Modeling, simulation, and experimental validation of electro-hydraulic power steering system in multi-axle vehicles

An accurate electro-hydraulic power steering system (EHPSS) model is essential to analyze dynamic steering performance and advanced nonlinear control. The main obstacle to establish an accurate model is the complex structure, including steering mechanism, valve controlled dual hydraulic-actuator, and heavy duty tires. This paper constructs a suitable model incorporating these parts, based on a Lagrange equation describing the steering trapezoid mechanism and dual cylinder hydraulic dynamics, regarding steering resisting moment as an external load. A simplified tire model is used to represent the tire basic steering load characteristics. Due to the complexity of the kinematic relationship in the model, several expressions are fitted using back propagation neural networks to significantly reduce calculation difficulty. Experimental measurements and simulation using Matlab/Simulink and experiment are realized for the case of in situ steering, and the results validate the proposed model accuracy. Thus, the proposed model is suitable to analyze the system and design advanced controllers.

• Record URL:
  https://doi.org/10.1177/0954407017743346
• Record URL:
  https://journals.sagepub.com/doi/abs/10.1177/0954407017743346
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09544070
• Supplemental Notes:
  • Reprinted by permission of Sage Publications, Ltd.
• Authors:
  • Du, Heng
  • Zhang, Qingming
  • Chen, Shumei
  • Fang, Jinhui
• Publication Date: 2019-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 317-332
• Serial:
  • Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
  • Volume: 233
  • Issue Number: 2
  • Publisher: Sage Publications Limited
  • ISSN: 0954-4070
  • EISSN: 2041-2991
  • Serial URL: http://pid.sagepub.com/content/current

Subject/Index Terms

• TRT Terms: Axles; Electrohydraulic mechanisms; Mathematical models; Neural networks; Power steering; Simulation; Steering systems; Validation
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01695914
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 22 2019 5:07PM