Design and Analysis of GWO-Based PI Controller for Solar Fed BLDC Motor with INC MPPT
Department of EEE, Sanketika Vidya Parishad Engineering College (SVPEC), Affiliated to Andhra University, Visakhapatnam, A.P., India
A. Pavan¹, B. Midhunesh2, K. John Harshad3, G. Sowmya4, S. Pujitha5
Under the Guidance of Mr. Ch. Vishnu Chakravarthi6, M.Tech., Assistant Professor
1Student, Department of ELECTRICAL ELECTRONICS ENGINEERING, Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India. pavanagraharapu143@gmail.com
2Student, Department of ELECTRICAL ELECTRONICS ENGINEERING, Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India. midhuneshbarinika@gmail.com
3Student, Department of ELECTRICAL ELECTRONICS ENGINEERING, Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India john.harshad75@gmail.com
4Student, Department of ELECTRICAL ELECTRONICS ENGINEERING, Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India. gondesisowmya@gmail.com
5Student, Department of ELECTRICAL ELECTRONICS ENGINEERING, Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India. reddyneelu623@gmail.com
6Assistant professor, Department of ELECTRICAL ELECTRONICS ENGINEERING Sanketika Vidya Parishad Engineering College, Visakhapatnam,
Andhra Pradesh, India. vishnu.eee@svpec.edu.in
Abstract
This paper presents the design and analysis of a Grey Wolf Optimization (GWO)-based PI controller for a solar-fed Brushless DC (BLDC) motor with Incremental Conductance (INC) MPPT technique. Conventional MPPT methods such as Perturb and Observe (P&O) and PSO suffer from steady-state oscillations, slower tracking, and limited optimization performance. The proposed system integrates the INC MPPT technique with GWO-tuned PI controller for enhanced performance. The solar PV array is connected to a DC-DC boost converter and three-phase inverter feeding the BLDC motor. The INC MPPT method ensures accurate and fast maximum power point tracking with reduced oscillations under varying environmental conditions, while the GWO algorithm optimally tunes the PI controller parameters by minimizing the Integral of Absolute Error (IAE). MATLAB/Simulink simulation demonstrates 99.4% MPPT tracking efficiency, 1.0% steady-state speed error, 35ms settling time, and 38% reduction in IAE compared to conventional PSO-tuned controllers, validating the approach for solar-powered electric drives in water pumping and EV applications.
Keywords: BLDC Motor, Solar PV, Grey Wolf Optimization, INC MPPT, PI Controller, Speed Control, Renewable Energy Drive
