Assessment of Novel Self-tuned Emotional Learning-based Intelligent Controller for Bidirectional Cascaded Quasi-Z-Source DC–DC Converter Control

Abstract

The self-tuned emotional learning-based intelligent controllers (STELBICs) are suggested to regulate a bidirectional cascaded quasi-Z-source DC-to-DC converters (BC-qZSCs). The bidirectional converters of DC-to-DC with a huge voltage conversion range are required in current times for voltage matching in a variety of applications, particularly electric automobiles. The BC-qZSC may raise or buck the voltage, and electricity flows in both directions. The switch’s duty cycle can be changed to keep the voltage steady. To produce a consistent output voltage, a good controller design is necessary. To enhance the performance of BC-qZSC in both operating modes, this study introduces a unique STELBIC. The proposed novel controller’s performance is evaluated by comparing it with an artificial neural networks-controlled converter and a traditional Proportional Integral-controlled converter. In both boost and buck modes of operation, the controller’s performance is evaluated in terms of voltage quality, including steady-state error, settling time, and voltage ripple. Matlab/Simulink is used to analyze the entire system.

Keywords:

• DC–DC converter
• BC-qZSC
• PI
• ANN
• STELBIC

Author contributions

All authors are contributed equally to this work.

Ethics approval and consent to participate

No participation of humans takes place in this implementation process.

Human and animal rights

No violation of human and animal rights is involved.

ACKNOWLEDGMENT

There is no acknowledgement involved in this work.

Disclosure statement

Conflict of interest is not applicable in this work.

Data availability statement

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Additional information

Funding

No funding is involved in this work.

Notes on contributors

S. Lavanya Devi

S. Lavanya Devi received her B.E degree in Electronics and Communication Engineering from Alagappa Chettiar College Of Engineering And Technology, Anna University in the year 2008 and M.E degree in Power Electronics and Drives from College of Engineering Guindy (CEG), Anna University Chennai, India in the year 2013. She is pursuing her Ph.D. in Saveetha Engineering College, Anna University Chennai, India under the eminent guidance of Dr. R. Vinifa, Assistant Professor, Department of EEE. She is working as an Assistant Professor in Jerusalem College of Engineering, Department of Electronics and Communication Engineering, Chennai, India. She is a life time member of IEI and ISTE. She has 14.5 years of teaching experience. She has published 1 patent, 3 Scopus Indexed papers, and more than 15 papers in various other reputed National, International conferences and Journals. She has received Two “Best Paper Award” in the year 2019 and 2023 for her excellent innovative idea in Integrated Smart Glasses for Drivers and Real-Time Sewage Surveillance and Management respectively. She is interested in research areas such as Renewable energy Systems, E Vehicle, Embedded systems and Artificial Intelligent Controllers.

R. Vinifa

R. Vinifa received the B.E. degree in Electrical and Electronics Engineering from Manonmanium Sundaranar University, Tirunelveli, India, in 2003, the M.E. degree in power electronics and drives from the College of Engineering, Guindy, Anna University, Chennai, India, in 2013, and the Ph.D. degree from the College of Engineering Guindy, Anna University, Chennai, India, in 2019. She has more than 13 years teaching experience and 6 years research experience. She has published several papers in reputed international journals. Currently, she is working as Assistant Professor in Saveetha Engineering College, Department of Electrical and Electronics Engineering, Chennai, India She is a Life Member of Indian Society for Technical Education and Institution of Engineers. Her research interests include renewable energy, Power Electronics, Electric Vehicles, and control systems.