Modeling and Nonlinear Parameter Identification of an Electric-Power Steering System

• Published in: Topics in Modal Analysis & Testing, Volume 10 pp. 127 - 135
• Main Authors: Faria, Cassio T., Pulvirenti, Giorgio, Geluk, Theo
• Format: Book Chapter
• Language: English
• Published: Switzerland River Publishers 01.01.2017; Springer International Publishing AG; Springer International Publishing
• Edition: 1
• Series: Conference Proceedings of the Society for Experimental Mechanics Series
• Subjects: CIVIL ENGINEERING, SURVEYING & BUILDING; Dynamics & vibration; Electric power steering; Mechanical engineering; Model based system testing; Multiphysics; Nonlinearity; Parameter identification; Multiphysics; Nonlinearity; Electric power steering; Parameter identification; Model based system testing
• ISBN: 3319548093; 9783319854892; 3319854895; 9783319548098
• ISSN: 2191-5644; 2191-5652
• DOI: 10.1007/978-3-319-54810-4_13

The electrification of auxiliary systems in the next generation of automobiles complies with the regulatory and customer requirements to increase the overall system efficiency and reduce the carbon footprint of the product. For the power steering system its electrification also attends another important demand of the industry: the actuation of the vehicle for autonomous driving function. The development of advanced model-based controllers increase the requirements for model accuracy which are met by incorporating nonlinearities in the model and also by carrying out advanced parameter identification in those systems. This paper illustrates a modeling and testing procedure for a C-class electric power steering (EPS) system, following a model-based system testing (MBST) approach and presents results from a test campaign. A comparison it is drawn on the model prediction capabilities when compared to collected experimental data.