Title: Vehicle sideslip angle estimation: fusion of vehicle kinematics and dynamics

Authors: Xin Xia; Lu Xiong; Yishi Lu; Letian Gao; Zhuoping Yu

Addresses: School of Automotive Studies, Tongji University, Shanghai, 201804, China ' School of Automotive Studies, Tongji University, Shanghai, 201804, China ' School of Automotive Studies, Tongji University, Shanghai, 201804, China ' School of Automotive Studies, Tongji University, Shanghai, 201804, China ' School of Automotive Studies, Tongji University, Shanghai, 201804, China; Nanchang Automotive Innovation Institute, Tongji University, Shanghai, 201804, China

Abstract: In this paper, a VSA estimation method is proposed based on fusing the vehicle kinematics and dynamics. First, the vehicle-kinematic-based (VK-based) VSA estimation method is provided by the global navigation satellite system (GNSS) and inertial navigation system (INS) integration system (GNSS/INS integration system). The heading error in GNSS/INS integration is not well observable and its estimation accuracy cannot be guaranteed when the acceleration in the horizontal plane is small and varies little. To improve the heading error estimation accuracy, a vehicle-dynamic-model-based (VDM-based) VSA estimation method is given and based on this method, a novel augmented heading estimator for the GNSS/INS integration system is designed. Besides, an intuitive heading error weighting strategy is presented to determine the heading error between the heading error from GNSS/INS integration system and that from the augmented heading error estimator. Finally, the proposed method is validated by a comprehensive test.

Keywords: vehicle sideslip angle estimation; heading error estimation; vehicle dynamics; information fusion; Kalman filter.

DOI: 10.1504/IJVD.2021.122688

International Journal of Vehicle Design, 2021 Vol.87 No.1/2/3/4, pp.73 - 94

Received: 29 Jun 2020
Accepted: 07 Apr 2021
Published online: 05 May 2022 *

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