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Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

Gasoline compression ignition shows great potential in reducing NOx and soot emissions with competitive thermal efficiency by leveraging the properties of gasoline fuels and the high compression ratio of compression ignition engines operating air-dilute. Meanwhile, its control becomes challenging due to not only the properties of different gasoline-type fuels but also the impacts of injection strategies on the in-cylinder reactivity. As such, a computationally efficient zero-dimension combustion model can significantly reduce the cost of control development. In this study, a previously developed zero-dimension combustion model for gasoline compression ignition was extended to multiple gasoline-type fuel blends and a port fuel injection/direct fuel injection strategy. Tests were conducted on a 12.4-liter heavy-duty engine with five fuel blends.

Multi-mode combustion strategies may provide a promising pathway to improve thermal efficiency in light-duty spark ignition (SI) engines by enabling switchable combustion modes, wherein an engine may operate under advanced compression ignition (ACI) at low load and spark-assisted ignition at high load. The extension from the SI mode to the ACI mode requires accurate control of intake charge conditions, e.g., pressure, temperature and equivalence ratio, in order to achieve stable combustion phasing and rapid mode-switches. This study presents results from computational fluid dynamics (CFD) analysis to gain insights into mixture charge formation and combustion dynamics pertaining to auto-ignition processes. The computational study begins with a discussion of thermal wall boundary condition that significantly impacts the combustion phasing.

Advanced compression ignition (ACI) operation in gasoline direct injection (GDI) engines is a promising concept to reduce fuel consumption and emissions at part load conditions. However, combustion phasing control and the limited operating range in ACI mode are a perennial challenge. In this study the combined impact of fuel properties and engine control strategies in ACI operation are investigated. A design of experiments method was implemented using a three level orthogonal array to determine the sensitivity of engine control parameters on the engine load, combustion noise and stability under low load ACI operation for three RON 98 gasoline fuels, each exhibiting disparate chemical composition. Furthermore, the thermodynamic state of the compression histories was studied with the aid of the pressure-temperature framework.

Currently there is a significant research effort being made in gasoline spark/ignition (SI) engines to understand and reduce cycle-to-cycle variations. One of the phenomena that presents this cycle-to-cycle variation is combustion knock, which also happens to have a very stochastic behavior in modern SI engines. Conversely, the CFR octane rating engine presents much more repeatable combustion knock activity. The aim of this study is to assess the impact of fuel composition on the cycle to cycle variation of the pressure and timing of end gas autoignition. The variation of cylinder conditions at the timing of end-gas autoignition (knock point) for a wide selection of cycle ensembles have been analyzed for several constant RON 98 fuels on the CFR engine, as well as in a modern single-cylinder gasoline direct injection (GDI) SI engine operated at RON-like intake conditions.

A multi-mode operation strategy, wherein an engine operates compression ignited at low load and spark ignited at high load, is an attractive way of achieving better part-load efficiency in a light duty spark ignition (SI) engine. Given the sensitivity of compression ignition operation to in-cylinder conditions, one of the critical requirements in realizing such strategy in practice, is accurate control of intake charge conditions - pressure (P), temperature (T) and equivalence ratio (φ), in order to achieve stable combustion and enable rapid mode-switches. This paper presents the first of a two part study, correlating ignition delay data for five RON98 gasoline blends measured under engine-relevant operating conditions in a rapid compression machine (RCM), to the cylinder conditions obtained from a modern SI engine operated in compression ignition mode.

A multi-mode operation strategy, wherein an engine operates compression ignited at low load and spark-ignited at high load, is an attractive way to achieve better part-load efficiency in light duty, spark-ignition (SI) engines, while maintaining robust operation and control across the operating map. Given the sensitivity of compression ignition operation to in-cylinder conditions, one of the critical requirements in realizing such a strategy in practice is accurate control of intake charge conditions - pressure, temperature, as well as fuel loading, to achieve stable combustion and enable rapid mode-switches. A reliable way of characterizing fuels under such operating schemes is key.

The knock resistance of fuels has been historically measured using the ASTM RON and MON methods. However, significant discrepancies between the fuel octane number and knock-limited performance in modern spark-ignited (SI) engines have been well-documented. Differences between the operating conditions of the Cooperative Fuels Research (CFR) engine during RON rating and those attained in modern SI engines have been highlighted in the literature. While octane ratings are performed for each fuel on the CFR engine at the lambda that provides the highest knockmeter reading, modern SI engines are generally operated at stoichiometry and knock intensity is based on the high frequency cylinder pressure oscillations associated with knocking combustion. In the present work, an instrumented CFR engine was used to analyze lambda effects on both the conventional knockmeter RON rating method and cylinder pressure transducer based knock intensity.

The CFR F1 engine is the standard testing apparatus used for rating the research octane number (RON) of gasoline fuels. Unlike the motor octane number (MON) method, where the intake port temperature after the carburetor is controlled by an electric heater, the mixture temperature can vary during the RON test due to the heat of vaporization (HoV) of the fuel. Ethanol is receiving increasing attention as a high octane and high HoV fuel component. This work presents an analysis of the combustion characteristics during the RON rating of ethanol fuel blends according to the standard ASTM D2699 method, highlighting the effects of ethanol concentration and base fuel composition. All fuels were blended to a constant RON of 98. Ethanol levels varied from 0 to 50 vol% and the base fuels were surrogate blends composed of primary reference fuels (PRF), toluene standardization fuels (TSF), and a four component gasoline surrogate.

Of late there has been a resurgence in studies investigating parameters that quantify combustion knock in both standardized platforms and modern spark-ignition engines. However, it is still unclear how metrics such as knock (octane) rating, knock onset, and knock intensity are related and how fuels behave according to these metrics across a range of conditions. As part of an ongoing study, the air supply system of a standard Cooperative Fuel Research (CFR) F1/F2 engine was modified to allow mild levels of intake air boosting while staying true to its intended purpose of being the standard device for American Society for Testing and Materials (ASTM)-specified knock rating or octane number tests. For instance, the carburation system and intake air heating manifold are not altered, but the engine was equipped with cylinder pressure transducers to enable both logging of the standard knockmeter readout and state-of-the-art indicated data.

The benefits of blending ethanol into gasoline fuel are well established. Ethanol’s high latent heat of vaporisation and chemical auto-ignition resistance combine in producing significant knock resistance, enabling higher compression ratio and/or higher charge boosting. Its high flame speed characteristics result in shorter burn durations. Its high knock resistance and rapid burning enable ignition phasing optimisation. These factors all improve the efficiency of spark ignition (SI) engines. Current “flex-fuel” vehicles are designed to operate on both conventional gasoline as well as blends containing higher volumes of ethanol and/or methanol, the former being commonly known as E85. The American Society for Testing and Materials ASTM D5798 specification for ethanol fuel blends was adapted in 2011 to prescribe a minimum ethanol content of 51 % with the remainder able to consist of low octane blending streams.

This paper investigated the laminar flame speed behavior of a matrix of ten spark-ignition fuels and fuel components using a spherical combustion bomb. The analysis methodology relied solely on the in-bomb pressure data. For each fuel measurements were performed at five different air-fuel ratios covering a mixture range from lean to rich. Six repeat combustion pressure traces were recorded for each air-fuel ratio, with each record containing approximately 90 data points. The entire sequence was performed at two initial temperatures resulting in a database of over 5000 individual calculations of laminar flame speed per fuel. A regression technique was employed to determine the relevant flame-speed parameters. The fuel matrix included synthetic and conventional crude-derived gasoline fuels as well as a selection of blend components that could be used in the formulation of synthetic gasoline.