A novel hyperbolic tangent sliding mode observation of vehicle lateral force fed back by longitudinal force error

Autor: Yunchao Wang, Siyi Huang, Shurong Zhou, Yun Liu
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: The Journal of Engineering, Vol 2023, Iss 5, Pp n/a-n/a (2023)
Druh dokumentu: article
ISSN: 2051-3305
DOI: 10.1049/tje2.12275
Popis: Abstract The tyre lateral force control is crucial to vehicle lateral stability. Vehicle side slip and out of control can be prevented effectively by observing accurately the lateral force. Thus, a novel quasi‐sliding mode observer (QSMO) is proposed. The algorithm adopts the longitudinal tyre force error as feedback considering vehicle parameter uncertainties and without a complex tyre model. First, the on‐line verification of the algorithm was carried out by dSPACE for using the experimental data of the real vehicle linear acceleration and deceleration conditions, and comparison of experimental output with different observation algorithms. Further, the simulation under emergency obstacle avoidance conditions and the double‐line shifting conditions were conducted to verify the accuracy of the algorithm respectively. Simulation results show that the percentage errors between the tyre lateral forces from the proposed QSMO and the actual data are less than 5.35%, and the prediction accuracy of the QSMO by 38.78% is higher than that of the conventional first‐order SMO (FSMO), which indicates that the QSMO is superior to the FSMO.
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