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Heavy-duty engine experiments were conducted to explore reactivity controlled compression ignition (RCCI) combustion through addition of the cetane improver di-tert-butyl peroxide (DTBP) to pump gasoline. Unlike previous diesel/gasoline dual-fuel operation of RCCI combustion, the present study investigates the feasibility of using a single fuel stock (gasoline) as the basis for both high reactivity and low reactivity fuels. The strategy consisted of port fuel injection of gasoline and direct injection of the same gasoline doped with a small volume percent addition of DTBP. With 1.75% DTBP by volume added to only the direct-injected fuel (which accounts for approximately 0.2% of the total fueling) it was found that the additized gasoline behaved similarly to diesel fuel, allowing for efficient RCCI combustion. The single fuel results with DTBP were compared to previous high-thermal efficiency, low-emissions results with port injection of gasoline and direct injections of diesel.

This study investigates the potential of controlling premixed charge compression ignition (PCCI and HCCI) combustion strategies by varying fuel reactivity. In-cylinder fuel blending using port fuel injection of gasoline and early cycle direct injection of diesel fuel was used for combustion phasing control at both high and low engine loads and was also effective to control the rate of pressure rise. The first part of the study used the KIVA-CHEMKIN code and a reduced primary reference fuel (PRF) mechanism to suggest optimized fuel blends and EGR combinations for HCCI operation at two engine loads (6 and 11 bar net IMEP). It was found that the minimum fuel consumption could not be achieved using either neat diesel fuel or neat gasoline alone, and that the optimal fuel reactivity required decreased with increasing load. For example, at 11 bar net IMEP, the optimum fuel blend and EGR rate for HCCI operation was found to be PRF 80 and 50%, respectively.

This study investigates the potential of controlling premixed charge compression ignition (PCCI) combustion strategies by varying fuel reactivity. In-cylinder fuel blending using port fuel injection of gasoline and early cycle, direct-injection of diesel fuel was used for combustion phasing control at a medium engine load of 9 bar net IMEP and was also found to be effective to prevent excessive rates of pressure rise. Parameters used in the experiments were guided from the KIVA-CHEMKIN code with a reduced primary reference fuel (PRF) mechanism including injection timings, fuel percentages, and intake valve closing (IVC) timings for dual-fuel PCCI combustion. The engine experiments were conducted with a conventional common rail injector (i.e., wide angle and large nozzle hole) and demonstrated control and versatility of dual-fuel PCCI combustion with the proper fuel blend, SOI and IVC timings.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that utilizes in-cylinder fuel blending to produce low NOx and PM emissions while maintaining high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines [1, 2, 3, 4, 5, 6]. The current study investigates RCCI operation in a light-duty multi-cylinder engine over a wide number of operating points representing vehicle operation over the US EPA FTP test. Similarly, previous RCCI engine experiments have used petroleum based fuels such as ultra-low sulfur diesel fuel (ULSD) and gasoline, with some work done using high percentages of biofuels, namely E85 [7]. The current study was conducted to examine RCCI performance with moderate biofuel blends, such as E20 and B20, as compared to conventional gasoline and ULSD.

The present experimental engine efficiency study explores the effects of intake pressure and temperature, and premixed and global equivalence ratios on gross thermal efficiency (GTE) using the reactivity controlled compression ignition (RCCI) combustion strategy. Experiments were conducted in a heavy-duty single-cylinder engine at constant net load (IMEPn) of 8.45 bar, 1300 rev/min engine speed, with 0% EGR, and a 50% mass fraction burned combustion phasing (CA50) of 0.5°CA ATDC. The engine was port fueled with E85 for the low reactivity fuel and direct injected with 3.5% 2-ethylhexyl nitrate (EHN) doped into 91 anti-knock index (AKI) gasoline for the high-reactivity fuel. The resulting reactivity of the enhanced fuel corresponds to an AKI of approximately 56 and a cetane number of approximately 28. The engine was operated with a wide range of intake pressures and temperatures, and the ratio of low- to high-reactivity fuel was adjusted to maintain a fixed speed-phasing-load condition.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

Reactivity Controlled Compression Ignition (RCCI) has been shown to be an attractive concept to achieve clean and high efficiency combustion. RCCI can be realized by applying two fuels with different reactivities, e.g., diesel and gasoline. This motivates the idea of using a single low reactivity fuel and direct injection (DI) of the same fuel blended with a small amount of cetane improver to achieve RCCI combustion. In the current study, numerical investigation was conducted to simulate RCCI and HCCI combustion and emissions with various fuels, including gasoline/diesel, iso-butanol/diesel and iso-butanol/iso-butanol+di-tert-butyl peroxide (DTBP) cetane improver. A reduced Primary Reference Fuel (PRF)-iso-butanol-DTBP mechanism was formulated and coupled with the KIVA computational fluid dynamic (CFD) code to predict the combustion and emissions of these fuels under different operating conditions in a heavy duty diesel engine.

The focus of the present study was to characterize Reactivity Controlled Compression Ignition (RCCI) using a single-fuel approach of gasoline and gasoline mixed with a commercially available cetane improver on a multi-cylinder engine. RCCI was achieved by port-injecting a certification grade 96 research octane gasoline and direct-injecting the same gasoline mixed with various levels of a cetane improver, 2-ethylhexyl nitrate (EHN). The EHN volume percentages investigated in the direct-injected fuel were 10, 5, and 2.5%. The combustion phasing controllability and emissions of the different fueling combinations were characterized at 2300 rpm and 4.2 bar brake mean effective pressure over a variety of parametric investigations including direct injection timing, premixed gasoline percentage, and intake temperature. Comparisons were made to gasoline/diesel RCCI operation on the same engine platform at nominally the same operating condition.

In the present paper optimization tools are used to recommend low-emission engine combustion chamber designs, spray targeting and swirl ratio levels for a heavy-duty diesel engine operated at high-load. The study identifies aspects of the combustion and pollution formation that are affected by mixing processes, and offers guidance for better matching of the piston geometry with the spray plume geometry for enhanced mixing. By coupling a GA (genetic algorithm) with the KIVA-CFD code, and also by utilizing an automated grid generation technique, multi-objective optimizations with goals of low emissions and fuel economy were achieved. Three different multi-objective genetic algorithms including a Micro-Genetic Algorithm (μGA), a Nondominated Sorting Genetic Algorithm II (NSGA II) and an Adaptive Range Multi-Objective Genetic Algorithm (ARMOGA) were compared for conducting the optimization under the same conditions.

In the present study a reduced chemical reaction mechanism for biodiesel surrogate fuel was developed and validated for multi-dimensional engine combustion simulations. An existing detailed methyl butanoate mechanism that contained 264 species and 1219 reactions was chosen to represent the oxygenated portion of the fuel. The reduction process included flux analysis, ignition sensitivity analysis, and optimization of reaction rate constants under constant volume conditions. The current reduced mechanism consists of 41 species and 150 reactions and gives predictions in excellent agreement with those of the comprehensive mechanism. In order to validate the mechanism under biodiesel-fueled engine conditions, it was combined with another skeletal mechanism for n-heptane oxidation. This combined reaction mechanism can be used to adjust the energy content of the fuel, and account for diesel/biodiesel blend engine simulations.

A computational study using multi-dimensional CFD modeling was performed to investigate the effects of physical properties on diesel engine combustion characteristics with bio-diesel fuels. Properties of typical bio-diesel fuels that were either calculated or measured are used in the study and the simulation results are compared with those of conventional diesel fuels. The sensitivity of the computational results to individual physical properties is also investigated, and the results provide information about the desirable characteristics of the blended fuels. The properties considered in the study include liquid density, vapor pressure, surface tension, liquid viscosity, liquid thermal conductivity, liquid specific heat, latent heat, vapor specific heat, vapor diffusion coefficient, vapor viscosity and vapor thermal conductivity. The results show significant effects of the fuel physical properties on ignition delay and burning rates at various engine operating conditions.

The development of a new Nitric Oxide (NOx) reaction mechanism has been conducted by adding species, including hydrogen cyanide (HCN) and the CH radical to a reduced chemistry diesel combustion model. The additional chemical reactions were added to the ERC's reduced 12-step NOx mechanism, which consists of N, NO, N2O, and NO2. The new NOx mechanism was implemented into the KIVA/ERC-CHEMKIN code and was found to be able to predict the experimentally observed trend that the amount of engine-out NOx decreases as engine load is increased, which is not reproduced by the current reduced NOx mechanism. HCN and CH were found to be species that bridge CxHy products and N radicals via the reaction CH+N2→HCN+N under high equivalence ratio conditions, and Zeldovich NO formation is suppressed by the formation of HCN, a species in the Fenimore NO formation pathway. The additional species and reactions were also found to influence the prediction of engine-out soot emissions.

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.

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Reactivity Controlled Compression Ignition combustion (RCCI) has been demonstrated at mid to high loads [1, 2, 3, 4, 5, 6] as a method to operate an internal combustion engine that produces low NOx and low PM emissions with high thermal efficiency. The current study investigates RCCI engine operation at loads of 2 and 4.5 bar gross IMEP at engine speeds between 800 and 1700 rev/min. This load range was selected to cover the range from the previous work of 6 bar gIMEP down to an off-idle load at 2 bar. The fueling strategy for the low load investigation consisted of in-cylinder fuel blending using port-fuel-injection of gasoline and early cycle, direct-injection of either diesel fuel or gasoline doped with 3.5% by volume 2-EHN (2-ethylhexyl nitrate). At these loads, engine operating conditions such as inlet air temperature, port fuel percentage, and engine speed were varied to investigate their effect on combustion.

Biodiesel-fueled engine simulations were performed using the KIVA3v-Release 2 code coupled with Chemkin-II for detailed chemistry. The model incorporates a reduced mechanism that was created from a methyl decanoate/methyl-9-decenoate mechanism developed at the Lawrence Livermore National Laboratory. A combination of Directed Relation Graph, chemical lumping, and limited reaction rate tuning was used to reduce the detailed mechanism from 3299 species and 10806 reactions to 77 species and 209 reactions. The mechanism was validated against its detailed counterpart and predicted accurate ignition delay times over a range of relevant operating conditions. The mechanism was then combined with the ERC PRF mechanism to include n-heptane as an additional fuel component. The biodiesel mechanism was applied in KIVA using a discrete multi-component model with accurate physical properties for the five common components of real biodiesel fuel.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that produces low NO and PM emissions with high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines. The current study investigates RCCI operation in a light-duty multi-cylinder engine at 3 operating points. These operating points were chosen to cover a range of conditions seen in the US EPA light-duty FTP test. The operating points were chosen by the Ad Hoc working group to simulate operation in the FTP test. The fueling strategy for the engine experiments consisted of in-cylinder fuel blending using port fuel-injection (PFI) of gasoline and early-cycle, direct-injection (DI) of diesel fuel. At these 3 points, the stock engine configuration is compared to operation with both the original equipment manufacturer (OEM) and custom-machined pistons designed for RCCI operation.

Many recent studies have shown that the Reactivity Controlled Compression Ignition (RCCI) combustion strategy can achieve high efficiency with low emissions. However, it has also been revealed that RCCI combustion is difficult at high loads due to its premixed nature. To operate at moderate to high loads with gasoline/diesel dual fuel, high amounts of EGR or an ultra low compression ratio have shown to be required. Considering that both of these approaches inherently lower thermodynamic efficiency, in this study natural gas was utilized as a replacement for gasoline as the low-reactivity fuel. Due to the lower reactivity (i.e., higher octane number) of natural gas compared to gasoline, it was hypothesized to be a better fuel for RCCI combustion, in which a large reactivity gradient between the two fuels is beneficial in controlling the maximum pressure rise rate.

A single-cylinder light-duty diesel engine was used to investigate dual fuel reactivity controlled compression ignition (RCCI) operated with two different fuel combinations: gasoline/diesel fuel and methanol/diesel fuel. The engine was operated over a range of conditions, from 1500 to 2300 rpm and 3.5 to 17 bar gross IMEP. Using the stock re-entrant piston bowl geometry, both fuel combinations were able to achieve low NOx and PM emissions with a peak gross indicated efficiency of 48%. However, at light load conditions both gasoline and methanol yielded poorer combustion efficiencies. Previous studies have shown that the high-levels of piston induced mixing that are created by the stock piston are not required, and in fact are detrimental due to increased heat transfer losses, for premixed combustion. Thus a modified piston featuring a shallow, flat piston bowl with nearly no squish land was also investigated.

Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.