ARTIFICIAL INTELLIGENCE BASED ON THE OPTIMAL STRATEGY OF MULTILEVEL CONVERTER FOR BRUSHLESS DC MOTOR

Abstract

This paper presents an interesting novelty in the implementation of artificial intelligence (AI) to apply multi-level converter control, the best strategy for the Brushless DC motor control (BLDC). The interesting highlight of this research is the importance of bringing artificial intelligence (AI) to develop multi-level converter mechanisms using the artificial neural network algorithm. The neural network is a branch of artificial intelligence and is used to detect the magnitude of the input voltage from batteries. The operation of this DC-DC voltage conversion mechanism detects the output voltage and current to control the operation of the multi-level conversion mechanism supplied with six switched three-phase converters (SSTPC) to the BLDC motor controller. For this BLDC motor control mechanism, the neural network algorithm detects the Hall Effect signal to generate a PWM signal to control the action of the SSTPC. Notwithstanding, the prototype mechanism of this research is divided into two parts, the first being the conversion control mechanism multi-level, which is an essential part of voltage regulation. The second is the BLDC motor torque and speed control mechanism. This torque and speed control uses the Hall Effect signal detection principle and processes it with a neural network algorithm to generate a PWM signal to control the SSTPC activity. This neural network algorithm is processed with a DSP-TMS320C2000 microcontroller. However, the results of the prototype mechanism tested; found the importance of artificial intelligence (AI) for developing multi-level conversion mechanisms using artificial neural network algorithms with comparison simulations with programs MATLAB/Simulink. Found that a multi-level conversion control mechanism can control the voltage according to the objectives. In addition, SSTPC can also control the torque and speed of BLDC Motors. Therefore, this research result is a confirmation sign as satisfactory and can be further developed.