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This paper focuses on an assessment of predictive combustion model using a 0D/1D simulation tool under high load, different excess air ratio λ , and different combustion stabilities (based on coefficient of variation of indicated mean effective pressure COVimep). To consider that, crank angle resolved data of experimental pressure of 500 cycles are recorded under engine speed 1000 RPM and 2000 RPM, wide-open throttle, and λ=1.0, 1.42, 1.7, and 2.0. Firstly, model calibration is conducted using 18 cases at 2000 RPM using 500 cycle-averaged in-cylinder pressure to find optimized model constants. Then, the model constants are unchanged for other cases. Next, different cycle-averaged pressure data are used as inputs in the simulation based on the COVimep for studying sensitivity of the turbulent model constants. The simulation is conducted using 1D simulation software GT-Power.

The purpose of this paper is to build up a model for predicting turbulent burning velocity which can be used for One-Dimensional (1D) engine simulation. This paper presents the relationship between turbulent burning velocity, the Karlovitz number, and the Markstein number for building up the prediction model. The turbulent burning velocity was measured using a single-cylinder gasoline engine, which has an external Exhaust Gas Recirculation (EGR) system. In the experiment, various engine operating parameters, e.g. engine loads and EGR rates, and various engine specifications, i.e. different types of intake ports were tested. The Karlovitz number was calculated using Three-Dimensional Computational Fluid Dynamics (3D-CFD) and detailed chemical kinetics simulation with a premixed laminar flame model. The Markstein number was also calculated using detailed chemical kinetics simulation with the Extinction of Opposed-flow Flame model.

This paper describes the development of an integrated simulation model for evaluating the effects of electrically heating the three-way catalyst (TWC) in a series hybrid electric vehicle (s-HEV) on fuel economy and exhaust gas purification performance. Engine and TWC models were developed in GT-Power to predict exhaust emissions during transient operation. These models were validated against data from vehicle tests using a chassis dynamometer and integrated into an s-HEV model built in MATLAB/Simulink. The s-HEV model accurately reproduced the performance characteristics of the vehicle’s engine, motor, generator, and battery during WLTC mode operation. It can thus be used to predict the fuel consumption, emissions, and performance of individual powertrain components. The engine combustion characteristics were reproduced with reasonable accuracy for the first 50 combustion cycles, representing the cold-start condition of the driving mode.

Natural gas pre-mixture is ignited by a small amount of pilot fuel in the dual fuel engine. In this paper, numerical studies were carried out to investigate the combustion and exhaust gas emissions formation process of this engine type by using a multi dimensional model combined with the detailed chemical kinetics including 57 chemical species and 290 elementary reactions. In calculation, the effect of the pre-mixture concentration on combustion was examined. The result indicated that the increased concentration of natural gas could improve the burning fraction and THC, CO emissions due to the increased pre-mixture consumption rate and the cylinders gas temperature.

A mixed timescale subgrid model of a large eddy simulation was used to simulate the turbulence regime in diesel engine combustion. The combustion model used the direct integration approach with a diesel oil surrogate mechanism (developed at Chalmers University of Technology and consisting of 70 species and 309 reactions). Additional reactions for the generation and consumption of OH*, CO2*, and CH* species were added from recent kinetic studies. Collisional quenching and spontaneous emission resulted in de-excitation of the excited state radical. A phenomenological soot formation model (developed at Waseda University) was combined with the LES code. The following important steps were considered in the soot model: particle inception where naphthalene grows irreversibly to form soot, surface growth with the addition of C2H2, surface oxidation (induced by OH radicals and O2 attack), and particle coagulation.

A CFD code combined with detailed chemical kinetics has been developed, linking with KIVA-3 and subroutines in CHEMKIN-II directly with some modifications. By using this CFD code, formation processes of combustion and exhaust gas emission for a turbo-charged DI diesel engine with common rail fuel injection system were simulated. As a result, formation processes of pollutant including NOx and soot were also considered according to the calculation results. The results show that NO caused by the extended Zeldvich mechanism accounted for about 88% of all NO, and it was found that there is a possibility to predict where and when soot will be formed by considering a simplified soot formation model.

A three-dimensional computational fluid dynamics (3D-CFD) code was combined with a detailed combustion chamber heat transfer model. The established model allowed not only prediction of instantaneous combustion chamber wall surface temperature distributions in practical calculation time but also investigation of the characteristics of combustion, emissions and heat losses affected by the wall temperature distributions. Although zero-dimensional combustion analysis can consider temporal changes in the heat transfer coefficient and in-cylinder gas temperature, it cannot take into account the effect of interactions between spatially distributed charge and wall temperatures. In contrast, 3D-CFD analysis can consider temporal and spatial changes in both parameters. However, in most zero-/multi- dimensional combustion analyses, wall temperatures are assumed to be temporally constant and spatially homogeneous.

Experimental and numerical studies on the combustion of the particulate matter in the diesel particulate filter with the particulate matter loaded under different particulate matter loading condition were carried out. It was observed that the pressure losses through diesel particulate filter loaded with particulate matter having different mean aggregate particle diameters during both particulate matter loading and combustion periods. Diesel particulate filter regeneration mode was controlled with introducing a hot gas created in Diesel Oxidation Catalyst that oxidized hydrocarbon injected by a fuel injector placed on an exhaust gas pipe. The combustion amount was calculated with using a total diesel particulate filter weight measured by the weight meter both before and after the particulate matter regeneration event.

Experimental and numerical studies were conducted on diesel particulate filters (DPFs) under different soot loading conditions and DPF configurations. Pressure drops across DPFs with various mean pore diameters loaded with soots having different mean particle diameters were measured by introducing exhaust gases from a 2.2 liter inline four-cylinder, TCI diesel engine designed for use in passenger cars. A mechanistic hypothesis was then proposed to explain the observed trends, accounting for the effects of the soot loading regime in the wall and the soot cake layer on the pressure drop. This hypothesis was used to guide the development and validation of a numerical model for predicting the pressure drop in the DPF. The relationship between the permeability and the porosity of the wall and soot cake layer was modeled under various soot loading conditions.

Cars with diesel engines are commonly equipped with a Diesel Particulate Filter (DPF) to reduce their emissions of particulate matter (PM). Because the pressure drop within the DPF reduces engine performance, it must be predicted with accuracy. The purpose of this study was to improve the accuracy of a DPF simulation model under transient conditions by parameter optimization. The DPF model under consideration consists of an inlet channel, a cake layer, wall layer, and an outlet channel. The pressure drop is influenced by the location, mass, and density of the deposited soot. Therefore, the model includes the following sub-models: Sub-model 1: Calculates the soot density deposited in the wall layer Sub-model 2: Computes the filtration efficiency and mass of the wall and cake layer Sub-model 3: Calculates the soot density deposited in the cake layer Because the sub-models include some empirical formulae, the first step in refining the model was to optimize their fitting parameters.

For a series hybrid electric vehicle (SHEV), the electric motor is responsible for driving the wheels, while the engine drives the only generator to provide electricity. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of a conventional drive system using only an internal combustion engine, and it is time-consuming to obtain the optimal components specification values and control parameters. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method.

Urea SCR (Selective Catalytic Reduction) exhaust after-treatment systems are one of the most promising measures to reduce NOx emissions from diesel engines. Both Cu-zeolite (Cu-SCR) and Fe-zeolite (Fe-SCR) urea SCR systems have been studied extensively but not many detailed studies have been conducted on the combination of both systems. Thus, we carried out studies on such Combined-SCR systems and their capability to reduce NOx under various engine operating conditions. We also conducted transient engine tests using different catalyst systems to compare their performance. The results show that combined-SCR systems can reduce NOx more effectively than Fe-SCR or Cu-SCR alone. The best NOx reduction performance was achieved at a Cu ratio of 0.667 (i.e. Fe: Cu =1: 2). Combined-SCR thus apparently benefits from the characteristics of both Cu-SCR and Fe-SCR, allowing it to reduce NOx over a wide range of operating conditions.

The recent and future trends of energy for heavy-duty vehicles are considered e-fuel, H2, and electricity, and the Selective Catalytic Reduction (SCR) system is necessary for achieving the goals of zero-emission internal combustion engines that use e-fuel and H2 as a fuel. The Japanese automotive industry uses a Cu-zeolite based SCR catalyst since Vanadium is designated as a specific chemical substance, which the Ministry of Environment prohibits its release into the atmosphere. This study attempted purification rate improvement by controlling the NH3 supply with a mini-reactor and by simulated exhaust gas. Specifically, the experiment was done by examining the effect of the pulse amplitude, frequency, and duty ratio on the purification rate by supplying the NH3 pulse injection to the test piece Cu-chabazite catalyst. Additionally, the results of the reactor experiment were validated by numerical simulation considering the detailed surface reaction processes on the catalyst.

The authors have previously proposed a plume ignition and combustion concept (i.e., PCC combustion), in which a hydrogen fuel is directly injected to the combustion chamber in the latter half of compression stroke and forms a richer mixture plume. By combusting the plume, both cooling losses and NOx formation are reduced. In this study, thermal efficiency was substantially improved and NOx formation was reduced with PCC combustion by optimizing such characteristics as direction and diameter of the jets in combination with combustion of lean mixture. Output power declined due to the lean mixture, however, was recovered by supercharging while keeping NOx emissions at the same level. Thermal efficiency was further improved by slightly re-optimizing the jet conditions.

In our previous reports, we proposed a new focusing engine with high thermal efficiency based on relatively-silent high compression and nearly-complete air-insulation effect, which employs pulsed multi-jets of gas collided around chamber center. Local compression level due to the gas jets colliding around chamber center before reaction can be varied from zero to 100MPa and 3000K, by changing the number of jets and intake pressure. Relatively-silent high compression is possible, because region around chamber wall is at pressure level of traditional engines. This is suitable for various usages of automobiles, aerocrafts, and rockets, and also for various fuels including hydrogen, because high compression around chamber center leads to stable auto-ignition and potential of low NOx at very lean burning operation. We developed two types of focusing compression engines, without and with piston. For the new engine without piston, we obtained nearly-complete air-insulation and high thrust.

Urea-SCR system has a high NOx reduction potential in the steady-state diesel engine operation. In complicated transient operations, however, there are certain problems with the urea-SCR system in that NOx reduction performance degrades and adsorbed NH3 would be emitted. Here, optimum urea injection methods and exhaust bypass control to overcome these problems are studied. This exhaust bypass control enables NO/NOx ratio at the inlet of SCR catalyst to be decreased widely, which prevents over production of NO2 at the pre-oxidation catalyst. Steady-state and simple transient engine tests were conducted to clarify NOx reduction characteristics when optimum urea injection pattern and exhaust bypass control were applied. In simple transient test, only the engine load was rapidly changed for obtaining the fundamental knowledge concerning the effect of those techniques.

Three-way catalyst (TWC) converters can purify harmful substances, such as carbon monoxide, nitrogen oxides, and hydrocarbons, from the exhaust gases of gasoline engines. However, large amounts of these substances may be emitted before the TWC reaches its light-off temperature during cold starts, and its performance may be impaired by thermal deterioration during high-load driving. In this work, a simulation model was developed using axisuite commercial software by Exothermia S.A to predict the light-off conversion performance of Pd/CeO2-ZrO2-Al2O3 catalysts with different degrees of thermal deterioration. The model considered detailed surface reactions and the main factor of the deterioration mechanism. In the detailed reaction mechanism, adsorption, desorption, and surface reactions of each gas species at active sites of the platinum group metal (PGM) particles were considered based on the Langmuir-Hinshelwood mechanism.

Difference of engine combustion characteristics, species and amount of exhaust gas and PM (particulate matter consisted of SOF and Soot and Ash), and especially PM oxidation characteristics were studied when diesel fuel or bio-fuel, here PME (palm oil methyl ester) as an example, was used as a fuel. The fueling rate was adjusted to obtain the same torque for both fuels and engine was operated under several range of EGR (Exhaust Gas Recirculation) ratio. Under such conditions, PME showed shorter ignition delay time and lower R.H.R (rate of heat release) under 0-40% EGR ratio. With respect to engine exhaust gas species, CO, NO, THC and HCHO, CH3CHO concentration was almost the same when the EGR ratio is higher than 35% (Intake-Air/Fuel: A/F=20). However, PME also showed lower exhaust gas emission when the EGR ratio is higher than 30%.

A mixed time-scale subgrid large eddy simulation was used to simulate mixture formation, combustion and soot formation under the influence of turbulence during diesel engine combustion. To account for the effects of engine wall heat transfer on combustion, the KIVA code's standard wall model was replaced to accommodate more realistic boundary conditions. This were carried out by implementing the non-isothermal wall model of Angelberger et al. with modifications and incorporating the log law from Pope's method to account for the wall surface roughness. Soot and NOx emissions predicted with the new model are compared to experimental data acquired under various EGR conditions.

The reduced chemical reaction scheme which can take the effect of major fuel components on auto ignition timing into account has been developed. This reaction scheme was based on the reduced reaction mechanism for the primary reference fuels (PRF) proposed by Tsurushima [1] with 33 species and 38 reactions. Some pre-exponential factors were modified by using Particle Swarm Optimization to match the ignition delay time versus reciprocal temperature which was calculated by the detailed scheme with 2,301 species and 11,116 elementary chemical reactions. The result using the present reaction scheme shows good agreements with that using the detailed scheme for the effects of EGR, fuel components, and radical species on the ignition timing under homogeneous charge compression ignition combustion (HCCI) conditions.