Engine Manufacturers Leverage Simulation to Engineer Ahead of Increasing Regulations

Environmental agencies, such as the EPA in the United States, play a vital role in controlling nitrogen oxide (NOx) emissions by setting limitations on airborne pollutants that harm public health and the environment. These standards have grown more stringent in recent years for heavy duty and/or road diesel trucks, particularly for engine-out NOx emissions, as shown in Figure 1. It is essential for internal combustion engine (ICE) manufacturers to accurately predict and control engine-out NOx emissions under various operating conditions during the design phase to meet these standards.

Figure 1: US EPA NOx emission standards for heavy-duty or road diesel trucks over the years.

Why GT-SUITE Should Be Your Go-To Simulation Platform for NOx prediction  

Accurate prediction of engine-out NOx emissions of IC engines requires capturing the in-cylinder interactions among fuel injection, turbulence, chemistry, piston motion, and wall heat transfer. These interactions can lead to the creation of in-cylinder stratification, as shown in Figure 2, which significantly impacts the engine’s NOx emission. 

Figure 2: A conceptual model of diesel spray showing in-cylinder stratification in a conventional diesel engine

This is where simulation modeling comes into play. Here are some modeling methods: 

3D, computational fluid dynamic (CFD) simulations can possibly provide better accuracy in capturing these interactions. However, these simulations can become computationally time-consuming, especially when trying to evaluate hundreds (or thousands) of designs and  operating conditions.  

An alternative approach is to use reduced-dimensional models, such as zero-dimensional stochastic reactor models (0D-SRM). These models represent the engine cylinder by hundreds of notional particles, providing a high-fidelity framework to capture in-cylinder stratification using detailed chemistry and accurate mixing models. A 0D-SRM model runs much faster than 3D-CFD simulations, making it a more feasible option for evaluating large numbers of designs and operating conditions. These 0D-SRM models can provide a good trade-off between accuracy and computational cost, making them a useful tool for diesel engine designers and researchers.  

Powerful simulation software, such as Gamma Technologies’ GT-SUITE, can be used to predict engine performance and engine-out emissions. It has an implemented zero-dimensional (0D) stochastic reactor model (SRM) that can predict engine performance and engine-out NOx emissions accurately using detailed chemistry [1]. The animation in Figure 3 demonstrates how the 0D-SRM model captures the in-cylinder inhomogeneity using hundreds of notional particles. This model has been extensively validated against experimental data, making it a reliable tool for predicting engine-out NOx emissions. 

Figure 3a: Distribution of equivalence ratio versus temperature.

Figure 3b: Distribution of mass at different equivalence ratio bins using the 0D-SRM model of the GT-SUITE software. Here the 0D-VCF-tPDF model represents 0D-SRM model.

In addition, GT-SUITE offers the ability to optimize the chemical reaction rates during a simulation, which can be particularly useful for improving emission prediction under different designs and operating conditions. In a study [2], different approaches were proposed to improve the accuracy of engine-out NOx predictions by optimizing the chemical reaction rate parameters (see Figure 4).  

Figure 4: GT-SUITE predicted the peak pressure, CA50, and NOx emissions for a GM diesel engine, and a comparison with 3D-CFD results is also provided [2].

Learn More About GT-SUITE’s Combustion Modeling 

Learn more about combustion and emission simulation solutions here.  If you are interested in using GT-SUITE for engine-out emission modeling needs, we encourage you to reach out and speak to a GT expert. 

References 

[1] Paul, C., Jin, K., Fogla, N., Roggendorf, K. et al., “A Zero-Dimensional Velocity-Composition-Frequency Probability Density Function Model for Compression-Ignition Engine Simulation,” SAE Int. J. Adv. & Curr. Prac. in Mobility 2(3):1443-1459, 2020, https://doi.org/10.4271/2020-01-0659. 

[2] Paul C, Gao J, Jin K, Patel D, Roggendorf K, Fogla N, Parrish S E, Wahiduzzaman S, An indirect approach to optimize the reaction rates of thermal NO formation for diesel engines, Fuel 338 (2023) 127287, https://doi.org/10.1016/j.fuel.2022.127287.