Journal of Applied Science and Engineering

Published by Tamkang University Press

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M. Yerri Veeresh1This email address is being protected from spambots. You need JavaScript enabled to view it., V. Naga Bhaskar Reddy2, and R. Kiranmayi3

1Department of E.E.E., JNTU Anantapur and Santhiram Engineering College, A.P, India.

2Department of E.E.E., RGMCET, Nandyal, A.P, India.

3Department of EE, JNTU Anantapur, Ananthapuramu, A.P, India.


 

Received: May 2, 2023
Accepted: August 3, 2023
Publication Date: November 8, 2023

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202407_27(7).0015  


Internal combustion engine (ICE) vehicles often exhibit quicker acceleration and a faster response to reach maximum speed than electric vehicles (EVs). The EVs can overcome this limitation with highly efficient motors and optimized control systems. This work proposes a speed control strategy for field-oriented control (FOC) PMSM-based battery electric vehicles (BEV) using a fuzzy logic controller (FLC) to attain quick acceleration and smooth steady-state operation. A minimal set of fuzzy rules is framed to achieve precise speed control of the PMSM propulsion system. A mathematical model is established in MATLAB-Simulink to emulate a BEV with a battery-driven PMSM propulsion system and a single-gear transmission to the wheels, including vehicle dynamics. The performance of this system is comprehensively evaluated during transient and steady-state conditions, focusing on parameters such as rise time, settling time, and steady-state error in operating speed and torque characteristics of the PMSM-BEV. Furthermore, the acceleration of the BEV at the wheels is assessed in terms of the time required to reach its maximum speed, typically 100 kilometers per hour. The results of the simulations are contrasted with conventional P.I. and P.I.D. controllers. The findings from these results validate that the minimal fuzzy rulesbased BEV is more resilient than P.I. and P.I.D. counterparts for quick acceleration and smooth steady-state operation, which is more suitable for electric automobiles.


Keywords: Electric Vehicle (E.V.), Fuzzy Logic Controller (FLC), Proportional plus Integral (P.I.) Controller, Proportional plus Integral plus Derivative (P.I.D.) Controller.


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