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Ducted Fuel Injection (DFI) engines have emerged as a promising technology in the pursuit of a clean and efficient combustion process. This article aims at elucidating the effect of piston geometry on the engine performance and emissions of a metal DFI engine. Three different types of pistons were investigated and the main piston design features including the piston bowl diameter, piston bowl slope angle, duct angle and the injection nozzle position were examined. To achieve the target, computational fluid dynamics (CFD) simulations were conducted coupled to a reduced chemical kinetics mechanism. Extensive validations were performed against the measured data from a conventional diesel engine. To calibrate the soot model, genetic algorithm and machine learning methods were utilized. The simulation results highlight the pivotal role played by piston bowl diameter and fuel injection angle in controlling soot emissions of a DFI engine.

This paper presents a comprehensive analysis of emerging powertrain technologies for a wide spectrum of vehicles, ranging from light-duty passenger vehicles to medium and heavy-duty trucks. The study focuses on the anticipated evolution of these technologies over the coming decades, assessing their potential benefits and impact on sustainability. The analysis encompasses simulations across a wide range of vehicle classes, including compact, midsize, small SUVs, midsize SUVs, and pickups, as well as various truck types, such as class 4 step vans, class 6 box trucks, and class 8 regional and long-haul trucks. It evaluates key performance metrics, including fuel consumption, estimated purchase price, and total cost of ownership, for these vehicles equipped with advanced powertrain technologies such as mild hybrid, full hybrid, plug-in hybrid, battery electric, and fuel cell powertrains.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

The Argon Power Cycle (APC) is a novel zero-emission closed-loop argon recirculating engine cycle which has been developed by Noble Thermodynamics Systems, Inc. It provides a significant gain in indicated thermal efficiency of the reciprocating engine by breathing oxygen and argon rather than air. The use of argon, a monatomic gas, greatly increases the specific heat ratio of the working fluid, resulting in a significantly higher ideal Otto cycle efficiency. This technology delivers a substantial improvement in reciprocating engine performance, maximizing the energy conversion of fuel into useful work. Combined Heat and Power (CHP) operating under the APC represents a promising solution to realize a net-zero-carbon future, providing the thermal energy that hard-to-electrify manufacturing processes need while at the same time delivering clean, dispatchable, and efficient power.

The internal combustion engine (ICE) has long dominated the heavy-duty sector by using liquid fossil fuels such as diesel but global commitments by countries and OEMs to reduce lifecycle carbon dioxide (CO2) emissions has garnered interest in alternative fuels like hydrogen. Hydrogen is a unique gaseous fuel that contains zero carbon atoms and has desired thermodynamic properties of high energy density per unit mass and high flame speeds. However, there are challenges related to its adoption to the heavy-duty sector as a drop-in fuel replacement for compression ignition (CI) diesel combustion given its high autoignition resistance. To overcome this fundamental barrier, engine manufacturers are exploring dual fuel combustion engines by substituting a fraction of the diesel fuel with hydrogen which enables fuel flexibility when there is no infrastructure and retrofittability to existing platforms.

Methanol is one of the most promising fuels for the decarbonization of the off-road and transportation sectors. Although methanol is typically seen as an alternative fuel for spark ignition engines, mixing-controlled compression ignition (MCCI) combustion is typically preferred in most off-road and medium-and heavy-duty applications due to its high reliability, durability and high-efficiency. In this paper, the potential of using ignition enhancers to enable methanol MCCI combustion was investigated. Methanol was blended with 2-ethylhexyl nitrate (EHN) and experiments were performed in a single-cylinder production-like diesel research engine, which has a displacement volume of 0.83 L and compression ratio of 16:1. The effect of EHN has been evaluated with three different levels (3%vol, 5%vol, and 7%vol) under low- and part-load conditions. The injection timing has been swept to find the stable injection window for each EHN level and load.

The rise in demand for electric and hybrid vehicles, the issue of bearing currents in electric motors has become increasingly relevant. These vehicles use inverters with high frequency switch that generates the common mode voltage and current, the main factor responsible for bearing issues. In the machine structure, there are some parasitic capacitances that exist inherently. They provide a low impedance path for the generated current, which flows through the machine bearing. Investigating this problem in practical scenarios during the design stage is costly and requires great effort to measure these currents. For this reason, a strategy of analysis aided by electromagnetic simulation software can achieve desired results in terms of complexity and performance. This work proposes a methodology using Ansys Maxwell software to simulate two-dimensional (2D) and three-dimensional (3D) model of a three-phase permanent magnet motor with eight poles.

Metal cutting/machining is a widely used manufacturing process for producing high-precision parts at a low cost and with high throughput. In the automotive industry, engine components such as cylinder heads or engine blocks are all manufactured using such processes. Despite its cost benefits, manufacturers often face the problem of machining chips and cutting oil residue remaining on the finished surface or falling into the internal cavities after machining operations, and these wastes can be very difficult to clean. While part cleaning/washing equipment suppliers often claim that their washers have superior performance, determining the washing efficiency is challenging without means to visualize the water flow. In this paper, a virtual engineering methodology using particle-based CFD is developed to address the issue of metal chip cleanliness resulting from engine component machining operations. This methodology comprises two simulation methods.

To properly compare and contrast the environmental performance of one vehicle technology against another, it is necessary to consider their production, operation, and end-of-life fates. Since 1995, Argonne’s GREET® life cycle analysis model (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) has been annually updated to model and refine the latest developments in fuels and materials production, as well as vehicle operational and composition characteristics. Updated cradle-to-grave life cycle analysis results from the model’s latest release are described for a wide variety of fuel and powertrain options for U.S. light-duty and medium/heavy-duty vehicles. Light-duty vehicles include a passenger car, sports utility vehicle (SUV), and pick-up truck, while medium/heavy-duty vehicles include a Class 6 pickup-and-delivery truck, Class 8 day-cab (regional) truck, and Class 8 sleeper-cab (long-haul) truck.

Ethanol blending is one method that can be used to reduce knock in spark ignition engines by decreasing the autoignition reactivity of the fuel and modifying its laminar flame speed. In this paper, the effects of ethanol blending on knock propensity and flame speed of petroleum and low-carbon gasoline fuels is analyzed. To do so, surrogate fuels were formulated for methanol-to-gasoline (MTG) and ethanol-to-gasoline (ETG) based on the fuels’ composition, octane number, and select physical properties; and 0-D and 1-D chemical kinetics simulations were performed to investigate reactivity and laminar flame speed, respectively. Results of MTG and ETG were compared against those of PACE-20, a well-characterized surrogate for regular E10 gasoline. Similarly to PACE-20, blending MTG and ETG with ethanol increases the fuel’s research octane number (RON) and sensitivity.

Low-temperature gasoline combustion (LTGC) engines can provide high efficiencies with very low NOx and soot emissions, but rapid control of the combustion timing remains a challenge. Partial Fuel Stratification (PFS) was demonstrated to be an effective approach to control combustion in LTGC engines. PFS is produced by a double-direct injection (DI) strategy with most of the fuel injected early in the cycle and the remainder of the fuel supplied by a second injection at a variable time during the compression stroke to vary the amount of stratification. Adjusting the stratification changes the combustion phasing, and this can be done on cycle-to-cycle basis by adjusting the injection timing. In this paper, the ability of PFS to control the combustion during wide engine load sweeps is assessed for regular gasoline and gasoline doped with 2-ethylhexyl nitrate (EHN). For PFS, the load control range is limited by combustion instability and poor combustion efficiency at low loads.

Methanol emerges as a compelling renewable fuel for decarbonizing engine applications due to a mature industry with high production capacity, existing distribution infrastructure, low carbon intensity and favorable cost. Methanol’s high flame speed and high autoignition resistance render it particularly well-suited for spark-ignition (SI) engines. Previous research showed a distinct phenomenon, known deflagration-based knock in methanol combustion, whereby knocking combustion was observed albeit without end-gas autoignition. This work studies the implications of deflagration-based knock on noise emissions by investigating the knock intensity and combustion noise at knock-limited operation of methanol in a single-cylinder direct-injection SI engine operated at both stoichiometric and lean (λ = 2.0) conditions. Results are compared against observations from a premium-grade gasoline.

This work represents an advanced engineering research project partially funded by the U.S. Department of Energy (DOE). Ford Motor Company, FEV North America, and Oak Ridge National Laboratory collaborated to develop a next generation boosted spark ignited engine concept. The project goals, specified by the DOE, were 23% improved fuel economy and 15% reduced weight relative to a 2015 or newer light-duty vehicle. The fuel economy goal was achieved by designing an engine incorporating high geometric compression ratio, high dilution tolerance, low pumping work, and low friction. The increased tendency for knock with high compression ratio was addressed using early intake valve closing (EIVC), cooled exhaust gas recirculation (EGR), an active pre-chamber ignition system, and careful management of the fresh charge temperature.

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. In the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied.

In a recent time, which new vehicle lines comes with a huge number of sensors, control units, embedded technologies, and the complexity of these systems (electronics, electrical and electromechanical parts) increases in an exponential way. Considering these events, the expressive generated data amount grows in the same pace, so, consume, transform, and analyze all these data to better understand the modern customer, their needs and how they use the car features becomes necessary. Through that scenario, connected vehicles developed by Ford Motor Company has been generating opportunities to feature’s improvement and cost reduction based on data analysis. This growing quantity of data might be used to optimize feature systems and help engineering teams to understand how the features have been used and enhance the systems engineering design for new or existing features.

The rise of greenhouse gas emissions has reached historic levels, with 37 billion tons of CO2 released into the atmosphere in 2018 alone. In the European Union, 32% of these emissions come from transportation, with 73.3% of that percentage coming from vehicles. To address this problem, solutions such as cleaner fuels and more efficient engines are necessary. Artificial Intelligence can also play a crucial role in climate analysis and verification to move towards a more sustainable future. By utilizing connected vehicle data, automakers can analyze real-time vehicle performance data to identify opportunities for improvement and reduce carbon emissions. This approach benefits the environment, improves vehicle quality, and reduces engineering work time, making it a win-win solution. Connected vehicle data offers a wealth of information on vehicle performance, such as fuel consumption and carbon emissions.

Molecular decomposition is a key chemical process in combustion systems. Particularly, the spatio-temporal information related to a fuel’s molecular breakdown is of high-importance regarding the development of combustion models and more specifically about chemical kinetic mechanisms. Most experiments rely on a variety of ultraviolet or infrared techniques to monitor the fuel breakdown process in 0-D type experiments such as those performed in shock-tubes or rapid compression machines. While the information provided by these experiments is necessary to develop and adjust kinetic mechanisms, they fail to provide the necessary data for applied combustion models to be predictive regarding the fuel’s molecular breakdown. In this work, we investigated the molecular decomposition of a fuel by applying high-speed planar laser Rayleigh scattering (PLRS).

Knock in spark-ignition (SI) engines has been a subject of many research efforts and its relationship with high efficiency operating conditions keeps it a contemporary issue as engine technologies push classical limits. Despite this long history of research, literature is lacking coherent and generalized descriptions of how knock is affected by changes in the full cylinder temperature field, residence time (engine speed), and air/fuel ratio. In this work, two dimensionless numbers are applied to fully 3D SI conditions. First, the characteristic time of autoignition (ignition delay) is compared against the characteristic time of end-gas deflagration, which was used to predict knocking propensity. Second, the temperature gradient of the end-gas is compared against a critical detonation-based temperature gradient, which predicts the knock intensity.

The autoignition chemistry of fuels depends on the pressure, temperature, and time history that the fuel-air mixture experiences during the compression stroke. While piezoelectric pressure transducers offer excellent means of pressure measurement, temperature measurements are not commonly available and must be estimated. Even if the pressure and temperature at the intake and exhaust ports are measured, the residual gas fraction (RGF) within the combustion chamber requires estimation and greatly impacts the temperature of the fresh charge at intake valve closing. This work replaced the standard D1 Detonation Pickup of a CFR engine with a rapid sampling valve to allow for in-cylinder gas sampling at defined crank-angle times during the compression stroke. The extracted cylinder contents were captured in an emissions sample bag and its composition was subsequently analyzed in an AVL i60 emissions bench.

In the present work, five surrogate components (n-Hexadecane, n-Tetradecane, Heptamethylnonane, Decalin, 1-Methylnaphthalene) are proposed to represent liquid phase of diesel fuel, and another different five surrogate components (n-Decane, n-Heptane, iso-Octane, MCH (methylcyclohexane), Toluene) are proposed to represent vapor phase of diesel fuel. For the vapor phase, a 5-component surrogate chemical kinetic mechanism has been developed and validated. In the mechanism, a recently updated H2/O2/CO/C1 detailed sub-mechanism is adopted for accurately predicting the laminar flame speeds over a wide range of operating conditions, also a recently updated C2-C3 detailed sub-mechanism is used due to its potential benefit on accurate flame propagation simulation. For each of the five diesel vapor surrogate components, a skeletal sub-mechanism, which determines the simulation of ignition delay times, is constructed for species C4-Cn.