Ignition Timing Map Calibration Based on Nonlinear Dynamic System Identification Using NARX Neural Network

Abstract

The main topic of this paper is presentation of methodology for process identification and mathematical modeling of a nonlinear dynamic system, such as an IC engine, based on the experimental data acquired during base engine calibration in terms of ignition timing. With the introduction of certain assumption, mathematical model generated in this way could be used for verification of potentially optimal look-up tables and for look-up tables smoothing. For this type of time-series modeling, nonlinear autoregressive network with exogenous inputs will be used and full-factorial sweep of limited set of neural network parameters will be analyzed. Guidelines for mathematical model formation, verification and idea of stationary-based engine calibration will be briefly outlined. Comparison between measured and modeled engine torque will be shown alongside with instructions for further research on this topic.