Studies On Performance Enhancement Of Brushless Dc Motor Drives Using Artificial Intelligence Techniques

Abstract

The recent rapid proliferation of motor drives in the automobile newlineindustry with the new hybrid technology has created a great demand for newlineefficient variable speed motor drives with longterm stability and good newlinetransient performance in the adjustable speed drives newlineA Brushless DC BLDC motor is a good choice for this type of newlinedrives A BLDC motor looks exactly similar to a DC motor with an newlineelectronically controlled commutation system instead of the mechanical newlinecommutation When the motor drive is used in variable speed applications newlinethe speed of the drive is seriously affected by the unknown load newlinecharacteristics and sudden variation of parameters As the BLDC motor drives newlineare non linear in nature they require an improved or modified controller that newlinecan adapt to the nonlinear situation and achieve the desired performance newlineThe BLDC motor drive is operated with sensors or without sensors newlineThe sensorless controlled BLDC motor drive is widely used as it reduces the newlinecost and size of the drive A simplified simulation model was developed for newlinethe BLDC motor drive with hall sensors and extended to the sensorless speed newlinecontrol technique A detailed analysis carried out on the sensorless controlled newlineBLDC motor under different operating conditions showed that the sensorless newlinemodel can be further used in the study of the proposed Artificial intelligence newlinecontroller for BLDC motor drives The PI controller showed improvement in newlinethe performance only in the designed case but it gave poor performance newlineunder other operating conditions Hence the PI controller requires optimal newlinetuning for improving the performance of the drive newlineThe Genetic algorithm based tuning of the gains of the PI controller newlinewas carried out to further improve the performance of the drive The Genetic newlinealgorithm tuned PI controller showed good improvement in the performance newlinewhen compared with the results obtained from the trial and error method The newlineresults also showed that the PI controller requires automatic tuning of the newlinegains of the controller newline newline