Overview
- Automated process for the simulation of new fuels’ combustion
- Extraordinarily high prediction quality for the 0D model class
- Validation for a wide range of (synthetic) fuels
Part of the book series: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart (WRFUS)
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Table of contents (7 chapters)
Keywords
About this book
Sebastian K. Crönert presents a new, automated process that makes it possible to obtain all the fuel properties required for combustion simulation. If necessary, these are then transferred - also automatically - into specially created correlation equations through which they are then made available again at simulation runtime. This method makes it possible to represent even more complex correlations and cross-influences on calculation variables in a resource-optimised way (memory requirements and access time) while maintaining the same accuracy. The procedure is validated using test bench measurement data for the pure fuels anisole and cyclopentanone and their blends with regular petrol (RON95E10). Additional validations include more established synthetic fuels and hydrogen. It is shown that an extraordinarily high prediction quality can be achieved for the model class.
Authors and Affiliations
About the author
Sebastian K. Crönert completed his doctorate at the Institute of Automotive Engineering Stuttgart (IFS) at the University of Stuttgart and continues to work there as a research assistant. His work focuses on reaction kinetic investigations of synthetic fuels, hydrogen and ammonia as well as software engineering and model development.
Bibliographic Information
Book Title: A Complete Methodology for the Predictive Simulation of Novel, Single- and Multi-Component Fuel Combustion
Authors: Sebastian K. Crönert
Series Title: Wissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart
DOI: https://doi.org/10.1007/978-3-658-43075-7
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science and Engineering (German Language)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2023
Softcover ISBN: 978-3-658-43074-0Published: 02 October 2023
eBook ISBN: 978-3-658-43075-7Published: 29 September 2023
Series ISSN: 2567-0042
Series E-ISSN: 2567-0352
Edition Number: 1
Number of Pages: XL, 186
Number of Illustrations: 72 b/w illustrations
Topics: Automotive Engineering, Engine Technology, Industrial Chemistry/Chemical Engineering