Estimation of vehicle state and road surface adhesion coefficient based on double square root cubature Kalman filter
by Wei Gao; Wenfei Liu; Zhaowen Deng; Baohua Wang; Youqun Zhao
International Journal of Vehicle Performance (IJVP), Vol. 10, No. 4, 2024

Abstract: With a focus on the problem of estimating the vehicle state and road surface attachment coefficient while in motion, and using distributed drive electric vehicles as the research subject, a double-square-root volumetric Kalman filtering vehicle traveling state and road surface attachment coefficient estimator (DSRCKF) is designed. It is based on the idea of square-root filtering, which introduces the square-root factor of the covariance matrix and updates the process iteratively. Two linked sub-filters that are updated in real-time are present in the estimator. To achieve accurate estimation of the vehicle state and roadway attachment coefficients, a nonlinear seven-degree-of-freedom vehicle model based on the dugoff tyre model is first established. Next, a vehicle simulation platform for distributed-drive electric vehicles is built using the CarSim-Simulink software, and the double-square-root-volume Kalman filtering algorithm is deduced. The DSRCKF estimation method outperforms the DCKF and DUKF algorithms after the created algorithm has been simulated and tested under typical operating conditions.

Online publication date: Mon, 07-Oct-2024

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