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Synthetic fuels can significantly improve the combustion and emission characteristics of heavy-duty diesel engines toward decarbonizing heavy-duty propulsion systems. This work analyzes the effects of engine operating conditions and synthetic fuel properties on spray, combustion, and emissions (soot, NOx) using a supercharging single-cylinder engine experiment and KIVA-4 code combined with CHEMKIN-II and in-house phenomenological soot model. The blended fuel ratio is fixed at 80% diesel and 20% n-paraffin by volume (hereafter DP). Diesel, DP1 (diesel with n-pentane C5H12), DP2 (diesel with n-hexane C6H14), and DP3 (diesel with n-heptane C7H16) are used in engine-like-condition constant volume chamber (CVC) and engine experiments. Boosted engine experiments (1080 rpm, common-rail injection pressure 160 MPa, multi-pulse injection) are performed using the same DP fuel groups under various main injection timings, pulse-injection intervals, and EGR = 0-40%.

A swirl-chamber diesel engine has an indirect injection system in which fuel is injected into a pre-chamber called the swirl-chamber that is separated from the main chamber. Indirect fuel injection systems can be directly mechanically controlled by the camshaft, which is cheaper than electronic control. For these reasons, they are used in diverse industrial applications and automobiles. However, optimization of the swirl-chamber shape and performance tests have been mainly experimental, and there has been insufficient verification of the accuracy of simulations. Thus, we have attempted to verify simulations using a rapid compression and expansion machine that can reproduce the combustion in one engine cycle, with a chamber like a swirl chamber in the cylinder head to visualize the behavior of evaporative sprays and the combustion process. In this study, the authors focused on the wall impingement of the fuel spray and took photos of its liquid phase and ignition.

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.

The purpose of the present study is to find a way to extend a combustion stability limit for diluted combustion in a spark-ignition (SI) gasoline engine which has a high compression ratio. This paper focuses on partial oxidation in an unburned mixture which is observed in the high compression engine and clarifies the effect of partial oxidation in an unburned mixture on the behavior of a flame stretch and the extinction limit. The behavior of the flame stretch was simulated using the detailed chemical kinetics simulation with the opposed-flow flame reactor model. In the simulation, the reactants which have various reaction progress variables were examined to simulate the flame stretch and extinction under the partial oxidation conditions. The mixtures were also diluted by complete combustion products which represent exhaust gas recirculation (EGR).

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.

In this study, reaction path analysis and modeling of NOx reduction phenomena by fast SCR reaction on a Cu-chabazite catalyst were conducted, considering the formation and decomposition of ammonium nitrate (NH4NO3). White crystals of NH4NO3 decompose at temperatures < 200 °C. Thus, the reaction behavior changes at 200 °C under fast SCR reaction conditions. NH4NO3 formation can occur on both Cu sites and Brønsted acid sites, which are active sites for NOx reduction in the Cu-chabazite catalyst, but it is unclear where NH4NO3 accumulates on the catalyst. Analyses using catalyst test pieces with different active sites were performed to estimate this accumulation. The results suggested that NH4NO3 accumulation does not depend on the presence of either Cu sites or Brønsted acid sites. Therefore, it is assumed that NH4NO3 can be accumulated everywhere on the catalyst, including on the zeolite framework. This phenomenon was included in the model as formation/accumulation sites S'.

Performance predictions of advanced turbocharged engines are becoming difficult because conventional engine models are built using performance map data of turbochargers with a proportional integral derivative (PID) controller. Improving prediction capabilities under transient test cycles or real driving conditions is a challenging task. This study applies a machine learning technique to predict turbocharger performances with high accuracy under steady-state and transient conditions. The manipulated signals of engine speed and torque created based on Compressed High-Intensity Radiated Pulse (Chirp signal) and Amplitude-modulated Pseudo-Random Binary Signal (APRBS) are used as inputs to the engine testbed. Data from the engine experiments are used as training data for the AI-based turbocharger model. High prediction accuracy of the AI turbocharger model is achieved with the co-efficient of determination in the model, and cross-validation results are higher than 0.8.

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.

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.

To prevent global warming, further reductions in carbon dioxide are required. It is therefore important to promote the spread of electric vehicles powered by internal combustion engines and electric vehicles without internal combustion engines. As a result, emissions from hybrid electric vehicles equipped with internal combustion engines should be further reduced. Interest in catalytic reactions in an electric field with a higher catalytic activity compared to conventional catalysts has increased because this technology consumes less energy than other electrical heating devices. This study was therefore undertaken to apply a catalytic reaction in an electric field to an exhaust emission control. First, the original experimental equipment was built with a high voltage system used to conduct catalytic activity tests.

The purpose of this paper is to find a universal law to predict a turbulent burning velocity under various operating conditions and engine specifications. This paper presents the relationship between turbulent burning velocity and Karlovitz number. 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 speed and EGR rates, and various engine specifications, i.e. different types of intake ports were tested. Karlovitz number was calculated with Three Dimensional Computational Fluid Dynamics (3D-CFD) and detailed chemical reaction calculation, which condition was based on the experiment. The experimental and calculation results show that turbulent burning velocity is predicted by using Karlovitz number in the engine conditions, which varies depending on engine speed, EGR rates and the designs of intake ports.

In this study, reaction path analysis and modeling of NOx reduction phenomena by selective catalytic reduction (SCR) with NH3 over a Cu-chabazite catalyst were conducted considering changes in the valence state of Cu sites and local structure due to differences in ligands to the Cu sites. The analysis showed that in the Cu-chabazite catalyst, NOx was mainly reduced by adsorbed NH3 on divalent Cu sites accompanied by a change in valence state of Cu from divalent to monovalent. It is known that the activation energy of NOx reduction on a Cu-chabazite catalyst changes between low temperatures ≤ 200 °C and mid to high temperatures ≥ 300 °C. To express this phenomenon, a reversible hydrolysis reaction based on the difference in coordination state of hydroxyl groups (OH−) to Cu sites at low and high temperatures was introduced into the model.

Battery models are being developed as a component of the powertrain systems of hybrid electric vehicles (HEVs) to predict the state of charge (SOC) accurately. Electrically heated catalysts (EHCs) can be employed in the powertrains of HEVs to reach the catalyst light off temperature in advance. However, EHCs draw power from the battery pack and hence sufficient energy needs to be stored to power auxiliary components. In series HEVs, the engine is primarily used to charge the battery pack. Therefore, it is important to develop a control strategy that triggers engine start/stop conditions and reduces the frequency of engine operation to minimize the equivalent fuel consumption. In this study, a battery pack model was constructed in MATLAB-Simulink to investigate the SOC variation of a high-power lithium ion battery during extreme engine cold start conditions (-7°C) with/without application of an EHC.

To identify ways of achieving good mixture formation and heat release in diesel spray combustion, we have performed Large Eddy Simulation (LES) using a detailed chemical reaction mechanism to study the temporal and spatial distribution of the local equivalence ratios and heat release rate. Here we characterize the effect of the fuel injection rate profile on these processes in the combustion chamber of a diesel engine. Two injection rate profiles are considered: a standard (STD) profile, which is a typical modern common rail injection profile, and the inverse delta (IVD) profile, which has the potential to suppress rich mixture formation in the spray tip region. Experimental data indicate that the formation of such mixtures may extend the duration of the late combustion period and thus reduce thermal efficiency.

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.

Three-way catalyst (TWC) converters are often used to purify toxic substances contained in exhaust emissions from gasoline engines. However, a large amount of CO, NOx and THC may be emitted before the TWC reaches its light-off temperature during a cold start. In this work, a numerical model was developed for studying the purification performance of a close-coupled TWC converter during the cold start period. The TWC model was built using axisuite, commercial software by Exothermia S.A. Model gas experiments were designed for calibrating the chemical reaction scheme and corresponding reaction rate parameters in the TWC model. The TWC model was able to simulate the purification performance of CO, NOx and THC under both lean and rich air-fuel equivalence ratios (λ) for different conditions. The light-off temperature and oxygen storage capacity (OSC) behavior were also successfully validated in the model. Vehicle tests were conducted on a chassis dynamometer to verify the TWC model.

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.

Ammonia-selective catalytic reduction (SCR) systems have been introduced commercially in diesel vehicles, however catalyst systems with higher conversion efficiency and better control characteristics are required to know the actual emissions during operation and the emissions in random test cycles. Computational fluid dynamics (CFD) is an effective approach when applied to SCR catalyst development, and many models have been proposed, but these models need experimental verification and are limited in the situations they apply to. Further, taking account of redox cycle is important to have better accuracy in transient operation, however there are few models considering the cycle. Model development considering the redox reactions in a zeolite catalyst, Cu-ZSM-5, is the object of the research here, and the effects of exhaust gas composition on the SCR reaction and NH3 oxidation at high temperatures are investigated.

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.

Much effort has been devoted to studies on auto-ignition engines of gasoline including homogeneous-charge combustion ignition engines over 30 years, which will lead to lower exhaust energy loss due to high-compression ratio and less dissipation loss due to throttle-less device. However, the big problem underlying gasoline auto-ignition is knocking phenomenon leading to strong noise and vibration. In order to overcome this problem, we propose the principle of colliding pulsed supermulti-jets. In a prototype engine developed by us, octagonal pulsed supermulti-jets collide and compress the air around the center point of combustion chamber, which leads to a hot spot area far from chamber walls. After generating the hot spot area, the mechanical compression of an asymmetric double piston unit is added in four-stroke operation, which brings auto-ignition of gasoline.