Eventos Anais de eventos
DINAME 2017
XVII International Symposium on Dynamic Problems of Mechanics
A Neural Network Observer for Injection Rate Estimation in Common Rail Injectors with Nozzle Wear
Submission Author:
Oliver Hofmann , Germany , Germany
Co-Authors:
Oliver Hofmann, Manuel Kiener, Daniel Rixen
Presenter: Oliver Hofmann
doi://10.26678/ABCM.DINAME2017.DIN17-0033
Abstract
The objective of this study is to present a neural observer estimating changing injection behavior due to wear and aging effects within the nozzle of a common rail diesel injector. Using a dynamic identification system in combination with a modified learning rule, the neural observer is applicable to a wide range of problem sets. A multilayer perceptron (MLP) network with three-layers and few neurons in the hidden layer ensures fast computing and high efficiency, and learning is based on quasi-Newton optimization and an additional line search algorithm. Modeling the bottom part of the injector introduces a simulation model, which is validated with experimental data from a solenoid common rail diesel injector. Estimation results conform well with to altered plant and therefore demonstrate the significant benefit of using the proposed neural network observer concept.
Keywords
diesel injector, injection rate estimation, neural network observer, nozzle wear
