speed ◽  
Three Phase

This paper presents improved Fuzzy Logic Controller (FLC) of the Direct Torque Control (DTC) of Three-Phase Induction Motor (IM) for high performance and torque control industrial drive applications. The performance of the IM using PI Controllers and general fuzzy controllers are meager level under load disturbances and transient conditions. The FLC is extended to have a less computational burden which makes it suitable for real time implementation particularly at constant speed and torque disturbance operating conditions. Hybrid control has advantage of integrating a superiority of two or more control techniques for better control performances. A fuzzy controller offers better speed responses for startup and large speed errors. If the nature of the load torque is varied, the steady state speed error of DTC based IM drive with fuzzy logic controller becomes significant. To improve the performance of the system, a new control method, Hybrid fuzzy PI control is proposed. The effectiveness of proposed method is verified by simulation based on MATLAB. The proposed Hybrid fuzzy controller has adaptive control over load toque variation and can maintain constant speed.

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.

scholarly journals Control of Rotary Cranes Using Fuzzy Logic

2003 ◽  
Vol 10 (2) ◽  
pp. 81-95 ◽  
Author(s):  
Amjed A. Al-mousa ◽  
Ali H. Nayfeh ◽  
Pushkin Kachroo
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Building Construction ◽  
Loop Control ◽  
Industrial Structures ◽  
Inference Engines ◽  
First Case

Rotary cranes (tower cranes) are common industrial structures that are used in building construction, factories, and harbors. These cranes are usually operated manually. With the size of these cranes becoming larger and the motion expected to be faster, the process of controlling them has become difficult without using automatic control methods. In general, the movement of cranes has no prescribed path. Cranes have to be run under different operating conditions, which makes closed-loop control attractive.In this work a fuzzy logic controller is introduced with the idea of “split-horizon”; that is, fuzzy inference engines (FIE) are used for tracking the position and others are used for damping the load oscillations. The controller consists of two independent sub-controllers: radial and rotational. Each of these controllers has two fuzzy inference engines (FIE). Computer simulations are used to verify the performance of the controller. Three simulation cases are presented. In the first case, the crane is operated in the gantry (radial) mode in which the trolley moves along the jib while the jib is fixed. In the second case (rotary mode), the trolley moves along the jib and the jib rotates. In the third case, the trolley and jib are fixed while the load is given an initial disturbance. The results from the simulations show that the fuzzy controller is capable of keeping the load-oscillation angles small throughout the maneuvers while completing the maneuvers in relatively reasonable times.

Modeling of Electric Vehicle Air Conditioning System and Analysis of Energy Consumption

2012 ◽  
Vol 516-517 ◽  
pp. 1164-1170 ◽  
Author(s):  
Jin Rui Nan ◽  
Yao Wang ◽  
Zhi Chai ◽  
Jun Kui Huang
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Air Conditioning ◽  
Control Method ◽  
Air Conditioning System ◽  
Logic Control ◽  
Ac Motor ◽  
Total Vehicle

An simulation model for pure electric vehicle air conditioning system is established in MATLAB/ Simulink environment. The critical component of air conditioning system is selected and simulated. Fuzzy logic control method is used in AC motor controlling strategy. Combined with ADVISOR, the total vehicle energy consumption and AC energy consumption are simulated and calculated. The research indicate that by using Fuzzy logic control led AC system, the vehicle’s economcial effeciency improved. Life mileage is longer than the EV with traditional AC system and a better effect of energy saving is achieved.

Designing Gear-Shift Pattern for an Electric Vehicle to Optimize Energy Consumption

2010 ◽  
Author(s):  
Mohammad A. Rahimi ◽  
Rasoul Salehi ◽  
Aria Alasty
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Fuzzy Controller ◽  
Main Idea ◽  
Fuzzy Rules ◽  
Average Speed ◽  
Gear Shift ◽  
Driving Cycles ◽  
Shift Pattern ◽  
The City

In this paper optimization of energy consumption in an electric vehicle is presented. The main idea of this optimization is based on selecting the best gear level in driving the vehicle. Two algorithms for optimization are introduced which are based on fuzzy rules and fuzzy controllers. In first algorithm, fuzzy controller simulates energy consumption in different gear levels, and chooses the optimum gear level. While in second method, fuzzy controller detects the optimum gear level by measuring the vehicle’s average speed and acceleration. To investigate the performance of these controllers, a model of TOSAN vehicle is developed and the controllers outputs are checked in simulation of TOSAN being driven within drive cycles in the city of Tehran. It is shown that both algorithms are able to improve efficiency in typical city driving cycles.

Anti-Swing Adaptive Fuzzy Controller for an Overhead Crane With Hoisting

2004 ◽  
Author(s):  
Jamil M. Renno ◽  
Mohamed B. Trabia ◽  
Kamal A. F. Moustafa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Overhead Crane ◽  
Fuzzy Logic Controllers ◽  
Adaptive Fuzzy Controller ◽  
Overhead Cranes ◽  
Logic Control ◽  
Novel Method

This paper presents a novel method for adaptive anti-swing fuzzy logic control for overhead cranes with hoisting. The control action is distributed between three fuzzy logic controllers (FLC’s): trolley controller, hoist controller, and anti-swing controller. A method for varying the ranges of the variables of the three controllers as a function of the crane’s parameters and/or motion variables is presented. Simulation examples show that the proposed controller can successfully drive overhead cranes under various operating conditions.

SIMULATION OF THE PROCESS OF MONITORING IN THE DISTRIBUTION ELECTRIC NETWORK AND CONTROL OF THE OPERATION OF THE ADAPTIVE POWER SUPPLY MODULE OF THE CONSUMER BASED ON FUZZY LOGIC

2021 ◽  
pp. 52-56
Author(s):  
Ю.А. Клименко ◽  
А.П. Преображенский
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Power Supply ◽  
System Analysis ◽  
Electrical Networks ◽  
Electric Network ◽  
Optimal State ◽  
Adaptive Power ◽  
And Control

В работе рассматривается возможность проведения системного анализа для мониторинга и управления энергопотреблением в распределительных электрических сетях на основе применения методов нечёткой логики для моделирования оптимального состояния электрических сетей в точках присоединения потребителей к сети. The paper considers the possibility of conducting a system analysis for monitoring and managing energy consumption in distribution electrical networks based on the use of fuzzy logic methods for modeling the optimal state of electrical networks at the points of connection of consumers to the network.

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