Optimized PV fed sensorless BLDC motor control system using Q-recurrent adaptive controller and Levy-enhanced...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Conventional controllers like PID and ANFIS have limitations in performance under varying loads and parameter sensitivity.
• Sensorless Brushless DC (BLDC) motor control is crucial for applications like electric vehicles and renewable power systems.
• Efficient and reliable operation of BLDC motors requires advanced control strategies.

Purpose of the Study:

• To develop an intelligent controller for a solar photovoltaic (PV)-fed sensorless BLDC motor.
• To enhance the performance of sensorless BLDC motors by addressing limitations of traditional control methods.
• To combine a Q-Recurrent Adaptive Motor Controller (Q-RAMC) with Levy-Enhanced Circular Search (LECS) for improved motor control.

Main Methods:

• Development of a smart controller integrating Q-Recurrent Adaptive Motor Controller (Q-RAMC) and Levy-Enhanced Circular Search (LECS).
• Utilizing a Solar PV system as the power source for the sensorless BLDC motor.
• Performance evaluation through simulation comparing the proposed method with PID and ANFIS controllers.

Main Results:

• The proposed controller significantly enhances motor control, outperforming PID and ANFIS.
• Torque ripple is reduced by 3.10%, leading to smoother torque delivery.
• Overall system efficiency reaches up to 99%, with a 1.5s decrease in speed transient time and a 0.5s reduction in rise time.

Conclusions:

• The developed smart controller offers superior performance for solar PV-fed sensorless BLDC motors.
• The integration of advanced control techniques leads to improved dynamic response and control precision.
• This approach provides an efficient and reliable solution for sensorless BLDC motor applications in renewable energy and electric vehicles.