A New Control Strategy of an Electric-Power-Assisted Steering System

• Published in: IEEE transactions on vehicular technology 2012-10, Vol.61 (8), p.3574-3589
• Main Authors: Marouf, A., Djemai, M., Sentouh, C., Pudlo, P.
• Format: Article
• Language: English
• Subjects: Applied sciences; Circuit properties; DC motors; Electric, optical and optoelectronic circuits; Electric-power-assisted steering (EPAS); Electrical engineering. Electrical power engineering; Electrical machines; Electrical power engineering; Electronic circuits; Electronics; Exact sciences and technology; Frequency filters; Miscellaneous; observer with unknown inputs; Power networks and lines; reference model; Regulation and control; Roads; robust differentiators; Robustness; sliding mode; Torque; Vehicles; Vibrations; Wheels
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2012.2209689

The control of electric-power-assisted steering (EPAS) systems is a challenging problem due to multiple objectives and the need for several pieces of information to implement the control. The control objectives are to generate assist torque with fast responses to driver's torque commands, ensure system stability, attenuate vibrations, transmit the road information to the driver, and improve the steering wheel returnability and free-control performance. The control must also be robust to modeling errors and parameter uncertainties. To achieve these objectives, a new control strategy is introduced in this paper. A reference model is used to generate an ideal motor angle that can guarantee the desired performance, and then, a sliding-mode control is used to track the desired motor angle. This reference model is built using a dynamic mechanical EPAS model, which is driven by the driver torque, the road reaction torque, and the desired assist torque. To implement the reference model with a minimum of sensors, a sliding-mode observer with unknown inputs and robust differentiators are employed to estimate the driver torque, the road reaction torque, and the system's states. With the proposed control strategy, there is no need for different algorithms, rules for switching between these algorithms, or fine-tuning of several parameters. In addition, our strategy improves system performance and robustness and reduces costs. The simulation results show that the proposed control structure can satisfy the desired performance.