PID-Ant Colony Optimization (ACO) control for electric power assist steering system for electric vehicle

• Main Authors: Abu Hanifah, Rabiatuladawiyah, Toha, Siti Fauziah, Ahmad, Salmiah
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: TJ212 Control engineering
• Online Access: http://irep.iium.edu.my/34112/1/ICSIMA-epas_DR_Fauziah_MCT.pdf; http://irep.iium.edu.my/34112/
• Institution: Universiti Islam Antarabangsa Malaysia

Electric Power Assist Steering (EPAS) system offers a significant potential in enhancing the driving performance of a vehicle where the energy conserving issue is important. In this paper, Ant Colony Optimization (ACO) algorithm is implemented as tuning mechanism for PID controller. The aim of this hybrid controller is to minimize energy consumption of the EPAS system in Electric Vehicle (EV) by minimizing the assist current supplied to the assist motor. The ACO algorithm searching technique is applied to search for the best gain parameters of the PID controller. The fast tuning feature of ACO algorithm is the factor that distinguish this hybrid method as compared to conventional trial and error method PID controller tuning. Simulation results shows the performance and effectiveness of using ACO algorithm for PID tuning.