Abstract
The prospect of analysis-driven pre-calibration of a modern diesel engine is extremely valuable in order to significantly reduce hardware investments and accelerate engine designs compliant with stricter EPA fuel economy regulations. Advanced modeling tools, such as CFD, are often used with the goal of streamlining significant portions of the calibration process. The success of the methodology largely relies on the accuracy of analytical predictions, especially engine-out emissions. However, the effectiveness of CFD simulation tools for in-cylinder engine combustion is often compromised by the complexity, accuracy, and computational overhead of detailed chemical kinetics necessary for combustion calculations. The standard approach has been to use skeletal kinetic mechanisms (~50 species) which consume acceptable computational time but with degraded accuracy. In this work, a comprehensive demonstration and validation of the analytical pre-calibration process is presented for a passenger car diesel engine using CFD simulations with CONVERGETM and a GPU-based chemical kinetics solver (Zero-RK, developed at Lawrence Livermore National Laboratory) on high performance computing resources to enable the use of detailed kinetic mechanisms. Diesel engine combustion computations have been conducted over 600 operating points spanning in-vehicle speed-load map, using massively parallel ensemble simulation sets on the Titan supercomputer located at the Oak Ridge Leadership Computing Facility. The results with different mesh resolutions have been analyzed to compare differences in combustion and emissions (NOx, Carbon Monoxide CO, Unburned Hydrocarbons UHC, and Smoke) with actual engine measurements. The results show improved agreement in combustion and NOx predictions with a large n-heptane mechanism consisting of 144 species and 900 reactions with refined mesh resolution; however; agreement in CO, UHC and Smoke remain a challenge.
| Original language | English |
|---|---|
| Title of host publication | Emissions Control Systems; Instrumentation, Controls, and Hybrids; Numerical Simulation; Engine Design and Mechanical Development |
| Publisher | American Society of Mechanical Engineers |
| ISBN (Electronic) | 9780791858325 |
| DOIs | |
| State | Published - 2017 |
| Event | ASME 2017 Internal Combustion Engine Division Fall Technical Conference, ICEF 2017 - Seattle, United States Duration: Oct 15 2017 → Oct 18 2017 |
Publication series
| Name | ASME 2017 Internal Combustion Engine Division Fall Technical Conference, ICEF 2017 |
|---|---|
| Volume | 2 |
Conference
| Conference | ASME 2017 Internal Combustion Engine Division Fall Technical Conference, ICEF 2017 |
|---|---|
| Country/Territory | United States |
| City | Seattle |
| Period | 10/15/17 → 10/18/17 |
Funding
Portions of this work were supported by the U.S. Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy under the Vehicle Technology Office’s (VTO) Advanced Combustion Engines Program and performed at Oak Ridge National Laboratory (ORNL) by UT-Battelle, LLC, under Contract No. DE-AC05-00OR22725 and at Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The authors gratefully acknowledge the support and direction of Leo Breton and Gurpreet Singh at DOE’s VTO. Portions of this work used resources of the Oak Ridge Leadership Computing Facility at ORNL, which is supported by the DOE Office of Science under Contract No. DE-AC05-00OR22725. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).