Torque characteristic of SI engine in dynamic operating states

Piotr Bera

doi:10.19206/ce-2017-429

Abstract

The article presents torque characteristic of the engine in dynamic operating conditions as a function of engine speed and throttle opening angle. All mentioned parameters are analyzed as independent variables over time. To develop such a characteristic an artificial neural network is used. The training data were obtained from measurements carried out on the test bench on SI engine. The operating states reflect all possible configurations of these parameters, which may occur during use of the vehicle in real traffic conditions. The article shows design of an artificial neural network that allows to designate the required dependences. Moreover, it describes the fit of the model to the measurement data, which clearly indicates its correctness. Then the developed characteristic in dynamic states is compared with the characteristic in static working states. The differences between them for selected cases of engine operation states are presented. It shows the versatility of the presented method.

Highlights

Internal combustion engines used to propel automotive vehicles work mainly under dynamic working states
On a basis of such measurements engine characteristics are determined and saved in ECU. One of such characteristics is engine torque characteristic that in static states is a function of engine speed and throttle opening angle
Engine test bed measurements Measurements in dynamic states must be performed on the engine test bed that ensures rapid changes of both drag torque and throttle opening angle

Summary

Introduction

Internal combustion engines used to propel automotive vehicles work mainly under dynamic working states. All engine characteristics should be based on measurements in dynamic working states. On a basis of such measurements engine characteristics are determined and saved in ECU One of such characteristics is engine torque characteristic that in static states is a function of engine speed and throttle opening angle. Only input (throttle angle and engine speed) and output (engine torque) parameters were measured in dynamic and static states and analyzed in time intervals. Measurement methodology was described in details by the author in works [2, 3]. These data are analyzed with use on ANN trained in supervised mode

Engine torque characteristic in static states

Engine torque characteristic in dynamic states

Findings

Summary and conclusions