Identification of optimal efficiency exploitation conditions of axial-piston hydraulic motor A2FM type using Artificial Neural Network algorithms

Abstract

The paper presents a calculation methodology of energetic optimal exploitation conditions of axial -piston hydraulic motor A2FM type using Artificial Neural Networks algorithms The aim of the work is to use an artificial neural network system for fast calculations of total efficiency values of analyzed hydraulic motor in function of oil pressure drop ratio and motor speed ratio. On the basis of the developed model, a set of optimum oil pressure values is determined at the set engine operating speed value, at which maximum values of total motor efficiency and optimum exploitation conditions in terms of energy are achieved. Based on the application of Neural Network Fitting app of Matlab R2020b, sample calculations were presented for the A2FM 125 type hydraulic motor from Bosch Rexroth were shown.