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Heavy-duty vehicles, currently the second largest source of fuel consumption and carbon emissions are projected to be fastest growing mode in transportation sector in future. There is a clear need to increase fuel efficiency and lower emissions for these engines. The Opposed-Piston Engine (OP Engine) has the potential to address this growing need. In this paper, results are presented for a 9.8L three-cylinder two-stroke OP Engine that shows the potential of achieving 55% brake thermal efficiency (BTE), while simultaneously satisfying emission targets for tail pipe emissions. The two-stroke OP Engines are inherently more cost effective due to less engine parts. The OP Engine architecture presented in this paper can meet this performance without the use of waste heat recovery systems or turbo-compounding and hence is the most cost effective technology to deliver this level of fuel efficiency.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

The government of India has decided to implement Bharat Stage VI (BS-VI) emissions standards from April 2020. This requires OEMs to equip their diesel engines with costly after-treatment, EGR systems and higher rail pressure fuel systems. By one estimate, BS-VI engines are expected to be 15 to 20% more expensive than BS-IV engines, while also suffering with 2 to 3 % lower fuel economy. OEMs are looking for solutions to meet the BS-VI emissions standards while still keeping the upfront and operating costs low enough for their products to attract customers; however traditional engine technologies seem to have exhausted the possibilities. Fuel economy improvement technologies applied to traditional 4-stroke engines bring small benefits with large cost penalties. One promising solution to meet both current, and future, emissions standards with much improved fuel economy at lower cost is the Opposed Piston (OP) engine.

Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

The low temperature combustion concept is very attractive for reducing NOx and soot emissions in diesel engines. However, it has potential limitations due to higher combustion noise, CO and HC emissions. A multiple injection strategy is an effective way to reduce unburned emissions and noise in LTC. In this paper, the effect of multiple injection strategies was investigated to reduce combustion noise and unburned emissions in LTC conditions. A hybrid surrogate fuel model was developed and validated, and was used to improve LTC predictions. Triple injection strategies were considered to find the role of each pulse and then optimized. The split ratio of the 1st and 2nd pulses fuel was found to determine the ignition delay. Increasing mass of the 1st pulse reduced unburned emissions and an increase of the 3rd pulse fuel amount reduced noise. It is concluded that the pulse distribution can be used as a control factor for emissions and noise.

This paper presents analytical and measured results on the effects of injection pattern design on piston thermal management in an Opposed-Piston, Two-Stroke (OP2S) diesel engine. The OP2S architecture investigated in this work comprises two opposing pistons forming an asymmetric combustion chamber with two opposing injectors mounted on the cylinder wall. This unique configuration offers opportunities to tailor the injection pattern to control the combustion heat flux and resulting temperatures on the piston surfaces while optimizing combustion simultaneously. This study utilizes three-dimensional (3D) computational fluid dynamics (CFD) with state-of-the-art spray, turbulence and combustion models that include detailed chemistry to simulate the in-cylinder combustion and the associated flame/wall interactions. In addition, the measurements comprise a real-time thermocouple system, which allows for up to 14 locations to be monitored and recorded on the intake and exhaust pistons.

The more and more severe regulations on exhaust emissions from vehicles and the worldwide demand for fuel consumption reduction impose continuous improvements of the engine thermal efficiency. Base engine geometrical setups are important aspects which have to be taken into account to improve the engine efficiency. This paper discusses the influence of the bore-to-stroke ratio on emissions, fuel consumption and full load performances of a Diesel engine. The expected advantage of a reduced bore-to-stroke ratio is mainly a decrease of the thermal losses, due to a higher volume-to-surface ratio, reducing the wall surfaces, responsible for the heat losses, per volume of gas. The advantages concerning the wall heat losses are opposed to the disadvantages of lower volumetric efficiency, as a smaller bore requires smaller valve diameter. Additionally does a reduction of the bore-to-stroke ratio lead to an increase of the friction losses, as the mean piston speed increases.

Traditional Lagrangian spray modeling approaches for internal combustion engines are highly grid-dependent due to insufficient resolution in the near nozzle region. This is primarily because of inherent restrictions of volume fraction with the Lagrangian assumption together with high computational costs associated with small grid sizes. A state-of-the-art grid-convergent spray modeling approach was recently developed and implemented by Senecal et al., (ASME-ICEF2012-92043) in the CONVERGE software. The key features of the methodology include Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, which enables use of cell sizes smaller than the nozzle diameter. This modeling approach was rigorously validated against non-evaporating, evaporating, and reacting data from the literature.

Diesel fuels are complex mixtures of thousands of hydrocarbons. Since modeling their combustion characteristics with the inclusion of all hydrocarbon species is not feasible, a hybrid surrogate model approach is used in the present work to represent the physical and chemical properties of three different diesel fuels by using up to 13 and 4 separate hydrocarbon species, respectively. The surrogates are arrived at by matching their distillation profiles and important properties with the real fuel, while the chemistry surrogates are arrived at by using a Group Chemistry Representation (GCR) method wherein the hydrocarbon species in the physical property surrogates are grouped based on their chemical classes, and the chemistry of each class is represented by using up to two hydrocarbon species.

A state-of-the-art spray modeling methodology, recently applied to RANS simulations, is presented for LES calculations. Key features of the methodology, such as Adaptive Mesh Refinement (AMR), advanced liquid-gas momentum coupling, and improved distribution of the liquid phase, are described. The ability of this approach to use cell sizes much smaller than the nozzle diameter is demonstrated. Grid convergence of key parameters is verified for non-evaporating and evaporating spray cases using cell sizes down to 1/32 mm. It is shown that for global quantities such as spray penetration, comparing a single LES simulation to experimental data is reasonable, however for local quantities the average of many simulated injections is necessary. Grid settings are recommended that optimize the accuracy/runtime tradeoff for LES-based spray simulations.

The present work proposes a methodology for diesel engine development using scaling laws and computational optimization with multi-dimensional CFD tools. A previously optimized 450cc HSDI diesel engine was down-scaled to 400cc size using recently developed scaling laws. The scaling laws were validated by comparing the performance of these two engines, including pressure, HRR, peak and averaged temperature, and pollutant emissions. A novel optimization methodology, which is able to simultaneously optimize multiple operating conditions, was proposed. The method is based on multi-objective genetic algorithms, and was coupled with the KIVA3V Release 2 code to further optimize the down-scaled diesel engine. An adaptive multi-grid chemistry model was used in the KIVA3V code to reduce the computational cost of the optimization. The computations were conducted using high-throughput computing with the CONDOR system.

The present work proposes a methodology for diesel engine development using multi-dimensional CFD and computer optimization. A multi-objective genetic algorithm coupled with the KIVA3V Release 2 code was used to optimize a high speed direct injection (HSDI) diesel engine for passenger car applications. The simulations were conducted using high-throughput computing with the CONDOR system. An automated grid generator was used for efficient mesh generation with 11 variable piston bowl geometry parameters. The first step in the procedure was to search for an optimal nozzle and piston bowl design. In this case, spray targeting, swirl ratio, and piston bowl shape were optimized separately for two full-load cases using simpler efficient combustion models (the characteristic time scale model and the shell ignition model). The optimal designs from the two optimizations were then validated using a combustion model with detailed chemistry (KIVA-CHEMKIN model and ERC n-heptane mechanism).

A multi-objective genetic algorithm coupled with the KIVA3V release 2 code was used to optimize the piston bowl geometry, spray targeting, and swirl ratio levels of a high speed direct injected (HSDI) diesel engine for passenger cars. Three modes, which represent full-, mid-, and low-loads, were optimized separately. A non-dominated sorting genetic algorithm II (NSGA II) was used for the optimization. High throughput computing was conducted using the CONDOR software. An automated grid generator was used for efficient mesh generation with variable geometry parameters, including open and reentrant bowl designs. A series of new spray models featuring reduced mesh dependency were also integrated into the code. A characteristic-time combustion (CTC) model was used for the initial optimization for time savings. Model validation was performed by comparison with experiments for the baseline engine at full-, mid-, and low-load operating conditions.

In the present work the three-dimensional KIVA CFD code was used to simulate the combustion process in a HSDI diesel engine. State-of-the-art models, including the KH-RT spray breakup model, the RNG k-ε turbulence model, and a n-heptane reduced chemistry including reduced GRI NOx mechanism were used. The performances of two combustion models, KIVA-CHEMKIN and GAMUT (KIVA-CHEMKIN-G), coupled with 2-step and multi-step phenomenological soot models were compared. The numerical results were compared with available experimental data obtained from an optically accessible HSDI engine and good agreement was obtained. To assess the effects of the in-cylinder flow field on combustion and emissions, off-centered swirl flows were also considered. In these studies, the swirl center was initialized at different positions in the chamber for different cases to simulate the effects of different intake flow arrangements.

A new Computational Fluid Dynamics (CFD) code has been developed in order to overcome the deficiencies of traditional grid generation and mesh motion methods. The new code uses a modified cut-cell Cartesian technique that eliminates the need for the computational grid to coincide with the geometry of interest. The code also includes state-of-the-art numerical techniques and sub-models for simulating the complex physical and chemical processes that occur in engines. Features such as shared and distributed memory parallelization, a multigrid pressure solver and user-specified grid embedding allow for efficient simulations while maintaining the grid resolution necessary for accurate engine modeling. In addition, a new Adaptive Grid Embedding (AGE) technique has been developed and implemented. Sub-models for turbulence, spray injection, spray breakup, liquid drop dynamics, ignition, combustion and emissions are also included in the code.

To facilitate the growing interest in hydrogen combustion for internal combustion engines, computer models are being developed to simulate gaseous fuel injection, air entrainment and the ensuing combustion. This paper introduces a new method for modeling the injection and air entrainment processes for gaseous fuels. Modeling combustion is not covered in this paper. The injection model uses a gaseous sphere injection methodology, similar to liquid droplet injection techniques used for liquid fuel injection. In this paper, the model concept is introduced and model results are compared with correctly- and under-expanded experimental data.

The heavy-duty diesel engine industry is required to meet stringent emission standards. There is also the demand for more fuel efficient engines by the customer. In a previous study on an engine with variable intake valve closure timing, the authors found that an early single injection and accompanying premixed charge compression ignition (PCCI) combustion provides advantages in emissions and fuel economy; however, unacceptably high peak pressures and rates of pressure-rise impose a severe operating constraint. The use of a Pressure Reactive Piston assembly (PRP) as a means to limit peak pressures is explored in the present work. The concept is applied to a heavy-duty diesel engine and genetic algorithms (GA) are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to provide an optimized set of operating variables.

Recent measurements by Siebers et al. have shown that the flame of a high pressure Diesel spray stabilizes under quiescent conditions at a location downstream of the fuel injector. The effects of various ambient and injection parameters on the flame “lift-off” length have been investigated under typical Diesel conditions in a constant-volume combustion vessel. In the present study, the experiments of Siebers et al. have been modeled using a modified version of the KIVA-3V engine simulation code. Fuel injection and spray breakup are modeled using the KH-RT model that accounts for liquid surface instabilities due to the Kelvin-Helmholtz and Rayleigh-Taylor mechanisms. Combustion is simulated using Convergent Thinking's recently developed detailed transient chemistry solver (SAGE) that allows for any number of chemical species and reactions to be modeled.

The present study extends the recently developed KIVA-GA computer code to incorporate a generalized piston bowl geometry parameterization and multi-mode optimization. The new code was used to optimize the combustion chamber geometry of a small-bore automotive Diesel engine. The Genetic Algorithm (GA) merit function, which was calculated with a modified version of the KIVA-3V engine simulation code, included NOx, unburned HC, soot, and fuel consumption. A novel parameterization was included in KIVA-GA that allows for a variable number of parameters to define the bowl shape. The in-house G-Smooth grid generation package was used to create the KIVA grids with a specified compression ratio and mesh resolution. The improved KIVA-GA methodology was used to optimize engine emissions and performance simultaneously for two operating conditions.

A model is developed based on Lagrangian-drop and Eulerian-fluid procedure to simulate fuel spray structure and the interaction of spray with in-cylinder gas motion. The hollow cone spray is modeled assuming the sheet consisting of blobs of droplets and these blobs are further subjected to secondary breakup. The droplet equations of position, momentum and temperature have been solved by the fourth order Runge-Kutta scheme. The gas phase compressible flow is solved using the finite volume method in conjunction with the SIMPLEC algorithm. The coupling between gas phase and the liquid phase has been achieved through the source terms arising in each phase. Three-dimensional spray and interaction with air motion inside the cylinder have been performed. The results show that the spray structure is well simulated. The model predicts the entrained air velocities and the fuel vapour concentration distribution as a function of time.