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An emissions and performance study was conducted to explore the effects of exhaust gas recirculation (EGR) and multiple injections on the emission of oxides of nitrogen (NOx), particulate emissions, and brake specific fuel consumption (BSFC) over a wide range of engine operating conditions. The tests were conducted on an instrumented single cylinder version of the Caterpillar 3400 series heavy duty Diesel engine. Data was taken at 1600 rev/min, and 75% load, and also at operating conditions taken from a 6-mode simulation of the federal transient test procedure (FTP). The fuel system used was an electronically controlled, common rail injector and supporting hardware. The fuel system was capable of as many as four independent injections per combustion event at pressures from 20 to 120MPa.

A, three-dimensional CFD code, based on the KIVA code, is used to explore alternatives to conventional DI diesel engine designs for reducing NOx and soot emissions without sacrificing engine performance. The effects of combustion chamber design and fuel spray orientation are investigated using a new proposed GAMMA engine concept, and two new multiple injector combustion system (MICS) designs which utilize multiple injectors to increase gas motion and enhance fuel/air mixing in the combustion chamber. From these computational studies, it is found that both soot and nitrous oxide emissions can be significantly reduced without the need for more conventional emission control strategies such as EGR or ultra high injection pressure. The results suggest that CFD models can be a useful tool not only for understanding combustion and emissions production, but also for investigating new design concepts.

The paper presents the development of a novel approach to the solution of detailed chemistry in internal combustion engine simulations, which relies on the analytical computation of the ordinary differential equations (ODE) system Jacobian matrix in sparse form. Arbitrary reaction behaviors in either Arrhenius, third-body or fall-off formulations can be considered, and thermodynamic gas-phase mixture properties are evaluated according to the well-established 7-coefficient JANAF polynomial form. The current work presents a full validation of the new chemistry solver when coupled to the KIVA-4 code, through modeling of a single cylinder Caterpillar 3401 heavy-duty engine, running in two-stage combustion mode.

Advanced combustion systems that simultaneously address PM and NOx while retaining the high efficiency of modern diesel engines, are being developed around the globe. One of the most difficult problems in the area of advanced combustion technology development is the control of combustion initiation and retaining power density. During the past several years, significant progress has been accomplished in reducing emissions of NOx and PM through strategies such as LTC/HCCI/PCCI/PPCI and other advanced combustion processes; however control of ignition and improving power density has suffered to some degree - advanced combustion engines tend to be limited to the 10 bar BMEP range and under. Experimental investigations have been carried out on a light-duty DI multi-cylinder diesel automotive engine. The engine is operated in low temperature combustion (LTC) mode using 93 RON (Research Octane Number) and 74 RON fuel.

Low-temperature combustion concepts that utilize cooled EGR, early/retarded injection, high swirl ratios, and modest compression ratios have recently received considerable attention. To understand the combustion and, in particular, the soot formation process under these operating conditions, a modeling study was carried out using the KIVA-3V code with an improved phenomenological soot model. This multi-step soot model includes particle inception, surface growth, surface oxidation, and particle coagulation. Additional models include a piston-ring crevice model, the KH/RT spray breakup model, a droplet wall impingement model, a wall heat transfer model, and the RNG k-ε turbulence model. The Shell model was used to simulate the ignition process, and a laminar-and-turbulent characteristic time combustion model was used for the post-ignition combustion process.

The strategy of variable Intake Valve Closure (IVC) timing, as a means to improve performance and emission characteristics, has gained much acceptance in gasoline engines; yet, it has not been explored extensively in diesel engines. In this study, genetic algorithms are used in conjunction with the multi-dimensional engine simulation code KIVA-3V to investigate the optimum operating variables for a typical heavy-duty diesel engine working with late IVC. The effects of start-of-injection timing, injection duration and exhaust gas recirculation were investigated along with the intake valve closure timing. The results show that appreciable reductions in NOx+HC (∼82%), soot (∼48%) and BSFC (∼7.4%) are possible through this strategy, as compared to a baseline diesel case of (NOx+HC) = 9.48g/kW-hr, soot = 0.17 g/kW-hr and BSFC = 204 g-f/kW-hr. The additional consideration of double injections helps to reduce the high rates of pressure rise observed in a single injection scheme.

In this paper, optimized single and double injection schemes were found using multi-dimensional engine simulation software (KIVA-3V) and a micro-genetic algorithm for a heavy duty diesel engine. The engine operating condition considered was at 1737 rev/min and 57 % load. The engine simulation code was validated using an engine equipped with a hydraulic-electronically controlled unit injector (HEUI) system. Five important parameters were used for the optimization - boost pressure, EGR rate, start-of-injection timing, fraction of fuel in the first pulse and dwell angle between first and second pulses. The optimum results for the single injection scheme showed significant improvements for the soot and NOx emissions. The start of injection timing was found to be very early, which suggests HCCI-like combustion. Optimized soot and NOx emissions were reduced to 0.005 g/kW-hr and 1.33 g/kW-hr, respectively, for the single injection scheme.

A multi-dimensional Computational Fluid Dynamics (CFD) code with detailed chemistry, the KIVA-CHEMKIN-GA code, was employed in this study, where Genetic Algorithms (GA) were used to optimize heavy-duty diesel engine operating parameters. A two-stage combustion (TSC) concept was explored to optimize the combustion process at high speed (1737 rev/min) and medium load (57% load). Two combustion modes were combined in this concept. The first stage is ideally Homogeneous Charge Compression Ignition (HCCI) combustion and the second stage is diffusion combustion under high temperature and low oxygen concentration conditions. This can be achieved for example by optimization of two-stage combustion using multiple injection or sprays from two different injectors.

Experiments were performed on a single-cylinder heavy-duty Caterpillar SCOTE 3401E engine at high speed (1737 rev/min) and loads up to 60% of full load for fully Premixed Charge Compression Ignition (PCCI) combustion. The engine was equipped with a high pressure (150 MPa) Caterpillar 300B HEUI fuel injection system. The engine was run with EGR levels up to 75% and with equivalence ratios up to 0.95. These experiments resulted in compliance of NOx and PM emissions to 2010 emissions mandates levels up to the tested load. The set of experiments also demonstrated the importance of cylinder charge preparation by way of optimized start-of-combustion timing for sufficient in-cylinder mixing. It was found that increased EGR rates, even with the correspondingly increased equivalence ratios, increase mixing time and substantially decrease PM emissions.

A computational optimization study is performed for a heavy-duty direct-injection diesel engine using the recently developed KIVA-GA computer code. KIVA-GA performs full cycle engine simulations within the framework of a Genetic Algorithm (GA) global optimization code. Design fitness is determined using a one-dimensional gas -dynamics code for calculation of the gas exchange process, and a three-dimensional CFD code based on KIVA-3V for spray, combustion and emissions formation. The performance of the present Genetic Algorithm is demonstrated using a test problem with a multi-modal analytic function in which the optimum is known a priori. The KIVA-GA methodology is next used to simultaneously investigate the effects of six engine input parameters on emissions and performance for a high speed, medium load operating point for which baseline experimental validation data is available.

A study of statistical optimization of engine operating parameters was conducted. The objective of the study was to develop a strategy to efficiently optimize operating parameters of diesel engines with multiple injection and EGR capabilities. Previous studies have indicated that multiple injections with EGR can provide substantial simultaneous reductions in emissions of particulate and NOx from heavy-duty diesel engines, but careful optimization of the operating parameters is necessary in order to receive the full benefit of these combustion control techniques. The goal of the present study was to optimize the control parameters to reduce emissions and brake specific fuel consumption. An instrumented single-cylinder heavy-duty diesel engine was used with a prototype mechanically actuated (cam driven) fuel injection system.

The present experimental study explores the effects of compression ratio and piston design in a heavy-duty diesel engine operated with Reactivity Controlled Compression Ignition (RCCI) combustion. In previous studies, RCCI combustion with in-cylinder fuel blending using port-fuel-injection of a low reactivity fuel and optimized direct-injections of higher reactivity fuels was demonstrated to permit near-zero levels of NOX and PM emissions in-cylinder, while simultaneously realizing high thermal efficiencies. The present study consists of RCCI experiments at loads from 4 to 17 bar indicated mean effective pressure at engine speeds of 1,300 and 1,700 [rev/min]. The experiments used a modified piston to examine the effect of piston crevice volume, squish geometry, and compression ratio on performance and efficiency.