The Journal of Engineering (May 2023)

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

  • Yunchao Wang,
  • Siyi Huang,
  • Shurong Zhou,
  • Yun Liu

DOI
https://doi.org/10.1049/tje2.12275
Journal volume & issue
Vol. 2023, no. 5
pp. n/a – n/a

Abstract

Read online

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.

Keywords