Simulasi Pengaturan Kontroler Pid dengan Metode Fuzzy-Pso terhadap Respon Kecepatan Motor Bldc pada Mobil Listrik

Abstract

Dynamic load changes are a major problem experienced in Electric Cars because it can make the value and quality of the speed generated by the drive motor. The nonlinear Brushless Direct Current (BLDC) motor, which is used in Electric Cars, will greatly degrade when dynamic load changes occur. An optimal and stable speed control system is needed to control the motor speed. There are many methods of controlling motor speed in Electric Car applications such as Proportional Integral Derivative (PID), Fuzzy¬ Logic, and Particle Swarm Optimization (PSO). However, the PID Controller becomes an optimal and effective device in controlling the speed of BLDC Motors subjected to dynam ic loads, with the help of Fuzzy Logic and PSO optimization. In this research, Fuzzy PID Controller with PSO Optimization will be used in controlling the speed of BLDC Motor, to reduce the speed drop due to dynamic load. Matlab Simulink will be used to analyze the optimality and effectiveness of Fuzzy PID with PSO optimization in reducing the impact of dynamic loads. From the measurement results, a significant improvement in control performance is shown, with a reduction i n response time (rising time) up to 20.982%, lowering the settling time value to 21.102%, and also eliminating the maximum overshoot which was originally 0.0123%. In addition, the optimized controller managed to minimize the speed drop due to load changes from 356.935 rpm to only 506.916 rp m. Moreover, the controller takes a faster recovery time to the stable value of only 2.267 seconds, which before optimization took 4.747 seconds. Overall, the Fuzzy PID controller after PSO optimization shows improved stability, faster response, and better precision in controlling BLDC Motors subjected to dynamic loads