Application of Recursive Subspace Method in Vehicle Lateral Dynamics Model Identification

Tengyue Ba, Xiqiang Guan, Jian W. Zhang and Sanzhou Wang

Mathematical Problems in Engineering, 2016, vol. 2016, 1-15

Abstract:

Modeling of vehicle behavior based on the identification method has received a renewed attention in recent years. In order to improve the linear time-invariant vehicle identification model, a more general identifiable vehicle model structure is proposed, in which time-varying characteristics of vehicle speed and cornering stiffness are taken into consideration. To identify the proposed linear time-varying vehicle model, a well-established data-driven method, named recursive optimized version of predictor-based subspace identification, is introduced. Before vehicle model identification, the influences of four parameters in the subspace algorithm are studied based on pulse input road test. And then a set of practical optimal parameters are chosen and used for the vehicle model identification. Through a series of standard road tests under different maneuvers, the linear time-varying vehicle model can be identified in real-time. It is demonstrated by comparison that the predicted outputs of the proposed vehicle model are much closer to the real vehicle outputs and the model has a wider range of application.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1715762

DOI: 10.1155/2016/1715762

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