UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Volume 11 | Issue 11 | November 2024

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Published in:

Volume 11 Issue 10
October-2024
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2410478


Registration ID:
544373

Page Number

e720-e726

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Title

Novel Approach of GA based PID controller design for Speed and Direction Control of Electric Vehicle

Abstract

Electric Vehicles (EVs) are pivotal in addressing global challenges related to environmental sustainability and energy efficiency. Among various motor types, Brushless DC (BLDC) motors are favored in EV applications due to their high efficiency, reliability, and power density. Achieving precise speed and direction control of BLDC motors is crucial for the optimal performance of EVs. This control is typically managed by Proportional-Integral-Derivative (PID) controllers, which are renowned for their simplicity and effectiveness. However, the conventional methods of tuning PID parameters can be cumbersome and often result in suboptimal performance. This proposed work explores the application of Genetic Algorithms (GAs) for optimizing PID controller parameters to enhance the control performance of BLDC motors in EVs. The core of this study lies in integrating GA with PID controllers to achieve superior speed and direction control of BLDC motors. GAs, inspired by the principles of natural selection and genetics, are robust optimization techniques that can efficiently search for optimal solutions in complex spaces. They are particularly advantageous in PID tuning, as they can handle the non-linearities and dynamic characteristics of BLDC motors more effectively than traditional methods. The GA-based PID controller design involves several critical steps: initializing a population of potential PID parameter sets, evaluating their fitness based on the control performance of the BLDC motor, selecting the best-performing sets, applying crossover and mutation to generate new parameter sets, and iterating this process until an optimal set of parameters is found. The fitness function is formulated to minimize control performance indices such as Integral Absolute Error (IAE), Integral Squared Error (ISE), rise time, settling time, and overshoot, ensuring a well-rounded improvement in motor control. Extensive simulations are conducted to validate the proposed GA-based PID tuning method. The results demonstrate significant improvements in the speed and direction control of BLDC motors compared to conventional PID tuning methods such as Ziegler-Nichols and Cohen-Coon. The optimized PID controllers exhibit reduced overshoot, faster response times, and enhanced stability, making them ideal for the dynamic and varying load conditions typical in EV applications. The present work focus on further refining the GA algorithm, exploring real-time implementation capabilities, and extending the approach to other types of electric motor control systems. The integration of advanced optimization techniques such as GA in PID controller design marks a significant step towards enhancing the performance and sustainability of electric transportation technologies.

Key Words

BLDC, Electric Vehicle, PID, Integral absolute error , rise time.

Cite This Article

"Novel Approach of GA based PID controller design for Speed and Direction Control of Electric Vehicle ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.e720-e726, October-2024, Available :http://www.jetir.org/papers/JETIR2410478.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Novel Approach of GA based PID controller design for Speed and Direction Control of Electric Vehicle ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. ppe720-e726, October-2024, Available at : http://www.jetir.org/papers/JETIR2410478.pdf

Publication Details

Published Paper ID: JETIR2410478
Registration ID: 544373
Published In: Volume 11 | Issue 10 | Year October-2024
DOI (Digital Object Identifier):
Page No: e720-e726
Country: Namakkal, Tamilnadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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