1. ICAT, November

2. 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

3. 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.

4. Heat Transfer from gas to walls

5. Heat Transfer correlations
Woschni:

6. Heat Transfer correlations
Characteristic velocity in Woschni:

7. Heat Transfer correlations
Assanis (Modified Woschni)

8. Heat Transfer correlations
Hohenberg

9. Heat Transfer correlations
Generic Form

10. Heat Transfer correlations
Generic Form

11. Heat Transfer correlations
Single Generic Form

12. Heat Transfer correlations
Single Generic Form

13. Results Single Generic Form
Normalized charasteristic length scale profiles

14. Normalized charasteristic velocity profiles

15. Normalized temperature profiles

16. Normalized pressure profiles

17. Variation of velocity term for each model

18. Effect of C2 on heat transfer coefficient for Assanis model

19. Variation of heat transfer coefficient traces

20. Heat transfer coefficient traces for different heat transfer models

21. Heat flux traces for different heat transfer models

22. Measured and predicted cylinder pressure traces for different conditions

23. Wiebe function

24. Double-Wiebe function

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

26. Results- The Differences
Late Combustion :

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

28. Results- Experimental validation
Measured and predicted cylinder pressure traces

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

30. 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.

31. 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.

32. 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.

33. 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