Experimental investigation and neural network prediction of brakes and clutch material frictional behaviour considering the sliding acceleration influence

The developers of innovative automotive active systems have recently stimulated new interest toward the analysis of the frictional behaviour of brake and clutch facings.This paper presents the experimental results acquired with a laboratory setup on brake and clutch facing samples in sliding motion for different operating conditions. An artificial neural network has been used to obtain a comprehensive view of the influence of the main sliding parameters.The study has also taken into account the not weak influence of the sliding acceleration to improve the friction coefficient prediction during transient operations of these dry friction based devices.

► The paper presents the frictional results on brake and clutch facings carried out on a pin-on-disc setup.
► An artificial neural network has been used to get comprehensive view of the physical parameters influence.
► The influences of sliding speed, sliding acceleration and contact pressure have been considered.
► The test patterns have been designed to take into account the acceleration-dependent part of friction force in unsteady-state sliding.
► Detailed frictional maps could improve the performance of the control strategies of several mechatronic automotive systems.