ICAT, November 13-14 2008

Outline Background, motivation and goals Heat Transfer in Engines Heat Transfer Correlations: Woschni, Assanis and Hohenberg HTCs Double-wiebe function for HCCI models Results Conclusions

Background and problem statement The ultimate aim of this work is to model the effect of combustion chamber deposits on the thermal environment of the engine and to validate the results by our experimental results. Combustion models are generally developed for conventional engines. These models need to be modified to be able to model HCCI conditions. Combustion in HCCI engines is a controlled auto-ignition of well-mixed, air and residual gas. Thermal conditions of the combustion chamber are governed by chemical kinetics strongly coupled with heat transfer from the hot gas to the walls. The heat losses have a critical effect on HCCI ignition timing and burning rate, thus it is essential to understand heat transfer process in the combustion chamber in the modelling of HCCI engines.

Heat Transfer from gas to walls

Heat Transfer correlations Woschni:

Heat Transfer correlations Characteristic velocity in Woschni:

Heat Transfer correlations Assanis (Modified Woschni)

Heat Transfer correlations Hohenberg

Heat Transfer correlations Generic Form

Heat Transfer correlations Generic Form

Heat Transfer correlations Single Generic Form

Heat Transfer correlations Single Generic Form

Results Single Generic Form Normalized charasteristic length scale profiles

Normalized charasteristic velocity profiles

Normalized temperature profiles

Normalized pressure profiles

Variation of velocity term for each model

Effect of C2 on heat transfer coefficient for Assanis model

Variation of heat transfer coefficient traces

Heat transfer coefficient traces for different heat transfer models

Heat flux traces for different heat transfer models

Measured and predicted cylinder pressure traces for different conditions

Wiebe function

Double-Wiebe function

Results- The Differences Wiebe functions with different m values for a burn duration of 10 CAD and 50% heat release at TDC

Results- The Differences Late Combustion :

Mass fraction burned traces Results- The Differences Mass fraction burned traces

Results- Experimental validation Measured and predicted cylinder pressure traces

Net heat release traces Results- Experimental validation Net heat release traces

Conclusions – Wiebe function with the standart Wiebe function, parameters can be adjusted to fit either the time or the value of maximum pressure if 100% combustion is assumed. It is possible to match both quantities if it is allowed less than 100% combustion. It becomes possible to fit both quantities without specifying an unrealistic proportion of unburned fuel if double-Wiebe definition is used. double-Wiebe function gives a lower peak heat-release rate than the standart-Wiebe. Result of the slower combustion of part of the mixture in double-Wiebe function agrees with experimental results as well.

Conclusions – Heat transfer correlations Woschni correlation includes a term representing the combustion compression velocity, which is the bulk gas movement due to compression of the unburned gas by an advancing flame front that is not applicable to HCCI engines. This exaggerates heat transfer rates during combustion and expansion. Assanis correlation is a modified type of Woschni HTC for HCCI engines. Here has movement issue is changed emprically by reducing the magnitude of the combustion velocity. It give very low heat transfer rates for whole engine cycle in our HCCI engine, thus overestimates peak pressures. Hohenberg heat transfer model which has no explicit combustion velocity term, give better aggrement with our experiments than the others.

Conclusions – Heat transfer correlations Although there are differences in the magnitudes obtained by using Assanis and Hohenberg correlations, it is possible to match with our experimental pressure data by adjusting the scaling coefficient as it is done by Assanis. However, it is rather unsatisfactory to adjust coefficients substantially for each different HCCI engine. We prefer not to do any empirical re-adjustment of the model coefficients. Hohenberg is the simplest correlation which needs little adjustment, therefore it may be advantageous to use Hohenberg correlation in HCCI simulations. The existing correlations are developed for SI conditions. It is likely that better correlations could be derived directly by making structural changes that represent more closely the nature of the HCCI process.

Thanks for your attention. I would like to invite you to International Conference on Fuels and Combustion in Engines in Istanbul, September 2009 For more information fce@sakarya.edu.tr www.fce.sakarya.edu.tr