scholarly journals DESIGN OF FUZZY LOGIC CONTROLLER FOR CHARGING SYSTEM WITH TEMPERATURE CONDITION SYSTEM IN EXCAVATOR

2019 ◽  
Vol 1 (1) ◽  
pp. 27-30
Author(s):  
Frendit Wijaya
Keyword(s):  
Fuzzy Logic ◽  
Software Design ◽  
Fuzzy Logic Controller ◽  
Battery Management ◽  
Motor Speed ◽  
Charging System ◽  
Energy Needs ◽  
A Charge ◽  
The Ideal

Batteries have an important role in the development of energy needs. A good battery performance, will support the device it supports. The amount of battery that can be stored is limited, the battery will experience a charge and discharge cycle. One aspect of battery management is how the temperature in the battery is always controlled. This will place the battery always in the ideal temperature so that it can work optimally. The stages in software design consist of designing a fuzzy logic controller that uses Arduino software. To display the results of reading the system, the Serial Monitor is used in the Arduino software. From the data, the response from the control used will be observed. The system is controlled using the Fuzzy Logic Controller method. In this experiment, the input used is the LM35 temperature sensor. This value will affect the speed of the DC motor which in this experiment is regulated through the determination of the PWM value. There are 3 PWM values, namely 100 for slow motor speed, 200 for medium motor speed and 255 for fast motor speed.

Prediction of State of Charge (SOC) of Battery Electric Vehicle

2021 ◽  
Vol 104 ◽  
pp. 65-71
Author(s):  
Illa Rizianiza ◽  
Dian Mart Shoodiqin
Keyword(s):  
Fuzzy Logic ◽  
Maximum Energy ◽  
State Of Charge ◽  
Battery Management ◽  
Charge Condition ◽  
Available Energy ◽  
Energy Needs ◽  
Fuzzy Logic Method ◽  
Input Variables ◽  
Charging And Discharging Processes

Batteries have an important thing in development of energy needs. A good performance battery, will support the device it supports. The energy that can save a battery is limited, so the battery will increase its charge and discharge cycles. Incorrect charging and discharging processes can cause battery performance to decrease. Therefore battery management is needed so that the battery can reach the maximum. One aspect of battery management is setting the state which is the ratio of available energy capacitance to maximum energy capacity. One method for estimating load states is the fuzzy logic method, namely by assessing the input and output systems of prediction. Predictor of State of Charge use Mamdani Fuzzy Logic that have temperature and voltage as input variables and State of Charge as output variable. A result of prediction State of Charge battery is represented by the number of Root Mean Square Error. Battery in charge condition has 2.7 for RMSE and level of accuracy 81.5%. Whereas Battery in discharge condition has RMSE 1.5 and level of accuracy 84.7%.

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 An intelligent lead-acid battery closed-loop charger using a combined fuzzy controller for PV applications

2021 ◽  
Vol 297 ◽  
pp. 01033
Author(s):  
Iliass Rkik ◽  
Mohamed El khayat ◽  
Hafsa Hamidane ◽  
Abdelali Ed-Dahhak ◽  
Mohammed Guerbaoui ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control Unit ◽  
Buck Converter ◽  
Lead Acid Battery ◽  
Charging System ◽  
Pv Array ◽  
Full Power ◽  
Lead Acid

This paper presents the modeling of an intelligent combined MPPT and Lead-Acid battery charger controller for standalone solar photovoltaic systems. It involves the control of a DC/DC buck converter through a control unit, which contains two cascaded fuzzy logic controllers (FLC), that adjusts the required duty cycle of the converter according to the state of charge and the three stage lead acid battery charging system. The first fuzzy logic controller (FLC1) consists of an MPPT controller to extract the maximum power produced by the PV array, while the second fuzzy controller (FLC2) is aimed to control the voltage across the battery to ensure the three stage charging approach. This solution of employing two distinct cascaded fuzzy controllers surmounts the drawbacks of the classical chargers in which the voltage provided to the lead acid battery is not constant owing to the effects of the MPPT control which can automatically damage the battery. Thus, the suggested control strategy has the benefit of extracting the full power against the PV array, avoiding battery damage incurred by variable MPPT voltage and increasing the battery’s lifespan.

scholarly journals Electric Drive Control with Rotor Resistance and Rotor Speed Observers Based on Fuzzy Logic

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
C. Ben Regaya ◽  
A. Zaafouri ◽  
A. Chaari
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Simple Algorithm ◽  
Simultaneous Estimation ◽  
Rotor Speed ◽  
Motor Speed ◽  
Speed Sensor ◽  
Rotor Resistance ◽  
Drive Control

Many scientific researchers have proposed the control of the induction motor without speed sensor. These methods have the disadvantage that the variation of the rotor resistance causes an error of estimating the motor speed. Thus, simultaneous estimation of the rotor resistance and the motor speed is required. In this paper, a scheme for estimating simultaneously the rotor resistance and the rotor speed of an induction motor using fuzzy logic has been developed. We present a method which is based on two adaptive observers using fuzzy logic without affecting each other and a simple algorithm in order to facilitate the determination of the optimal values of the controller gains. The control algorithm is proved by the simulation tests. The results analysis shows the characteristic robustness of the two observers of the proposed method even in the case of variation of the rotor resistance.

scholarly journals Optimal Tuning of Fuzzy Logic Controller Based Speed Control of DC Motor

2021 ◽  
Vol 19 (1) ◽  
pp. 77-80
Author(s):  
Mohsin A. Koondhar ◽  
Muhammad U. Keerio ◽  
Rameez A. Talani ◽  
Kamran A. Samo ◽  
Muhammad S. Bajwa ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Dc Motors ◽  
Manual Adjustment ◽  
Control Application ◽  
Installation Time ◽  
Transient And Steady State

Fuzzy logic controller (FLC) has become popular in the speed control application of DC motors with automatic adjustment function. In this article, the performance of a specific FLC controlled DC motor is studied. The exceed speed is observed with a stabilization time, thus confirming the FLC behavior. Therefore, FLC must be set to obtain the required performance by applying appropriate expert rules, the minimum overshoot and installation time can be maintained within the required values. With the help of FLC, the manual adjustment function is gradually eliminated, and the intelligent adjustment function is at the center position, and the performance is satisfactory. FLC DC motor speed control is implemented in MATLAB environment. The results show that the FLC method has the smallest bypass, smallest transient and steady-state error, and shows higher FLC efficiency as compared with other conventional controllers.

scholarly journals Simple Implementation of a Fuzzy Logic Speed Controller for a PMDC Motor with a Low Cost Arduino Mega

2020 ◽  
Vol 10 (2) ◽  
pp. 5419-5422
Author(s):  
K. S. Belkhir
Keyword(s):  
Fuzzy Logic ◽  
Flash Memory ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Computation Time ◽  
Motor Speed ◽  
Speed Controller ◽  
Simple Implementation ◽  
Speed Mode ◽  
Transient And Steady State

Control of the permanent magnetic direct current PMDC motor is a common practice, hence the importance of the implementation of the PMDC motor speed controller. The results of a fuzzy logic speed controller for the PMDC motor rely on an appropriate base. As the dimension of the rules increases, its difficulty rises which affects computation time and memory requirements. Fuzzy Logic Controller (FLC) can be carried out by a low-cost Arduino Mega which has a small flash memory and a maximum clock speed of 16MHz. It is realized by three membership functions and each was divided into three memberships. The results of the FLC are satisfactory, revealing superior transient and steady-state performance. In addition, the controller is robust to speed mode variations.

scholarly journals Low Voltage Battery Management System with Internal Adaptive Charger and Fuzzy Logic Controller

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2221
Author(s):  
Omer Faruk Goksu ◽  
Ahmet Yigit Arabul ◽  
Revna Acar Vural
Keyword(s):  
Fuzzy Logic ◽  
Management System ◽  
Fuzzy Logic Controller ◽  
Low Voltage ◽  
Lithium Ion ◽  
Discharge Voltage ◽  
System Control ◽  
Battery Management System ◽  
Battery Management ◽  
Battery Cells

Lithium ion (Li-Ion) and lithium polymer (Li-Po) batteries need to be used within certain voltage/current limits. Failure to observe these limits may result in damage to the battery. In this work, we propose a low voltage battery management system (LV-BMS) that balances the processes of the battery cells in the battery pack and the activating-deactivating of cells by guaranteeing that the operation is within these limits. The system operates autonomously and provides energy from the internal battery. It has a modular structure and the software is designed to control the charging and discharging of eight battery cells at most. A STM32F103 microcontroller is used for system control. The fuzzy logic controller (FLC) is used to set the discharge voltage limit to prevent damage to the battery cells, shorten the settlement time and create a specialized design for charge control. The proposed structure enables solar panel or power supplies with different voltage values between 5 V and 8 V to be used for charging. The experimental results show there was a 42% increase in usage time and the voltage difference between the batteries was limited to a maximum of 65 mV. Moreover, the charge current settles at about 20 ms, which is a much faster response when compared to a PID controller.

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