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A Machine Learning-Genetic Algorithm (ML-GA) approach was developed to virtually discover optimum designs using training data generated from multi-dimensional simulations. Machine learning (ML) presents a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. In the present work, a total of over 2000 sector-mesh computational fluid dynamics (CFD) simulations of a heavy-duty engine were performed. These were run concurrently on a supercomputer to reduce overall turnaround time. The engine being optimized was run on a low-octane (RON70) gasoline fuel under partially premixed compression ignition (PPCI) mode. A total of nine input parameters were varied, and the CFD simulation cases were generated by randomly sampling points from this nine-dimensional input space. These input parameters included fuel injection strategy, injector design, and various in-cylinder flow and thermodynamic conditions at intake valve closure (IVC).

A 500-hour test cycle has been used to evaluate the durability of a prototype high pressure common rail injection system operating up to 1800 bar with E10 gasoline. Some aspects of the original diesel based hardware design were optimized in order to accommodate an opposed-piston, two-stroke engine application and also to mitigate the impacts of exposure to gasoline. Overall system performance was maintained throughout testing as fueling rate and rail pressure targets were continuously achieved and no physical damage was observed in the low-pressure components. Injectors showed no deviation in their flow characteristics after exposure to gasoline and high resolution imaging of the nozzle spray holes and pilot valve assemblies did not indicate the presence of cavitation damage. The high pressure pump did not exhibit any performance degradation during gasoline testing and teardown analysis after 500 hours showed no evidence of cavitation erosion.

In order to extend the operability limit of the gasoline compression ignition (GCI) engine, as an avenue for low temperature combustion (LTC) regime, the effects of parametric variations of engine operating conditions on the performance of six-stroke GCI (6S-GCI) engine cycle are numerically investigated, using an in-house 3D CFD code coupled with high-fidelity physical sub-models along with the Chemkin library. The combustion and emissions were calculated using a skeletal chemical kinetics mechanism for a 14-component gasoline surrogate fuel. Authors’ previous study highlighted the effects of the variation of injection timing and split ratio on the overall performance of 6S-GCI engine and the unique mixing-controlled burning mode of the charge mixtures during the two additional strokes. As a continuing effort, the present study details the parametric studies of initial gas temperature, boost pressure, fuel injection pressure, compression ratio, and EGR ratio.

Past experimental studies conducted by the current authors on a 13 liter 16.7:1 compression ratio heavy-duty diesel engine have shown that diesel-Compressed Natural Gas (CNG) Reactivity Controlled Compression Ignition (RCCI) combustion targeting low NOx emissions becomes progressively difficult to control as the engine load is increased. This is mainly due to difficulty in controlling reactivity levels at higher loads. For the current study, CFD investigations were conducted in CONVERGE using the SAGE combustion solver with the application of the Rahimi mechanism. Studies were conducted at a load of 5 bar BMEP to validate the simulation results against RCCI experimental data. In the low load study, it was found that the Rahimi mechanism was not able to predict the RCCI combustion behavior for diesel injection timings advanced beyond 30 degCA bTDC. This poor prediction was found at multiple engine speed and load points.

Gasoline compression ignition (GCI) technology shows the potential to obtain high thermal efficiencies while maintaining low soot and NOx emissions in light-duty engine applications. Recent experimental studies and numerical simulations have indicated that high reactivity gasoline-like fuels can further enable the benefits of GCI combustion. However, there is limited empirical data in the literature studying the gasoline compression ignition process at relevant in-cylinder conditions, which are required for further optimizing combustion system designs. This study investigates the temporal and spatial evolution of the compression ignition process of various high reactivity gasoline fuels with research octane numbers (RON) of 71, 74 and 82, as well as a conventional RON 97 E10 gasoline fuel. A ten-hole prototype gasoline injector specifically designed for GCI applications capable of injection pressures up to 450 bar was used.

Ducted fuel injection (DFI) is a developing technology for reducing in-cylinder soot formed during mixing-controlled combustion in diesel compression ignition engines. Fuel injection through a small duct has the effect of extending the lift-off length (LOL) and reducing the equivalence ratio at ignition. In this work, the feasibility of DFI to reduce soot and to enable leaner lifted-flame combustion (LLFC) is investigated for a single diesel jet injected from a 138 μm orifice into engine-like (60-120 bar, 800-950 K) quiescent conditions. High-speed imaging and natural luminosity (NL) measurements of combusting sprays were used to quantify duct effects on jet penetration, ignition delay, LOL, and soot emission in a constant pressure high-temperature-pressure vessel (HTPV). At the highest ambient pressure and temperatures tested, soot luminosity was reduced by as much as 50%.

Combustion systems with advanced injection strategies have been extensively studied, but there still exists a significant fundamental knowledge gap on fuel spray interactions with the piston surface and chamber walls. This paper is meant to provide detailed data on spray-wall impingement physics and support the spray-wall model development. The experimental work of spray-wall impingement with non-vaporizing spray characterization, was carried out in a high pressure-temperature constant-volume combustion vessel. The simultaneous Mie scattering of liquid spray and schlieren of liquid and vapor spray were carried out. Diesel fuel was injected at a pressure of 1500 bar into ambient gas at a density of 22.8 kg/m3 with isothermal conditions (fuel, ambient, and plate temperatures of 423 K). A Lagrangian-Eulerian modeling approach was employed to characterize the spray-gas and spray-wall interactions in the CONVERGETM framework by means of a Reynolds-Averaged Navier-Stokes (RANS) formulation.

Cyclic variability in internal combustion engines (ICEs) arises from multiple concurrent sources, many of which remain to be fully understood and controlled. This variability can, in turn, affect the behavior of the engine resulting in undesirable deviations from the expected operating conditions and performance. Shot-to-shot variation during the fuel injection process is strongly suspected of being a source of cyclic variability. This study focuses on the shot-to-shot variability of injector needle motion and its influence on the internal nozzle flow behavior using diesel fuel. High-speed x-ray imaging techniques have been used to extract high-resolution injector geometry images of the sac, orifices, and needle tip that allowed the true dynamics of the needle motion to emerge. These measurements showed high repeatability in the needle lift profile across multiple injection events, while the needle radial displacement was characterized by a much higher degree of randomness.

Homogeneous charge compression ignition (HCCI) offers the potential for significant improvements in efficiency with a substantial reduction in emissions. However, achieving heavy-duty (HD) HCCI engine operation at practical loads and speeds presents numerous technical challenges. Successful expansion of the HCCI operating range to include the full range of load and speed must be accomplished while maintaining proper combustion phasing, control of maximum cylinder pressure and pressure rise rates, and low emissions of NOx and particulate matter (PM). Significant progress in this endeavour has been made through a collaborative research effort between Caterpillar and ExxonMobil. This paper evaluates fuel effects on HCCI engine operating range and emissions. Test fuels were developed in the gasoline and diesel boiling range covering a broad range of ignition quality, fuel chemistry, and volatility.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Optimal fuel injection strategies are obtained with a micro-genetic algorithm and an adaptive gradient method for a nonroad, medium-speed DI diesel engine equipped with a multi-orifice, asynchronous fuel injection system. The gradient optimization utilizes a fast-converging backtracking algorithm and an adaptive cost function which is based on the penalty method, where the penalty coefficient is increased after every line search. The micro-genetic algorithm uses parameter combinations of the best two individuals in each generation until a local convergence is achieved, and then generates a random population to continue the global search. The optimizations have been performed for a two pulse fuel injection strategy where the optimization parameters are the injection timings and the nozzle orifice diameters.

A quasi-steady 1-dimensional computer model of a catalyzed particulate filter (CPF) capable of simulating active regeneration of the CPF via diesel fuel injection upstream of a diesel oxidation catalyst (DOC) or other means to increase the exhaust gas temperature has been developed. This model is capable of predicting gaseous species concentrations (HC's, CO, NO and NO2) and exhaust gas temperatures within and after the CPF, for given input values of gaseous species and PM concentrations before the CPF and other inlet variables such as time-varying temperature of the exhaust gas at the inlet of the CPF and volumetric flow rate of exhaust gas.

As the incentive to produce cleaner and more efficient engines increases, diesel engines will become a primary, worldwide solution. Producing diesel engines with higher efficiency and lower emissions requires a fundamental understanding of the interaction of the injected fuel with air as well as with the surfaces inside the combustion chamber. One aspect of this interaction is spray impingement on the piston surface. Impingement on the piston can lead to decreased combustion efficiency, higher emissions, and piston damage due to thermal loading. Modern high-speed diesel engines utilize high pressure common-rail direct-injection systems to primarily improve efficiency and reduce emissions. However, the high injection pressures of these systems increase the likelihood that the injected fuel will impinge on the surface of the piston.

In modern production diesel engine control systems, fuel path control is still largely conducted through a system of tables that set mode, timing and injection quantity and with common rail systems, rail pressure. In the hands of an experienced team, such systems have proved so far able to meet emissions standards, but they lack the analytical underpinning that lead to systematic solutions. In high degree of freedom systems typified by modern fuel injection, there is substantial scope to deploy optimising closed loop strategies during calibration and potentially in the delivered product. In an optimising controller, a digital algorithm will explicitly trade-off conflicting objectives and follow trajectories during transients that continue to meet a defined set of criteria. Such an optimising controller must be based on a model of the system behaviour which is used in real time to investigate the consequences of proposed control actions.

A two-zone NOx model intended for 1-D engine simulations was developed and used to model NOx emissions from a 2.5 L single-cylinder engine. The intent of the present work is to understand key aspects of a simple NOx model that are needed for predictive accuracy, including NOx formation and destruction phenomena in a DI Diesel combustion system. The presented two-zone model is fundamentally based on the heat release rate and thermodynamic incylinder data, and uses the Extended Zeldovich mechanism to model NO. Results show that the model responded very well to changes in speed, load, injection timing, and EGR level. It matched measured tail pipe NOx levels within 20%, using a single tuning setup. When the model was applied to varied injection rate shapes, it showed correct sensitivity to speed, load, injection timing, and EGR level, but the absolute level was well outside the target accuracy. The same limitation was seen when applying the Plee NOx model.

This research investigates the combustion characteristics and engine performance of a conventional non-ethanol gasoline with a research octane number of 91(RON 91) and a higher reactivity RON80 gasoline under mixing-controlled combustion. The work was conducted in a model year 2013 Cummins ISX15 heavy-duty diesel engine. A split fuel injection strategy was developed to address the long ignition delay and high maximum pressure rise rate for the two gasoline fuels. Using the split fuel injection strategy, steady-state NOx sweeps were conducted at 1375 rpm with a load sweep from 5 to 15 bar BMEP. At 5 and 10 bar BMEP, both gasolines consistently exhibited lower soot levels than ULSD with the reduction more pronounced at 5 bar BMEP. 3-D CFD combustion simulation suggested that the higher volatility and lower viscosity of gasoline fuels can help improve the in-cylinder air utilization and therefore reduce the presence of fuel-rich regions in the combustion chamber.

The characteristics of combustion knock metrics over a number of engine cycles can be an essential reference for knock detection and control in internal combustion engines. In a Spark-Ignition (SI) engine, the stochastic nature of combustion knock has been shown to follow a log-normal distribution. However, this has been derived from experiments done with gasoline only and applicability of log-normal distribution to dual-fuel combustion knock has not been explored. To evaluate the effectiveness and accuracy of log-normal distributed knock model for methane-gasoline blended fuel, a sweep of methane-gasoline blend ratio was conducted at two different engine speeds. Experimental investigation was conducted on a single cylinder prototype SI engine equipped with two fuel systems: a direct injection (DI) system for gasoline and a port fuel injection (PFI) system for methane.

This research investigates the potential of gasoline compression ignition (GCI) to achieve low engine-out NOx emissions with high fuel efficiency in a heavy-duty diesel engine. The experimental work was conducted in a model year (MY) 2013 Cummins ISX15 heavy-duty diesel engine, covering a load range of 5 to 15 bar BMEP at 1375 rpm. The engine compression ratio (CR) was reduced from the production level of 18.9 to 15.7 without altering the combustion bowl design. In this work, four gasolines with research octane number (RON) ranging from 58 to 93 were studied. Overall, GCI operation resulted in enhanced premixed combustion, improved NOx-soot tradeoffs, and similar or moderately improved fuel efficiency compared to diesel combustion. A split fuel injection strategy was employed for the two lower reactivity gasolines (RON80 and RON93), while the RON60 and RON70 gasolines used a single fuel injection strategy.

The accurate modeling of fuel spray behavior under diesel engine conditions requires well-characterized boundary conditions. Among those conditions, the spray cone angle is important due to its impact on the spray mixing process, flame lift-off locations and subsequent soot formation. The spray cone angle is a highly dynamic variable, but existing correlations have been developed mainly for diesel fuels at quasi-steady state and relatively low injection pressures. The objective of this study was to develop spray cone angle correlations for both diesel and a light-end gasoline fuel over a wide range of diesel-engine operating conditions that are capable of capturing both the transient and quasi-steady state processes. Two important macroscopic characteristics of solid cone sprays, the spray cone angle and spray penetration, were measured using a single-hole heavy-duty injector using two fuels at diesel engine conditions in an optical constant volume vessel.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.