Incorporating CFD to Reduce the Development Time of Low NO_x Engine Technologies, 03-R8079

Principal Investigators
Zainal Abidin
Kaushik Das
Debashis Basu
Rainer Rothbauer

Inclusive Dates:  07/01/08 – 07/01/09

Background - It is well known that in-cylinder NO_x formation is a strong function of combustion temperature, where higher temperatures produce higher amounts of NO_x. As such, the primary approach to reducing in-cylinder NO_x  is to use high levels of exhaust gas recirculation (EGR) to reduce combustion temperatures. At higher temperatures, the dominant NO_x  formation mechanism is thermal NO_x , which is characterized well by the Zeldovich mechanism in virtually all CFD models. However, when high levels of EGR are used to drive down the combustion temperature, the NO_x  vs. temperature relationship breaks down and the Zeldovich mechanism no longer accurately predicts NO_x  formation. At these lower temperatures, different mechanisms for NO_x  formation are at work. With respect to the reduction of the NO_x  emissions post-cylinder, two leading NO_x  aftertreatment systems are lean NO_x  traps (LNT) and selective catalytic reduction (SCR) systems. SCR systems are of primary interest to the transportation industry because when properly implemented they offer high levels of NO_x  reduction with no adverse effect on fuel economy. CFD can be used to simulate the SCR system and predict the effect of design variables on the NO_x conversion and ammonia slip. The objectives were to: improve the accuracy of in-cylinder NO_x  prediction under high EGR conditions by improving the NO_x  model; reduce the simulation time of SCR systems by implementing 0-D model for NO_x  and ammonia predictions in place of computationally intensive detailed chemistry.

Approach - A CFD model of a combustion chamber from a Caterpillar C15 engine was used. The approach for the in-cylinder NO_x prediction involves CFD simulation using Converge 3-D CFD software. Different NO_x formation (called "prompt NO_x") models have been implemented to improve the in-cylinder NO_x prediction at low temperature. The models are inserted to the Converge software using a user defined function (UDF). In SCR system modeling, the 3-D domain of SCR is substituted by a 0-D SCR model. A coupling between 0-D and 3-D was developed.

Accomplishments - Of several prompt NO_x models, it was found that the prompt NO_x model of De Soeto shows the best prompt NO_x prediction. Based on measured and simulated data, a correction factor is implemented to the model to increase its accuracy, namely 1.086x10^-2 for low-end-of-injection pressure and 1.211x10^-2 for high end-of-injection pressure. The application of the corrected De Soeto version 1 model in other operating conditions results in maximum error of 4.3 percent. For the SCR model, detailed chemistry process inside the SCR system is substituted by a 0-D empirical model. The research found that the application of 0-D empirical model saves 40 percent of the calculation time.

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