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Pre-chamber spark ignition technology can stabilize combustion and improve thermal efficiency of lean burn natural gas engines. During compression stroke, a homogeneous lean mixture is introduced into pre-chamber, which separates spark plug electrodes from turbulent flow field. After the pre-chamber mixture is ignited, the burnt jet gas is discharged through multi-hole nozzles which promotes combustion of the lean mixture in the main chamber due to turbulence caused by high speed jet and multi-points ignition. However, details mechanism in the process has not been elucidated. To design the pre-chamber geometry and to achieve stable combustion under the lean condition for such engines, it is important to understand the fundamental aspects of the combustion process. In this study, a high-speed video camera with a 306 nm band-pass filer and an image intensifier is used to visualize OH* self-luminosity in rapid compression-expansion machine experiment.

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.

The objective of the present research is to analyze the effects of using oxygenated fuels (FAMEs) on diesel engine combustion and emission (NOx and soot). We studied methyl oleate (MO), which is an oxygenated fuel representative of major constituents of many types of biodiesels. Engine tests and numerical simulations were performed for 100% MO (MO100), 40% MO blended with JIS#2 diesel (MO40) and JIS#2 diesel (D100). The effects of MO on diesel combustion and emission characteristics were studied under engine operating conditions typically encountered in passenger car diesel engines, focusing on important parameters such as pilot injection, injection pressure and exhaust gas recirculation (EGR) rate. We used a diesel engine complying with the EURO4 emissions regulation, having a displacement of 2.2 L for passenger car applications. In engine tests comparing MO with diesel fuel, no effect on engine combustion pressure was observed for all conditions tested.

A numerical study was carried out to investigate combustion characteristics of a dual-fuel gas diesel engine, using a multi-dimensional model combined with detailed chemical kinetics, including 43 chemical species and 173 elementary reactions. In calculations, the effects of initial temperature, EGR ratios on ignition, and combustion were examined. The results indicated EGR combined with intake preheating can favorably reduced NOx and THC emissions simultaneously. This can be explained by the fact that combustion mechanism is changed from flame propagation to HCCl like combustion.

A major issue of battery electric vehicles (BEV) is optimizing driving range and energy consumption. Under actual driving, transient thermal and electrical performance changes could deteriorate the battery cells and pack. These performances can be investigated and controlled efficiently with a thermal management system (TMS) via model-based development. A complete battery pack contains multiple cells, bricks, and modules with numerous coolant pipes and flow channels. However, such an early modeling stage requires detailed cell geometry and specifications to estimate the thermal and electrochemical energies of the cell, module, and pack. To capture the dynamic performance changes of the LIB pack under real driving cycles, the thermal energy flow between the pack and its TMS must be well predicted. This study presents a BTMS model development and validation method for a 75-kWh battery pack used in mass-production, mid-size battery SUV under WLTC.

We have constructed a quasi-2-dimensional NH₃-SCR model with detailed surface reactions to analyze the NOx conversion mechanism and reasons for its inhibition at low temperatures. The model consists of seven detailed surface reactions proposed by Grozzale et al., and calculates longitudinal gas flow, gas phase-catalyst phase mass transfer, and mass diffusion within the catalyst phase in the depth dimension. Using the model, we have analyzed the results of pulsed ammonia (NH₃) feed tests at various catalyst temperatures, and results show that ammonium nitrate (NH₄NO₃) is the inhibitor in NH₃-SCR reactions at low temperatures. In addition, we found that cutting the supply of NH₃ causes decomposition of NH₄NO₃, providing surface ammonia (NH₄+), which rapidly reacts with adjacent NOx, leading to an instantaneous rise in nitrogen (N₂) formation.

The NOx-reducing activity of a Cu-chabazite selective catalytic reduction (SCR) catalyst was analyzed over a wide temperature range. The analysis was based on the ammonia SCR (NH3-SCR) mechanism and accounted for Cu redox chemistry and reactions at Brønsted acid sites. The reduction of NOx to N2 (De-NOx) at Cu sites was found to proceed via different paths at low and high temperatures. Consequently, the rate-limiting step of the SCR reaction at Cu sites varied with the temperature. The rate of NOx reduction at Cu sites below 200°C was determined by the rate of Cu oxidation. Conversely, the rate of NOx reduction above 300°C was determined by the rate of NH3 adsorption on Cu sites. Moreover, the redox state of the active Cu sites differed at low and high temperatures. To clarify the role of the chabazite Brønsted acid sites, experiments were also performed using a H-chabazite catalyst that lacks Cu sites.

This paper describes a method for estimating constants related to NH3 gas diffusion phenomena to the active sites in a selective catalytic reduction diesel particulate filter (SCR/DPF) catalyst. A simple one-dimensional NH3 gas diffusion model based on the pore structure inside the catalyst was developed and used to estimate the intracrystalline diffusion coefficient. It was shown that the estimated value agreed well with experimental data.

Emission regulations are becoming tighter, and Real Driving Emissions (RDE) is proposed as a testing cycle for evaluating modern engine emissions under a wide operation range. For this reason, engine manufacturers have been developing a method to effectively assess engine performances and emissions under a wide range of transient conditions. Transient engine performances can be evaluated efficiently by applying time-series data created by chirp signals. However, when the time-series data produced by the chirp signal are used directly, the engine hardware may damage, and emission performances deteriorate drastically. It is therefore essential to develop a method to avoid these undesirable operating conditions. This work aims to develop an algorithm to avoid such unrealistic operation conditions for engine performance evaluation. A virtual diesel engine (VDE) model is developed based on a four-cylinder engine using GT-POWER software.

Water and diesel fuel emulsions containing 13% and 26% water by volume were investigated in a modern diesel engine with relatively early pilot injection, supercharging, and cooled EGR. The heat release from the pilot injection with water emulsions is retarded toward the top dead center due to the poor ignitability, which enables larger pilot and smaller main injection quantities. This characteristic results in improvements in the thermal efficiency due to the larger heat release near the top dead center and the smaller afterburning. With the 26% water emulsion, mild, smokeless, and very low NOx operation is possible at an optimum pilot injection quantity and 15% intake oxygen with EGR at or below 0.9 MPa IMEP, a condition where large smoke emissions are unavoidable with regular unblended diesel fuel. Heat transfer analysis with Woschni's equation did not show the decrease in cooling loss with the water emulsion fuels.

Combustion and exhaust gas emissions of alcohol and vegetable oil blends including a 20% ethanol + 40% 1-butanol + 40% vegetable oil blend and a 50% 1-butanol + 50% vegetable oil blend were examined in a single cylinder, four-stroke cycle, 0.83L direct injection diesel engine, with a supercharger and a common rail fuel injection system. A 50% diesel oil + 50% vegetable oil blend and regular unblended diesel fuel were used as reference fuels. The boost pressure was kept constant at 160 kPa (absolute pressure), and the cooled low pressure loop EGR was realized by mixing with a part of the exhaust gas. Pilot injection is effective to suppress rapid combustion due to the lower ignitability of the alcohol and vegetable oil blends. The effects of reductions in the intake oxygen concentration with cooled EGR and changes in the fuel injection pressure were investigated for the blended fuels.

The objective of this paper is to investigate the potential of lean burn combustion to improve the thermal efficiency of spark ignition engine. Experiments used a single cylinder gasoline spark ignition engine fueled with primary reference fuel of octane number 90, running at 4000 revolution per minute and at wide open throttle. Experiments were conducted at constant fueling rate and in order to lean the mixture, more air is introduced by boosted pressure from stoichiometric mixture to lean limit while maintaining the high output engine torque as possible. Experimental results show that the highest thermal efficiency is obtained at excess air ratio of 1.3 combined with absolute boosted pressure of 117 kPa. Three dimensional computational fluid dynamic simulation with detailed chemical reactions was conducted and compared with results obtained from experiments as based points.

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.

An experimental ultra lightweight compact vehicle named “the Waseda Future Vehicle” has been designed and developed, aiming at a simultaneous achievement of low exhaust gas emissions, high fuel economy and driving performance. The vehicle is powered by a dual-type hybrid system having a SI engine, electric motor and generator. A high performance lithium-ion battery unit is used for electricity storage. A variety of driving cycles were reproduced using the hybrid vehicle on a chassis dynamometer. By changing the logics and parameters in the electronic control unit (ECU) of the engine, a significant improvement in emissions was possible, achieving a very high fuel economy of 34 km/h at the Japanese 10-15 drive mode. At the same time, a numerical simulation model has been developed to predict fuel economy. This would be very useful in determining design factors and optimizing operating conditions in the hybrid power system.

Battery thermal management system (BTMS) significantly improves battery electric vehicle (BEV) performance, especially under cold weather. A tradeoff between battery power consumption and cabin heating performance must be considered in cold driving conditions. This preliminary study aims to develop an integrated battery pack and coolant channel model to predict the thermal behavior of a BEV thermal management system. In this study, we develop and calibrate the physical baseline model with testbench data using finite element and CFD software. First, an electrochemical battery cell 1D model (Pseudo-2D or P2D) is built and calibrated against the cell reference data. An integrated pack model consisting of four modules (each has 23 and 25 bricks and a total of 4416 cells) with coolant flow channels is developed using reference and benchmarked data.

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.