Scopus
YÖKSİS DOI Eşleşti
SJR Q2
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
International Journal of Fuzzy Systems · Ekim 2023
YÖKSİS Kayıtları
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
International Journal of Fuzzy Systems · 2023 SCI-Expanded
Doç. Dr. ALİ YAŞAR →
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
International Journal of Fuzzy Systems · 2023 SCI-Expanded
Doç. Dr. ALİ YAŞAR →
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
International Journal of Fuzzy Systems · 2023 SCI-Expanded
Prof. Dr. İSMAİL SARITAŞ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
A Decentralized Model for Allied Closed Loop Supply Chains Comparative Analysis of Interactive Fuzzy Programming Approaches
2017 ISSN: 1562-2479 SCI-Expanded
Prof. Dr. NİMET YAPICI PEHLİVAN →
Novel Hamacher Aggregation Operators Based on Complex T-Spherical Fuzzy Numbers for Cleaner Production Evaluation in Gold Mines
2022 ISSN: 1562-2479 SCI-Expanded Q2
Prof. Dr. NİMET YAPICI PEHLİVAN →
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
2023 ISSN: 1562-2479 SCI-Expanded Q2
Doç. Dr. ALİ YAŞAR →
Regenerative Braking Control of Brushless DC Motors with Type 2 Fuzzy Logic Controller
2023 ISSN: 1562-2479 SCI-Expanded Q2
Prof. Dr. İSMAİL SARITAŞ →
Makale Bilgileri
ISSN15622479
Yayın TarihiEkim 2023
Cilt / Sayfa25 · 2722-2732
Scopus ID2-s2.0-85161636048
Özet
The aim of this study is to model the brushless direct current motors and regenerative braking system used in electric vehicles using intelligent control approaches. Type-2 fuzzy logic control model is used as an intelligent control method. The application of regenerative braking extends the driving range of electric vehicles. In this study, an innovative regenerative braking system is presented. Speed control of brushless direct current motor and control of regenerative braking system are provided by Type-2 fuzzy logic control. Type-2 fuzzy logic control outperforms other solutions in terms of modeling uncertainties, generating new solutions, robustness, and efficiency. Type-2 fuzzy logic control is built on Matlab/M-file platform. The simulation in which the experimental studies were carried out was created on the MATLAB/Simulink platform. With this simulation study, battery charge status, battery current and brushless direct current motor speed values were obtained. The simulation results show that Type-2 fuzzy logic control can effectively control regenerative braking system. The regenerative braking system maintains its braking quality, while the electric vehicle slows it down at a safe driving distance. In addition, it is clearly seen in the results that the brushless direct current motor in the electric vehicle can increase the driving distance by charging the vehicle battery, thanks to its use as an alternator during braking.
Yazarlar (3)
1
Yusuf Karabacak
ORCID: 0000-0001-9864-7512
2
Ali Yasar
3
Ismail Saritas
Anahtar Kelimeler
BLDC motor
Electric vehicles
Regenerative braking system
Type-2 fuzzy logic control
Kurumlar
Milli Savunma Üniversitesi
Istanbul Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
International Journal of Fuzzy Systems
Q2
SJR Skoru0,668
H-Index72
YayıncıSpringer International Publishing AG
ÜlkeSwitzerland
Artificial Intelligence (Q2)
Computational Theory and Mathematics (Q2)
Control and Systems Engineering (Q2)
Information Systems (Q2)
Software (Q2)
Theoretical Computer Science (Q2)
Metrikler
11
Atıf
3
Yazar
4
Anahtar Kelime