Neural Network Based Optimisation of Sinusoidal PWM Controller for VSI-Driven BLDC Motor
More details
Hide details
University of Mines and Technology
Univesity of Mines and Technology
Corresponding author
George Owusu   

University of Mines and Technology
Power Electronics and Drives 2023;8(Special Section - Artificial Intelligent Based Designs and Applications for the Control of Electrical Drives )
Although increasing the number of switches increases the switch losses, most designed controllers focus on controlling an inverter circuit with more than 6 switches. The work aims to address this issue that arises in the implementation of the VSI for BLDC motors. It optimises the sinusoidal PWM controller, minimising THD while keeping the VSI's circuit at six switches to avoid increased switching losses. This was achieved by applying an ANN to generate a signal, which combines with the already existing reference and carrier signals. The addition of the new signal to the existing signals contributed to generating more pulses compared to conventional sinusoidal PWM. Simulink was used to design the system and analyse its performance with conventional and the NPC VSI system. Results indicated that the proposed system performs better when controlled with LCC filter. Compared to the control experiments, its output waveform has the lowest THD value, which is 6.04%. The switching losses of all the systems were also computed. Results from the computation indicated that the proposed system is capable of reducing the switching losses by 0.6 kW compared to the NPC VSI BLDCM system. BLDCM speed was tested across various conditions; results were reported in conclusion section.
Journals System - logo
Scroll to top