Identification of Phenomenological Shock Absorber Model Using Neuro-Fuzzy Method

The paper deals with the creation of the phenomenological damper model using the neuro-fuzzy identification algorithm LOLIMOT. The models are identified based on the measured data of passenger car shock absorber. The different variants of model inputs are tested. The damper force of the final model depends statically on relative velocity and relative acceleration inputs. The identified model is implemented into simulation model of the car suspension. The acceleration is resolved from the implicit nonlinear equations in order to preserve causality of differential equations solution.