GPS Based Estimation of Vehicle Sideslip Angle Using Multi-Rate Kalman Filter with Prediction of Course Angle Measurement Residual-Reference-Cited by-同舟云学术

GPS Based Estimation of Vehicle Sideslip Angle Using Multi-Rate Kalman Filter with Prediction of Course Angle Measurement Residual

Published:2012-10-26 Issue: Volume: Page:597-609
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
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Author:

Nguyen B. M.,Wang Yafei,Oh Sehoon,Fujimoto Hiroshi,Hori Yoichi

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-33829-8_56.pdf

Reference8 articles.

1. Wong JY (2001) Theory of ground vehicles, 3rd edn. Wiley, Hoboken

2. Corrsys-Datron http://www.corrsys-datron.com/optical_sensor.htm

3. Geng C, Mostefai L, Denai M, Hori Y (2009) Direct yaw moment control of an in wheel motored electric vehicle based on body slip angle fuzzy observer. IEEE Trans Industr Electron 56:1411–1419

4. Wang Y, Nguyen BM, Kotchapansompote P, Fujimoto H, Hori Y (2012) Vision-based vehicle body slip angle estimation with multi-rate kalman filter considering time delay. In: 21st IEEE international symposium on industrial electronics

5. Bevly DM, Ryu J, Gerdes JC (2006) Integrating INS sensors with GPS measurements for continuous estimation of vehicle sideslip, roll, and tire cornering stiffness. IEEE Trans Intell Transp Syst 7(4):483–493

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1. On the vehicle dynamics prediction via model-based observation;Vehicle System Dynamics;2023-06-06

2. A fusion methodology for sideslip angle estimation on the basis of kinematics-based and model-based approaches;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2019-12-24

3. A low-cost GPS/INS integrated vehicle heading angle measurement system;AIP Conference Proceedings;2018