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Induction Machine-Based EV Vector Control Model Using Mamdani Fuzzy Logic Controller

delete2022-05-05
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OA
AI
H
Humayun Salahuddin
K
Kashif Imdad
M
Muhammad Umar Chaudhry *
D
Dmitry Nazarenko
V
Vadim Bolshev *
M
Muhammad Yasir
DOI:10.3390/app12094647delete
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Abstract

Abstract

En 中文
The substantial rise in the demand for electric vehicles (EVs) has emphasized an environment-friendly and intelligent design for speed control strategies. In this paper, a Mamdani fuzzy logic controller (MFLC) was proposed to vigorously control the speed of EVs at discrete levels. MFLC member functions (MFs) are tuned for EVs operating at three different speed modes (40, 60, and 80 km/h). The proposed speed controller operation for the speed tracking of EVs was designed and tested in MATLAB (Simulink) environment. The proposed speed controller validated a remarkable improvement in dynamic speed control compared with existing P-I, FLC, Fuzzy FOPID (ACO), Fuzzy FOPID (GA), and Fuzzy FOPID (PSO) controllers. Its stability under a user-defined drive pattern is also observed. In this proposed work, the speed controller highlights the better tracking of user-defined speed response compared to the conventional aforementioned controllers. Moreover, the speed tracking of the designed model was tested for robustness against speed transients at predefined time instants, respectively. The comparison suggests that the MFLC model removes overshoot and significantly reduces the steady-state time.
Keywords:
induction machine
Mamdani fuzzy logic controller
proportional-integral
integrated gate bipolar transistor
inductance
electromagnetic torque
flux
membership function

Journal

A
Applied Sciences Basel
IF:
2.5
Papers:
1.9K
Citations:
15.9W

Organization

HITEC University cover
HITEC University
Scholars:
295
Papers: 336
Citations: 345
F
Federal Scientific Agroengineering Center VIM
Scholars:
224
Papers: 116
Citations: 88
D
don state technical university
Scholars:
635
Papers: 370
Citations: 3
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