Numerical Prediction of Cyclic Variability in a Spark Ignition Engine Using a Parallel Large Eddy Simulation Approach
- Argonne National Laboratory,9700 S Cass Avenue,Lemont, IL 60439e-mail: mameen@anl.gov
- Politecnico di Torino,c.so Duca degli Abruzzi, 24,Torino 10129, Italye-mail: mohsen.mirzaeian@polito.it
- Politecnico di Torino,c.so Duca degli Abruzzi, 24,Torino 10129, Italye-mail: federico.millo@polito.it
- Argonne National Laboratory,9700 S Cass Avenue,Lemont, IL 60439e-mail: ssom@anl.gov
Cycle-to-cycle variability (CCV) is detrimental to IC engine operation and can lead to partial burn, misfire, and knock. Predicting CCV numerically is extremely challenging due to two key reasons. First, high-fidelity methods such as large eddy simulation (LES) are required to accurately resolve the in-cylinder turbulent flow field both spatially and temporally. Second, CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. Ameen et al. (2017, "Parallel Methodology to Capture Cyclic Variability in Motored Engines,"Int. J. Engine Res., 18(4), pp. 366-377.) developed a parallel perturbation model (PPM) approach to dissociate this long time-scale problem into several shorter time-scale problems. This strategy was demonstrated for motored engine and it was shown that the mean and variance of the in-cylinder flow field was captured reasonably well by this approach. In the present study, this PPM approach is extended to simulate the CCV in a fired port-fuel injected (PFI) spark ignition (SI) engine. The predictions from this approach are also shown to be similar to the consecutive LES cycles. It is shown that the parallel approach is able to predict the coefficient of variation (COV) of the in-cylinder pressure and burn raterelated parameters with sufficient accuracy, and is also able to predict the qualitative trends in CCV with changing operating conditions. It is shown that this new approach is able to give accurate predictions of the CCV in fired engines in less than one-tenth of the time required for the conventional approach of simulating consecutive engine cycles.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technology; USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Bioenergy Technologies Office (BETO)
- DOE Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1461465
- Journal Information:
- Journal of Energy Resources Technology, Vol. 140, Issue 5; ISSN 0195-0738
- Publisher:
- ASME
- Country of Publication:
- United States
- Language:
- English
Similar Records
PARALLEL PERTURBATION MODEL FOR CYCLE TO CYCLE VARIABILITY PPM4CCV
Parallel methodology to capture cyclic variability in motored engines