Sensor-less Speed Control of PV-fed PMSM using MRAS with 2-stage (RCC–MRAC) MPPT under Partial Shading Conditions

Read full text
Authors: HUSSAIN MEHBOOB, UĞURENVER ABBAS
Cited by: 0

Abstract

Over the past few years, the use of Permanent Magnet Synchronous Motors (PMSMs) in various applications, such as robotics, industrial automation, water pumping, and HVAC systems, has grown significantly. This is primarily due to their compact construction, high efficiency, ease of use, outstanding controllability, ability to maintain full load speed, and low operational speeds. Their performance in pumping water and HVAC systems is even more beneficial when used with photovoltaic (PV) solar systems. To optimally use such systems, the incorporation of a power Maximization Point Tracking (MPPT) algorithm is essential. In this work, we develop a PV powered PMSM with sensor-less speed control. This work is structured into two main parts. The first part presents a two-stage MPPT strategy intended to overcome some of the challenges in speed and precision tracking posed by traditional MPPT methods. First stage is Ripple Correlation Control (RCC) and the second stage is Model Reference Adaptive Control (MRAC) to maintain overall system stability. The second part discusses the PMSM drive system where a physical encoder is not required because the encoder-less speed estimation is done using the Model Reference Adaptive System (MRAS) approach. The PMSM is controlled using vector control as it shows the dynamic behavior of a DC motor. Furthermore, higher operating speeds are achieved by weakening the magnetic flux where the inverse d-axis current is injected into the rotor. The entire system has been modeled and simulated in MATLAB/Simulink, and its performance has been analyzed for different operating conditions

Fields of Study & Subjects

Sensorless Control of Electric Motors Photovoltaic System Optimization Techniques Electric Motor Design and Analysis

Publication details

Journal / source
Konya Journal of Engineering Sciences
Publication date
1 January 2026
Language
EN
Document type
Preprint