An estimation scheme of road friction coefficient based on novel tyre model and improved SCKF
In order to identify the road friction coefficient of the left and right sides of the vehicle more accurately, this paper presents an estimation framework based on a novel tyre model and modified square-root cubature Kalman filter (SCKF). To begin with, a novel tyre model is proposed by adaptively calculating the longitudinal and lateral stiffness and the effective friction coefficient. The tyre forces calculated by this model are more accurate than those calculated by the Brush model. Then, to avoid the influence of abnormal measurement noise on the estimation effect, we develop an improved SCKF (ISCKF) algorithm based on the maximum correntropy criterion. The algorithm can update the measurement noise covariance adaptively. Furthermore, a real-time estimation scheme of road friction coefficient is designed by combining the vehicle dynamics model with the proposed novel tyre model and ISCKF algorithm. Finally, the performance of the presented method is verified by the co-simulation of CarSim and MATLAB/Simulink. The results show that the designed estimation scheme not only has excellent robustness in the case of abnormal measurement noise interference but also has good adaptability to the uncertainty of road friction coefficients distribution.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/00423114
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Supplemental Notes:
- © 2021 Informa UK Limited, trading as Taylor & Francis Group 2021. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Zhang, Zhida
- Zheng, Ling
- Wu, Hang
- Zhang, Ziwei
- Li, Yinong
- Liang, Yixiao
- Publication Date: 2022-8
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 2775-2804
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Serial:
- Vehicle System Dynamics
- Volume: 60
- Issue Number: 8
- Publisher: Taylor & Francis
- ISSN: 0042-3114
- EISSN: 1744-5159
- Serial URL: https://www.tandfonline.com/toc/nvsd20/current
Subject/Index Terms
- TRT Terms: Coefficient of friction; Kalman filtering; Mathematical models; Motor vehicle dynamics; Roads; Tire forces
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01855943
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 24 2022 3:05PM