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In-cylinder pressure measurement is an important tool in internal combustion engine research and development for combustion, cycle performance, and knock analysis in spark-ignition engines. In a typical laboratory setup, a sub crank angle resolved (typically between 0.1o and 0.5o) optical encoder is installed on the engine crankshaft, and a piezoelectric pressure transducer is installed in the engine cylinder. The charge signal produced by the transducer due to changes in cylinder pressure during the engine cycle is converted to voltage by a charge amplifier, and this analog voltage is read by a high-speed data acquisition (DAQ) system at each encoder trigger pulse. The high speed of engine operation and the need to collect hundreds of engine cycles for appropriate cycle-averaging requires significant processor speed and memory, making typical data acquisition systems very expensive.

Spark ignition engines utilize catalytic converters to reform harmful exhaust gas emissions such as carbon monoxide, unburned hydrocarbons, and oxides of nitrogen into less harmful products. Aftertreatment devices require the use of expensive catalytic metals such as platinum, palladium, and rhodium. Meanwhile, tightening automotive emissions regulations globally necessitate the development of high-performance exhaust gas catalysts. So, automotive manufactures must balance maximizing catalyst performance while minimizing production costs. There are thousands of different recipes for catalytic converters, with each having a different effect on the various catalytic chemical reactions which impact the resultant tailpipe gas composition. In the development of catalytic converters, simulation models are often used to reduce the need for physical parts and testing, thus saving significant time and money.

The possibility to operate current diesel engines in dual-fuel mode with the addition of an alternative fuel is fundamental to accelerate the energy transition to achieve carbon neutrality. The simulation of the dual- fuel combustion process with 0D/1D combustion models is fundamental for the performance prediction, but still particularly challenging, due to chemical interactions of the mixture. The authors defined a novel data-driven workflow for the development of combustion reaction mechanisms and used it to generate a dual-fuel mechanism for Ammonia and Diesel Primary Reference Fuels (DPRF) suitable for efficient combustion simulations in heavy duty engines, with variable cetane number Diesel fuels. A baseline reaction mechanism was created by merging the detailed ammonia mechanism by Glarborg et al. with reaction pathways for n- hexadecane and 2,2,4,4,6,8,8-heptamethylnonane from a well-established multi-component fuel mechanism.

We propose a novel dual-fuel combustion model for simulating heavy-duty engines with the G-Equation. Dual-Fuel combustion strategies in such engines features direct injection of a high-reactivity fuel into a lean, premixed chamber which has a high resistance to autoignition. Distinct combustion modes are present: the DI fuel auto-ignites following chemical ignition delay after spray vaporization and mixing; a reactive front is formed on its surroundings; it develops into a well-structured turbulent flame, which propagates within the premixed charge. Either direct chemistry or the flame-propagation approach (G- Equation), taken alone, do not produce accurate results. The proposed Dual-Fuel model decides what regions of the combustion chamber should be simulated with either approach, according to the local flame state; and acts as a “kernel” model for the G- Equation model. Direct chemistry is run in the regions where a premixed front is not present.

In the automotive industry, performing steady-state tests on an internal combustion engine can be a time consuming and costly process, but it is necessary to ensure the engine meets performance and emissions criteria set by the manufacturer and regulatory agencies. Any measures that can reduce the amount of time required to complete these testing campaigns provides significant benefits to manufacturers. The purpose of this work is then to develop a systematic approach to minimize the time required to conduct a steady-state engine test campaign using a Savitsky-Golay filter to calculate measured signal gradients for continuous steady-state detection. Experiments were conducted on an Armfield CM11-MKII Gasoline Engine test bench equipped with a 1.2L 3-cylinder Volkswagen EA111 R3 engine. The test bench utilizes throttle position control and an eddy current dynamometer braking system with automatic PID control of engine speed.

With the ever-increasing demand for sustainable energy, alcohol fuels have garnered interest for use in heavy duty engines. The significant infrastructure for ethanol production and blending of ethanol with gasoline make these fuels/fuel blends desirable candidates. However, development of heavy duty engine technology that is capable of burning alcohol fuels while retaining the advantages of traditional diesel combustion requires an improved understanding of the soot formation for these fuels under conditions relevant to mixing-controlled combustion. This work uses an extinction diagnostic to study the sooting tendency of ethanol and gasoline/ethanol blends ranging from E10 to E98 during ignition in a homogeneous environment. Experiments were conducted in a rapid compression machine (RCM) for compressed conditions of 20 ± 1 bar and an approximately constant temperature (± 10K) which was unique for each fuel.

The American Society for Testing and Materials (ASTM) D613 test method involves the use of a variable compression ratio CFR F5 engine to determine the cetane number of diesel fuels for use in compression ignition engines. The CFR F5 remains relatively unchanged since its conception, utilizing a swirl prechamber, mechanical jerk fuel pump, and a 10.3 MPa cracking pressure pintle nozzle mechanical injector. Recent efforts to improve the repeatability of the F5 engine involved the development of prototype engines equipped with electronic fuel injection (EFI) and upgraded high-speed instrumentation. These modifications have demonstrated the capability to improve the ASTM D613 precision limits by at least a factor of two. Parameterization of injection strategy has further optimized the test method, producing cycle-to-cycle variations of ignition delay analogous to modern day compression ignition engines.

Over the past few decades, numerous studies have been performed to investigate how to improve the precision of the ASTM D613 Standard Test Method for Cetane Number of Diesel Fuel Oil. Many of these studies concluded that inconsistent combustion is the main contributing factor behind the lack of precision in the cetane number method, followed by shortcomings in the instrumentation used to measure ignition delay. This study is a continuation of recent work that investigated the benefits of installing a high-pressure common rail electronic fuel injection (EFI) system onto a CFR F5 cetane engine. The previous work presented baseline engine measurements that compared EFI against the original mechanical fuel injection system, along with computational fluid dynamics (CFD) simulations of the EFI injection and combustion processes. The previous work also indicated EFI makes it possible to improve the current ASTM D613 cetane test precision limits by at least a factor of two.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.

With the introduction of EV technology into the light-duty vehicle market, the demand for gasoline in conventional spark ignition engines is projected to decline in the coming decades. Therefore, researchers have been investigating the use of gasoline and other light fuels in heavy-duty engine applications. In heavy-duty engines, the combustion mode will likely be non-premixed, mixing-controlled combustion, where the rate of combustion is determined by the fuel-air mixing process. This creates a range of mixture conditions inside the engine cylinder at every instance in time. The goal of this research is to experimentally quantify the sooting behaviors of light fuels under a range of compression ignition engine mixture conditions (i.e., a range of equivalence ratios).

Reactivity Controlled Compression Ignition (RCCI) is a low temperature combustion regime that has demonstrated ultra-low NOx and soot while achieving high thermal efficiency. RCCI uses a low reactivity premixed charge which is ignited via direct injection of a high reactivity fuel. The aim is to create a nearly homogeneous charge but maintain control over the combustion timing via the ratio between the premixed and direct injected fuel, hence controlling global reactivity via reactivity gradients in-cylinder. RCCI combustion with gasoline as the premixed fuel and diesel as the high reactivity fuel has shown good combustion timing controllability. However, RCCI with alcohol fuels, in which pure alcohol is the low reactivity premixed fuel and the alcohol doped with a reactivity enhancer is the direct injected high reactivity fuel, has shown a lack of control over the combustion timing, which is undesirable.

As the global economy grows, so does the demand for heavy-duty commercial vehicles, both on-road and off-road. Currently, these vehicles are powered almost entirely by diesel engines. There is an imminent need to reduce the greenhouse gases (GHG) from this growing sector, but alternatives to the internal combustion engine face many challenges and can increase GHG emissions. For example, through simple analysis, this work will show that a Class 8 long haul on-highway truck powered entirely by battery electrics and charged from the average US electrical grid, yields significantly higher CO2 emissions per ton-mile as compared to an engine using alternative fuels. Thus, the most pragmatic and impactful way to reduce GHG emissions in commercial vehicles is using low carbon alternative fuels, such as ethanol made from renewable sources.

Expanding upon the authors’ previous work which utilized a GT-Power model of the Cooperative Fuels Research (CFR) engine under Research Octane Number (RON) conditions, this work defines the boundary conditions of the CFR engine under Motored Octane Number (MON) test conditions. The GT-Power model was validated against experimental CFR engine data for primary reference fuel (PRF) blends between 60 and 100 under standard MON conditions, defining the full range of interest of MON for gasoline-type fuels. The CFR engine model utilizes a predictive turbulent flame propagation sub-model, and a chemical kinetic solver for the end-gas chemistry. The validation was performed simultaneously for thermodynamic and chemical kinetic parameters to match in-cylinder pressure conditions, burn rate, and knock point prediction with experimental data, requiring only minor modifications to the flame propagation model from previous model iterations.

This work explores the effectiveness of common rail fuel injectors equipped with Grouped Hole Nozzles (GHNs) in aiding the mixing process and reducing particulate matter (PM) emissions of Conventional Diesel Combustion (CDC) engines, while maintaining manageable Oxides of Nitrogen (NOx) levels. Parallel (pGHN), converging (cGHN) and diverging (dGHN) - hole GHNs were studied and the results were compared to a conventional, single hole nozzle (SHN) with the same flow area. The study was conducted on a single cylinder medium-duty engine to isolate the effects of the combustion from multi-cylinder effects and the conditions were chosen to be representative of a typical mid-load operating point for an on-road diesel engine. The effects of injection pressure and the Start of Injection (SOI) timing were explored and the tradeoffs between these boundary conditions are examined by using a response surface fitting technique, to identify an optimum operating condition.

Machine learning methods, such as decision trees and deep neural networks, are becoming increasingly important and useful for data analysis in various scientific fields including dynamics and control, signal processing, pattern recognition, fluid mechanics, and chemical synthesis, etc. For future engine design and performance optimization, there is an urgent need for a robust predictive model which could capture the major combustion properties such as autoignition and flame propagation of multicomponent fuels under a wide range of engine operating conditions, without massive experimental measurement or computational efforts. It will be shown that these long-held limitations and challenges related to complex fuel combustion and engine research could be readily solved by implementing machine learning methods.

Given increasingly stringent emission targets, engine efficiency has become of foremost importance. While increasing engine compression ratio can lead to efficiency gains, it also leads to higher in-cylinder pressure and temperatures, thus increasing the risk of knock. One potential solution is the use of a Variable Compression Ratio system, which is capable of exploiting the advantages coming from high compression ratio while limiting its drawbacks by operating at low engine loads with a high compression ratio, and at high loads with a low compression ratio, where knock could pose a significant threat. This paper describes the design of a model for the evaluation of fuel consumption for an engine equipped with a VCR system over representative drive cycles. The model takes as inputs; a switching time for the VCR system, the vehicle characteristics, engine performance maps corresponding to two different compression ratios, and a drive cycle.

Variable Compression Ratio systems are an increasingly attractive solution for car manufacturers in order to reduce vehicle fuel consumption. By having the capability to operate with a range of compression ratios, engine efficiency can be significantly increased by operating with a high compression ratio at low loads, where the engine is normally not knock-limited, and with a low compression ratio at high load, where the engine is more prone to knock. In this way, engine efficiency can be maximized without sacrificing performance. This study aims to analyze how the effectiveness of a VCR system is affected by various powertrain and vehicle parameters. By using a Matlab model of a VCR system developed in Part 1 of this work, the influence of the vehicle characteristics, the drive cycle, and of the number of stages used in the VCR system was studied.

Developments in modern spark ignition (SI) engines such as intake boosting, direct-injection, and engine downsizing techniques have demonstrated improved performance and thermal efficiency, however, these strategies induce significant deviation in end-gas pressure/temperature histories from those of the traditional Research and Motor Octane Number (RON and MON) standards. Attempting to extrapolate the anti-knock performance of fuels tested under the traditional RON/MON conditions to boosted operation has yielded mixed results in both SI and advanced compression ignition (ACI) engines. This consideration motivates the present work with seeks to establish a pathway towards the development of the test conditions of a boosted octane number, which would better correlate to fuel performance at high intake pressure conditions.

Fundamental understanding of the sources of fuel-derived Unburned Hydrocarbon (UHC) emissions in heavy duty diesel engines is a key piece of knowledge that impacts engine combustion system development. Current emissions regulations for hydrocarbons can be difficult to meet in-cylinder and thus after treatment technologies such as oxidation catalysts are typically used, which can be costly. In this work, Computational Fluid Dynamics (CFD) simulations are combined with engine experiments in an effort to build an understanding of hydrocarbon sources. In the experiments, the combustion system design was varied through injector style, injector rate shape, combustion chamber geometry, and calibration, to study the impact on UHC emissions from mixing-controlled diesel combustion.

Heavy-duty vehicles, currently the second largest source of fuel consumption and carbon emissions are projected to be fastest growing mode in transportation sector in future. There is a clear need to increase fuel efficiency and lower emissions for these engines. The Opposed-Piston Engine (OP Engine) has the potential to address this growing need. In this paper, results are presented for a 9.8L three-cylinder two-stroke OP Engine that shows the potential of achieving 55% brake thermal efficiency (BTE), while simultaneously satisfying emission targets for tail pipe emissions. The two-stroke OP Engines are inherently more cost effective due to less engine parts. The OP Engine architecture presented in this paper can meet this performance without the use of waste heat recovery systems or turbo-compounding and hence is the most cost effective technology to deliver this level of fuel efficiency.