Research on the Control of Brushless DC Motors in Automobile Automatic Steering Devices

• Published in: Journal of physics. Conference series Vol. 3023; no. 1; pp. 12002 - 12008
• Main Authors: Zhao, Xin Tong, Song, Cun Long
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.06.2025
• Subjects: Adaptive algorithms; Adaptive control; Brushless motors; Control systems; Controllers; Critical components; D C motors; Fuzzy control; Kinematics; Proportional integral derivative; Real time; Simulation models; Steering
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/3023/1/012002

The automotive automatic steering device serves as a critical component in the Kinematics & Compliance (KC) characteristic test bench for measuring specific vehicle data. This paper focuses on the Brushless Direct-Current Motor (BLDCM)within the automotive automatic steering device as the research subject, establishing a mathematical model of the system. It introduces traditional Proportional-Integral-Differential (PID) control and adaptive fuzzy control strategies, combining them to design an adaptive fuzzy PID controller. Due to the nonlinear and time-varying characteristics of BLDCM, the control effectiveness of PID in the automatic steering device is suboptimal. Therefore, an adaptive fuzzy algorithm is employed to dynamically adjust the parameters of the PID controller in real-time, thereby optimizing the control of BLDCM in the automotive automatic steering device. By constructing a simulation model in the simulation software environment, experimental results demonstrate that The PID controller using adaptive fuzzy algorithm for real-time control can effectively control the control system of automatic steering devices, with better adaptability, anti-interference and stability, and the steering accuracy of automotive automatic steering devices is improved.