Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter

Jing Li and Jiaxu Zhang

Mathematical Problems in Engineering, 2016, vol. 2016, 1-10

Abstract:

Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF), which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF), which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM) approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.

Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2016/3269142.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2016/3269142.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3269142

DOI: 10.1155/2016/3269142

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().