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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.

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.

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.

Swirl injector spray at high fuel temperatures has unique characteristics [1][2][3][4] compared to normal fuel temperature spray such as strong penetration and narrow spray width. These characteristics have a possibility for improving fuel consumption and exhaust emission at the cold start condition. Thus, Swirl injector spray at high fuel temperature conditions was modeled in a CFD(Computational Fluid Dynamics) code by using a multi components fuel evaporation model and other spray sub-models to predict the mixture formation process at the cold start condition. Results show that, high temperature fuel decreases wall film amount and increases vapor amount. It can be concluded that high temperature fuel has the possibility for improving fuel consumption and exhaust emission at the cold start condtion.

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%.

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.