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Intelligent Control System for High Efficiency Electric Vehicles
Muhammad Rifan, Ermi Medias, Heri Firmansyah

Universitas Negeri Jakarta


Abstract

Brush-less Direct Current (BLDC) motor drive systems are widely used in electric vehicles (EV). However, most EV control strategies only focus on BLDC motors without considering changes in different driving conditions. This paper propose an intelligent control strategy based on an intelligent neural network that is able to change control parameters based on changing driving conditions. This system has the ability to self-learning and adapt based on driving conditions. The simulation is carried out using the Electric Vehicle Drive Train model and run on the MATLAB-SIMULINK platform. The simulation results show that the smart control strategy designed shows very good efficiency with minimal errors and quickly adapts to different driving conditions.

Keywords: Intelligent Control System, BLDC, Efficiency, Electric Vehicles

Topic: Electrical Engineering

Plain Format | Corresponding Author (Muhammad Rifan)

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