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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.

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.

Natural gas has been used in spark-ignition (SI) engines of natural gas vehicles (NGVs) due to its resource availability and stable price compared to gasoline. It has the potential to reduce carbon monoxide emissions from the SI engines due to its high hydrogen-to-carbon ratio. However, short running distance is an issue of the NGVs. In this work, methodologies to improve the fuel economy of a heavy-duty commercial truck under the Japanese Heavy-Duty Driving Cycle (JE05) is proposed by numerical 1D-CFD modeling. The main objective is a comparative analysis to find an optimal fuel economy under three variable mechanisms, variable valve timing (VVT), variable valve actuation (VVA), and variable compression ratio (VCR). Experimental data are taken from a six-cylinder turbocharged SI engine fueled by city gas 13A. The 9.83 L production engine is a CR11 type with a multi-point injection system operated under a stoichiometric mixture.

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).

Soot mass production was investigated in high-boosted diesel engine tests by changing various operating parameters. A mixed timescale subgrid model of large eddy simulation (LES) was applied to simulate the detailed mixture formation, combustion and soot formation influenced by turbulence in diesel engine combustion. The combustion model used a direct integration approach with an explicit ordinary differential equation (ODE) solver and additional parallelization by OpenMP. Soot mass production within a computation cell was determined from a phenomenological soot formation model developed by WASEDA University. The model was combined with the LES code and included the following important steps: particle inception, in which naphthalene was assumed to grow irreversibly to form soot; surface growth with the addition of C2H2; surface oxidation due to OH radicals and O2 attack; particle coagulation; and particle agglomeration.

In the conventional approval test method of fuel consumption for heavy-duty diesel vehicles currently in use in Japan, the fuel consumption under the transient test cycle is calculated by integrating the instantaneous fuel consumption rate referred from a look-up table of fuel consumptions measured under the steady state conditions of the engine. Therefore, the transient engine performance is not considered in this conventional method. In this study, a highly accurate test method for fuel consumption in which the map-based fuel consumption rate is corrected using the transient characteristics of individual engines was developed. The method and its applicability for a heavy-duty diesel engine that complied with the Japanese 2009 emission regulation were validated.

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.

For diesel emission control systems containing a Diesel Oxidation Catalyst (DOC) and a Catalyzed Soot Filter (CSF) the DOC is used to oxidize the additional fuel injected into the cylinder and/or the exhaust pipe for the purpose of increasing the CSF inlet temperature during the soot regeneration. Hydrocarbon (HC) oxidation performance of the DOC is affected by HC species as well as a catalyst design, i.e., precious metal species, support materials and additives. How engine-out HC species vary as a function of fuel supply conditions is not well understood. In addition, the relationship between catalyst design and oxidation activity of different hydrocarbon species requires further study. In this study, diesel fuel was supplied by in-cylinder, post injection and exhaust HC species were measured by a gas chromatograph-mass spectrometry (GC-MS) and a gas analyzer. The post injection timing was set to either 73°, 88° or 98° ATDC(after top dead center).

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.

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.

The use of biomass fuels for vehicles has been a focus of attention all over the world in terms of prevention of global warming, effective utilization of resources and local revitalization. For the purpose of beneficial use of unused biomass resources, the movement of the use of bioethanol and biodiesel made from them has spread in Japan. In Japan, biodiesel is mainly made from waste cooking oil collected by local communities or governments, and in terms of local production for local consumption, it is used as neat fuel (100% biofuel) or mixed with diesel fuel in high concentration for the vehicles. On the other hand, extremely low emission level must be kept for not only gasoline vehicles but also diesel vehicles in the post new long-term regulation implemented from 2009 in Japan.

Application of biodiesel fuel (BDF) to diesel engine is very effective to reduce CO2 emission, because bio-diesel is carbon neutral in principle. However, when biodiesel was applied to conventional diesel engines without modification for biodiesel, NOx emission was increased by the change in fuel characteristics. It is necessary to introduce some strategies into diesel engines fuelled with biodiesel for lower NOx emission than conventional diesel fuel case. The purpose of this study is to reveal that exhaust gas recirculation (EGR) is one of the solutions for the reduction of NOx emission and meeting the future emission regulations when using biodiesel. Neat Rapeseed oil methyl ester (RME) as a biodiesel (B100) was applied to diesel engines equipped with high pressure loop (HPL) EGR system and low pressure loop (LPL) EGR system. Cooled HPL EGR was increased during steady-state operations and JE05 transient mode tests.

Application of biodiesel fuel (BDF) to diesel engine is very effective to reduce CO2 emission, because biodiesel is carbon neutral in principle. However, biodiesels yield an increase in NOx emission from conventional diesel engine, compared with diesel fuel case. Therefore, some strategies are needed for meeting the future emission regulations when using biodiesel. In this study, rapeseed oil methyl ester (RME) was applied to diesel engine equipped with exhaust gas recirculation (EGR) system and NOx storage reduction (NSR) catalyst. NOx reduction rate of NSR catalyst was drastically decreased by using RME, even if injection quantity of RME for rich spike was enhanced. However, an increase in EGR rate could reduce NOx emission without the deterioration in smoke and PM emissions.

To suppress knock in small gasoline engines, the coolant flow of a single-cylinder engine was improved by using two methods: a multi-dimensional knock prediction method combining a Flamelet model with a simple chemical kinetics model, and a method for predicting combustion chamber wall temperature based on a thermal fluid calculation that coupled the engine coolant and the engine structure (engine head, cylinder block, and head gasket). Through these calculations as well as the measurement of wall temperatures and the analysis of combustion by experiments, the effects of wall temperature distribution and consequent unburnt gas temperature distribution on knock onset timing and location were examined. Furthermore, a study was made to develop a method for cooling the head side, which was more effective to suppress knock: the head gasket shape was modified to change the coolant flow and thereby improve the distribution of wall temperatures on the head side.

The biomass fuel is expected to solve the global warming due to a carbon neutral. A rapeseed oil methyl ester (RME) as biomass fuel was selected, and also a low sulfur diesel fuel is tested as reference fuel in this study. The experiments were carried out to improve diesel emissions and engine performance using high boost and high rate EGR system and a common rail injection system in a single cylinder engine. The diesel emissions and engine performance have been measured under the experimental conditions such as charging boost pressure from atmospheric pressure to 401.3kPa maximum and changing EGR rate from 0% to 40% maximum. RME contain about 10 mass % oxygen in the fuel molecule. Furthermore, RME does not contain aromatic hydrocarbons in the fuel. Due to these chemical properties, RME can be used at 40% high EGR condition.

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%.

The use of biodiesel fuels as an alternative fuel for petroleum diesel fuel is very effective for the reduction of CO2 emission, because biodiesel is produced from renewable biomass resources. Biodiesel is usually blended to conventional diesel fuel in various proportions. It is possible that this biodiesel blending causes the problems on emission characteristics of modern diesel engine, because it could be confirmed that the application of neat biodiesel to modern diesel engines whose control parameters were optimized for conventional diesel fuel deteriorated the emission performances. It is necessary to clarify the effect of biodiesel blending on exhaust emissions of modern diesel engine. Rapeseed oil methyl ester (RME) was selected as a biodiesel used in this study.