PREDICTION OF SUSPENSION RESOURCEVEHICLE

Abstract

The issues of forecasting the resource of the suspension from the leaf spring of the vehicle using energy consumption during cyclic loading are presented. A refined formula for calculating energy consumption is given, which has a closer connection with failures of parts in operating conditions than kilometers of mileage. It is shown that when the vehicle is moving, the suspension is loaded and unloaded, described by the «hysteresis loop» calculation method. The area of the hysteresis loop is used in predicting the suspension resource using a neural network. This makes it possible to increase the utilization rate of the vehicle by reducing costs and downtime during current repairs.