Abstract
This chapter presents several examples of engine optimization using multi-dimensional CFD and genetic algorithms. The examples in the first part use simple combustion models to benefit efficiency. The ones in the second part use detailed chemistry for better accuracy, especially for the cases in which the simple combustion models fail. The third part discusses strategies for simultaneous optimization of multiple operating conditions. The fourth part presents a methodology that combines scaling laws and computational optimization for engine development.
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Notes
- 1.
GISFC refers to the work delivered to the piston over compression and expansion strokes, i.e., from BDC to TDC to BDC. In the present work, “GISFC” is defined as the output work from IVC to EVO for convenience. Apparently, there is a difference between these two “GISFC”. This difference is a constant for the same engine and same operating conditions. Therefore it will not affect the results and conclusions.
- 2.
According to NEDC emission tests (Schmidt 2008), NOx emissions are not considered under full-load conditions. Since soot emission is usually proportional to GISFC, only GISFC was considered.
- 3.
In Chap. 5, different initial temperatures were used to take into account the different heat transfer between engines of different sizes. Since the scaling factor in this section is close to unity, the corresponding volume-to-area ratios of the two engines are similar and thus the same initial temperatures were used in this section.
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© 2011 Springer-Verlag London Limited
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Shi, Y., Ge, HW., Reitz, R.D. (2011). Applications. In: Computational Optimization of Internal Combustion Engines. Springer, London. https://doi.org/10.1007/978-0-85729-619-1_6
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DOI: https://doi.org/10.1007/978-0-85729-619-1_6
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