@inbook{f699f56a60f14074bacb3f8924d0392b,
title = "A neural network observer for injection rate estimation in common rail injectors with Nozzle wear",
abstract = "The objective of this study is to present a neural observer that estimates 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; network 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 the altered plant and therefore demonstrate the significant benefit of using the proposed neural network observer concept.",
keywords = "Diesel injector, Injection rate estimation, Injector aging, Neural network observer, Nozzle wear",
author = "Oliver Hofmann and Manuel Kiener and Daniel Rixen",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2019.",
year = "2018",
doi = "10.1007/978-3-319-91217-2_19",
language = "English",
series = "Lecture Notes in Mechanical Engineering",
publisher = "Pleiades journals",
pages = "277--289",
booktitle = "Lecture Notes in Mechanical Engineering",
}