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Particle swarm optimization technique of current tracking controller for electric power-assisted steering system


Citation

Bahmanshiri, Adel Amiri (2015) Particle swarm optimization technique of current tracking controller for electric power-assisted steering system. Masters thesis, Universiti Putra Malaysia.

Abstract

Electric Power Assisted Steering (EPAS) system is a new power steering technology for vehicles especially for Electric Vehicles (EV). It has been applied to displace conventional Hydraulic Power Assisted Steering (HPAS) system due to space efficiency, environmental compatibility and engine performance. An EPAS system is a driver-assisting feedback system designed to boost the driver input torque to a desired output torque causing the steering action to be undertaken at much lower steering efforts. Various control algorithms are derived in order to achieve the specified system characters. To achieve better driving feeling in the EPAS system for EV, there are two problems need to be addressed: sufficient assist torque should be transferred to drivers;motor current tracking should be perform by controller. In this thesis, a controller structure design is proposed for EPAS system that addresses motor current tracking performance, offering sufficient gain for different driver torques and different vehicle speeds. This thesis introduces a control strategy to design the controller that control motor current in different speeds and different driver torques. The motor controller is PID controller that optimized by Particle Swarm Optimization (PSO) technique that is used to improve current tracking performance. The simulation for the whole EPAS system is implemented by Matlab/Simulink. In this case, three test procedure are done to show the performance of current tracking controller in different situations, also the current tracking performance with Particle Swarm Optimization (PSO)-PID controller compared to previous research that used Ant Colony Optimization (ACO)-PID controller [1] to show the percentage of error between reference motor current and actual motor current of proposed PSO optimization algorithm with 0.023% is much less than previous worked (ACO optimization algorithm) with 4.76%.So the proposed control strategy can improve otor current tracking performance in electric powers assisted steering (EPAS) systems.


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Additional Metadata

Item Type: Thesis (Masters)
Subject: Swarm intelligence
Subject: Automobiles - Steering-gear
Subject: Automobile driving - Steering
Call Number: FK 2015 5
Chairman Supervisor: Mohd Khair Bin Hassan, PhD, Ir
Divisions: Faculty of Engineering
Depositing User: Haridan Mohd Jais
Date Deposited: 30 Jun 2017 03:42
Last Modified: 30 Jun 2017 03:42
URI: http://psasir.upm.edu.my/id/eprint/56216
Statistic Details: View Download Statistic

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