Fine-Tuning Quarter Vehicle Performance: PSO-Optimized Fuzzy PID Controller for In-Wheel BLDC Motor Systems

被引:2
|
作者
Baz, Rachida [1 ]
El Majdoub, Khalid [1 ]
Giri, Fouad [2 ]
Ammari, Ossama [1 ]
机构
[1] Univ Hassan 2, Casablanca, Morocco
[2] Normandie Univ, UNICAEN, F-14000 Caen, France
来源
IFAC PAPERSONLINE | 2024年 / 58卷 / 13期
关键词
Fuzzy logic controllers; PID; Particle swarm optimization (PSO); PACEJKA tire model; longitudinal model;
D O I
10.1016/j.ifacol.2024.07.566
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces an enhanced approach for monitoring the speed of an electric car propelled by a brushless DC motor (BLDC) through the utilization of particle swarm optimization (PSO). The aim is to optimize the proportional (Kp), integral (Ki), and derivative (Kd) gains of the PID controller in conjunction with the fuzzy controller. The system architecture is meticulously modeled, and optimization is conducted within the MATLAB/Simulink environment. Through rigorous experimentation, the proposed methodology showcases superior efficacy in minimizing error compared to conventional techniques. By synergizing PSO with PID and fuzzy control, the study demonstrates a promising avenue for enhancing the speed control system of BLDC-powered electric cars, thereby advancing the field of electric vehicle technology toward greater efficiency and performance. Copyright (c) 2024 The Authors.
引用
收藏
页码:715 / 720
页数:6
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