Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-11246
Authors: Xie, Yijiang
Title: Automatische Applikation modellbasierter Diesel-Luftsystem-Funktionen in Motorsteuergeräten
Issue Date: 2020
metadata.ubs.publikation.typ: Dissertation
metadata.ubs.publikation.seiten: xi, 163
URI: http://elib.uni-stuttgart.de/handle/11682/11263
http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-112638
http://dx.doi.org/10.18419/opus-11246
Abstract: The continuous development of diesel engines for meeting the legal and functional requirements, e.g. reducing emissions and fuel consumption while taking drivability into account, has led to a significant increase in the number of sensors and actuators required for the engine. For the diesel-air system it means to introduce a turbocharger, a system for exhaust gas recirculation (EGR), an exhaust gas aftertreatment system, a variable valve control, etc. In order to control such an increasingly complex system in diesel engines, ECU-functions are developed by means of a model-based approach. The success of a model-based development methodology is based on a precise and e cient modeling of the relevant engine behavior. Because of the limited computing power of an ECU, a combination of physical models and so-called calibration parameters is usually preferred for engine modeling. The calibration parameters can be scalar or one or two-dimensional empirical models and usual ly have to be determined (calibrated) by experiments on an engine test bench. Typical examples for such calibration parameters are lookup-tables for modeling the cylinder charge (volumetric e ciency) and the e ective area of the EGR valve. In this thesis a procedure is proposed which is able to calibrate the ECU functions for stationary relationships, e.g. in the diesel-air system, automatically and with as little measurement e ort as possible in terms of the number of measurement points. The algorithm runs within the framework of sequential experimental planning, in which Gaussian models with non-stationary covariance functions are used to approximate the relations of interest. For adaptive experimental planning an active sampling strategy is developed based on the concept of mutual information and optimal system inputs (engine speed, fuel quantity, air actuators, etc.) and which determines the resulting operating points, with respect to the input space coverage, the inhomogeneous properties of the relations, the uncertainty of the estimated calibration parameters and the feasibility of the operating points. The method is able to predict the stationary engine behavior, which results from the selected system inputs, by means of the physical structure of the air system and the data-based models of the calibration parameters. On this basis the uncertainties of the application parameters are estimated using extended Kalman filters. The feasibility of the operating point is checked by comparing the predicted system behavior with the engine limits. For validation the developed algorithm was implemented on an engine test bench to calibrate the air system of a diesel engine equipped with high and low pressure EGR, a variable geometry turbocharger and variable valve timing. As a result, using the presented approach, using as little as approx. 130 measurement points is enough to obtain a comparable application quality to that achieved by conventional methods with more than 800 measurement points.
Appears in Collections:07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

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