Abstract: In order to achieve optimal control of the automotive anti-lock controller based on slip ratio identification,an optimal slip ratio identification estimator is designed based on the Kiencke μ-S model using an improved forgetting factor recursive least squares algorithm,and the estimation results of the identification estimator regarding the optimal slip ratio and peak adhesion coefficient are compared with those under the Burckhardt μ-S model.The discriminative estimator is applied to the fuzzy sliding mode controller of the automotive anti-lock braking system,and simulation experiments are conducted under single pavement and variational pavement conditions.The experimental results show that the discriminative estimator has small errors and delays,and the anti-lock controller based on the optimal slip ratio identification can achieve online identification and fast tracking of the optimal slip ratio and effectively improve the braking efficiency.

Key words: optimal slip ratio, identification estimator, Kiencke μ-S model, recursive least square method, forgetting factor