Dual Stage Speed Control of BLDC Motor Using Hybrid QPSO-CSO Technique

Abstract

Systems for driving motors are frequently employed with renewable energy sources. By using cutting-edge methods and algorithms, the power converter controlling technology boosts performance. The switching state of the converter from the solar module’s generation unit is where the QPSO (Quantum Particle Swarm Optimization) technique is applied in the currently available work. The duty cycle depends on the swarm velocities, which indirectly depends on the QPSO parameters. Hence, the QPSO parameters inertia (W), and learning coefficients C1 and C2, were determined using the Cuckoo search algorithm (CSO). This approach helps to extract the most powerful solar panel output and continuously operate a BLDC motor performance increasing the power converter controlling technology by utilizing state-of-the-art techniques and algorithms. Every module of the suggested boost converter was examined by the experimental findings. Based on generation and load, a boost converter module is obtained. The Models for single-ended primary inductors (SEPIC) and zeta converters are contrasted with the suggested logic. The overall design model is done by using MATLAB/Simulink 2021a.

Keywords:

• PV module
• Boost converter
• Hybrid QPSO-CSO
• Voltage Source Inverter (VSI)
• constant speed

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

INVOLVEMENT PERMISSION AND ETHICS APPROVAL

In this implementation procedure, no human beings are involved.

BOTH ANIMAL AND HUMAN RIGHTS

There isn’t any transgression of either human or animal rights.

AVAILABILITY OF DATA STATEMENT

As no datasets were created or analyzed for the present investigation, data sharing is not applicable to this article.

AUTHORSHIP CONTRIBUTIONS

No one contributed to the writing.

Additional information

Notes on contributors

S. Pandeeswari

S. Pandeeswari is currently working as Assistant Professor in the Department of Electronics and Communication Engineering at RVS College of Engineering and Technology, Coimbatore. She has completed her BE and ME degree from PSNA College of Engineering and Technology, Dindigul. Now she is pursuing Ph.D at Anna University Chennai. She has 24 years of teaching experience. She has published 2 patents, 5 journals and 7 conferences. Her area of interest on Power Electronics, Power converters, Electrical drives and Communication Engineering.

S. Jaganathan

S. Jaganathan is currently working Professor and Head at Department of Electrical and Electronics Engineering, Dr. N.G.P. Institute of Technology, Coimbatore. He has completed his Ph.D. in Electrical Engineering from Anna University, Chennai, Tamil Nadu, India. Dr. S. Jaganathan has over 15.1 years of experience in reputed Engineering Colleges such as Lecturer at Sapthagiri College of Engineering, Dharmapuri, Lecturer at Maharaja Engineering College, Avinashi, Assistant Professor at Park College of Engineering and Technology, Coimbatore, Senior Lecturer, Assistant Professor, Associate Professor and Professor at RVS College of Engineering and Technology, Coimbatore. He has published over 20 technical papers and presented lectures at various national conferences. He has conducted many workshops/conferences in the emerging area such as power systems, embedded systems, Industry applications and Hotline maintenance in EHV & UHV transmission line at PARKCET and RVSCET. He is reviewer of Elsevier Transactions, International Journal of Electrical Power and Energy Systems, Scientific Research and Essays, Springer publications, IJCA and IJCSNS journals and recognized supervisor for Research in Anna University, Chennai. He is member of International Society for Research and Development, Indian Society for Technical Education, life member of IAENG, member of ISDS, IORSD, UACEE and member of Asian Council for Science Editors. His main area of interest focuses on Power Systems Modeling, Analysis and Operation, Power Electronics applications to Power system, Soft Computing Techniques, Electrical Machines, and Embedded Systems.