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Optimized Brushless Dc Motor(BLDCM) Controller for Electric Vehicle

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dc.contributor.authorMuhammad Danial bin Adrisen_US
dc.date.accessioned2023-05-03T17:32:07Z
dc.date.available2023-05-03T17:32:07Z
dc.date.issued2020-09
dc.descriptionInterim Semester 2020/2021en_US
dc.description.abstractThis paper demonstrates a control method for brushless direct current (BLDC) engine drives from a Fuzzy Logic. The BLDC motor has several benefits relative to other motor types. The nonlinearity of this drive function, however, implies that the usage of traditional proportional, integral and differential (PID) controller is difficult to manage. A Fuzzy-PID controller with a Gaussian membership feature is designed to solve this key issue. The conceptual model is extracted from the BLDC generator. The controller is programmed to detect shifts in speed comparisons and to maintain performance speed in load changes. The efficacy of the proposed approach is verified by the MATLAB Simulink programme simulation model. The simulation results indicate that the proposed Fuzzy-PID controller offers substantial improvement in control efficiency, compared with the PID controller, for both speed and load disruption controlsen_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/21646
dc.language.isoenen_US
dc.subjectBLDC Motoren_US
dc.subjectSpeed Controlen_US
dc.subjectPID-Fuzzyen_US
dc.titleOptimized Brushless Dc Motor(BLDCM) Controller for Electric Vehicleen_US
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