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Incorporating Design Variation into a 1-D Analytical Model of a 4.6L-4V Ford Engine for Improving Performance Projections
ISSN: 0148-7191, e-ISSN: 2688-3627
Published October 29, 2007 by SAE International in United States
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One-dimensional simulation tools are used extensively in the automotive industry to improve and optimize engine design for WOT performance. They are useful in target setting and in assessing the effects of certain design changes (e.g. intake manifold, valve timing, exhaust manifold, etc.). Generally the inputs to these models are “nominal” values or curves from a particular set of data and, therefore, do not take into account design or assembly variations. Often times, performance expectations are not met due to these “real world” effects and may result in significant re-design and testing efforts.
The purpose of this paper is to assess the impact of typical model input variation on engine performance and to instill greater confidence in the use of these models in forecasting performance. The approach taken is to collect, analyze, and categorize actual build measurements from a 4.6L 4V Ford engine that are considered important inputs for a one-dimensional modeling. From these inputs Monte Carlo simulations are run through the one-dimensional model to produce a range of performance output. The output is then analyzed via statistical methods to assess the impact of each input on engine performance variance.
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CitationDaniels, C. and Miazgowicz, K., "Incorporating Design Variation into a 1-D Analytical Model of a 4.6L-4V Ford Engine for Improving Performance Projections," SAE Technical Paper 2007-01-4098, 2007, https://doi.org/10.4271/2007-01-4098.
- Gamma Technologies GT-Power User's Manual, GT-Suite Version 6.1 August 2004 9 121 123
- Ricardo Wave Basic Manual, User's Manual version 3.5 November 1999 1 1
- Heywood, J. Internal Combustion Engine Fundamentals McGraw-Hill 1988 209 249
- Heywood, J. Internal Combustion Engine Fundamentals McGraw-Hill 1988 177 197
- Obert, E. Internal Combustion Engines and Air Pollution Harper & Row 1973 2 522
- Shen, j. “Software Review: Tolerance Analysis with EDS/VisVSA,” ASME Journal of Computer and Information Science in Engineering 2003
- Stephens, M. Tests of Fit for the Logistic Distribution Based on the Empirical Distribution Function Biometrika 66 591 595 1979
- Snedecor, G. Cochran, W. Statistical Methods 8th Iowa State University Press 1989
- Levene, H. Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling Olkin I. et al. eds. Stanford University Press 278 292 1960
- Walpole, R. Myers, R. Probability and Statistics for Engineers and Scientists 2nd MacMillian 1978
- Railton, J. Batty A. Hypothesis Testing Road Map Sep 7 2000
- Taylor, C. The Internal Combustion Engine in Theory and Practice 1 2nd The M.I.T. Press 1986 312 314
- Neter, J. Wasserman, W. Kutner, M. Applied Linear Statistical Models 2nd Irwin 1985 798 819
- Miller, I. Freund, J. Probability and Statistics for Engineers 3rd Prentice-Hall 1985 290 327
- Montgomery, D. Design and Analysis of Experiments 3rd John Wiley & Sons 1991 205 206