• SAE-2010-01-0152

Moving Toward Establishing More Robust and Systematic Model Development for IC Engines Using Process Informatics

Authors: Andrew J. Smallbone*, Amit Bhave, Andreas Braumann, Markus Kraft*, Antonis Dris, and Robert M. McDavid

Reference: SAE Paper 2010-01-0152


Analyzing the combustion characteristics, engine performance, and emissions pathways of the internal combustion (IC) engine requires management of complex and an increasing quantity of data. With this in mind, effective management to deliver increased knowledge from these data over shorter timescales is a priority for development engineers. This paper describes how this can be achieved by combining conventional engine research methods with the latest developments in process informatics and statistical analysis. Process informatics enables engineers to combine data, instrumental and application models to carry out automated model development including optimization and validation against large data repositories of experimental data. This is complemented with the inclusion of experimental error and model parameter uncertainty, to yield confidence regimes on the final model result, hence the impact of specific shortcomings of the model and/or experimental dataset can be identified in a systematic manner. A methodology for model implementation is described including an extensible data model for storing engine experimental data in a consistent format. Finally, a working example for an application model is presented through the development of a semi-empirical soot model for diesel engines.

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*Corresponding author:
Telephone: 0191 208 4954
Address: Sir Joseph Swan Centre for Energy Research Newcastle University Newcastle upon Tyne NE1 7RU
Website: Personal Homepage
*Corresponding author:
Telephone: +44 (0)1223 762784 (Dept) 769010 (CHU)
Address: Department of Chemical Engineering and Biotechnology
University of Cambridge
West Cambridge Site
Philippa Fawcett Drive
Cambridge CB3 0AS
United Kingdom
Website: Personal Homepage