Application of an inverse data-driven model for reconstructing wheel movement signals

This paper considers a method for indirect measuring the vertical displacement of wheels resulting from the road profile, using an inverse parametric data-driven model. Wheel movement is required in variable damping suspension systems, which use an onboard electronic control system that improves ride quality and vehicle handling in typical maneuvres. This paper presents a feasibility study of such an approach which was performed in laboratory conditions. Experimental validation tests were conducted on a setup consisting of a servo-hydraulic test rig equipped with displacement, force and acceleration transducers and a data-acquisition system. The fidelity and adequacy of various parametric SISO model structures were evaluated in the time domain based on correlation coefficient, FPE and AIC criteria. The experimental test results showed that inverse models provide accuracy of inversion, ranging from more than 70% for the ARX model structure to over 90% for the OE model structure.