Control strategy of automotive electric power steering system based on generalized internal model control

Abstract

In terms of the research on electric power steering system, there are some problems, such as model uncertain and external interference. However, it is difficult for a general controller to deal with those problems as well as the performance of the system. Therefore, the paper is to propose a control method based on generalized internal model control, which is based on feedback and Youla parameterization, including performance controller and compensation controller. The performance controller is used to make the electric power steering system work well, while the compensation controller is used to solve model uncertain and external interference. First of all, the paper is to establish the model of electric power steering system, introduce the 2DOF vehicle and the tire model, set up the state space of the electric steering system including model uncertain and interference and design the generalized internal model controller. Finally, the simulation and the hardware-in-the-loop experiment are carried out to verify the controller. The results show that the proposed controller takes advantages of better control performance, solving model uncertain and external interference, and improving the performance and robustness of the system.

Modelling and Simulation of a Brushless Motor DC for Electric Power Steering Assistance

“…BLDC motors have many advantages over DC brushed motors. The main advantages of replacing the brushed DC motor with BLDC motors are: high power efficiency, high dynamic response, less noise, less maintenance, no arc is generated during operation, longer life compared to DC motors, higher torque / volume ratio and higher speed range [15], [16], [26].…”

Proposing a BSPID Control Strategy Considering External Disturbances for Electric Power Steering (EPS) Systems

“…This problem could be solved using the two-loop algorithm (the torque loop and current loop) in reference [48]. Some nonlinear control methods for EPS systems should be found in references [49][50][51][52][53].…”