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The EcoCAR Mobility Challenge (EMC) is the latest edition of the Advanced Vehicle Technology Competition (AVTC) series sponsored by the US Department of Energy. This competition challenges 11 North American universities to redesign a stock 2019 Chevrolet Blazer into an energy-efficient, SAE level 2-autonomous mild hybrid electric vehicle (mHEV) for use in the Mobility as a Service (MaaS) market. The Mississippi State University (MSU) team designed a P4 electric powertrain with an 85kW (113.99 HP) permanent magnet synchronous machine (PMSM) powered by a custom 5.4 kWh lithium-ion energy storage system. To maximize energy efficiency, Model Based Design concepts were leveraged to optimize the overall gear ratio for the P4 system. To accommodate this optimized ratio in the stock vehicle, a custom offset gearbox was designed that links the PMSM to the rear drive module.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Dimethyl ether (DME) represents a promising fuel for heavy-duty engines thanks to its high cetane number, volatility, absence of aromatics, reduced tank-to-wheel CO2 emissions compared to Diesel fuel and the possibility to be produced from renewable energy sources. However, optimization of compression-ignition engines fueled with DME requires suitable computational tools to design dedicated injection and combustion systems: reduced injection pressures and increased nozzle diameters are expected compared to conventional Diesel engines, which influences both the air-fuel mixing and the combustion process. This work intends to evaluate the validity of two different combustion models for the prediction of performance and pollutant emissions in compression-ignition engines operating with DME. The first one is the Representative Interactive Flamelet while the second is the Approximated Diffusive Flamelet.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

This work has the objective to present the extension of a novel quasi-dimensional model, developed to simulate the combustion process in diesel Compression Ignition (CI) engines, to describe this process when Dimethyl ether (DME) is used as fuel. DME is a promising fuel in heavy-duty CI engines application thanks to its high Cetane Number (CN), volatility, high reactivity, almost smokeless combustion, lower CO2 emission and the possibility to be produced with renewable energy sources. In this paper, a brief description of the thermodynamic model will be presented, with particular attention to the implementation of the Tabulated Kinetic Ignition (TKI) model, and how the various models interact to simulate the combustion process. The model has been validated against experimental data derived from constant-volume DME combustion, in this case the most important parameters analyzed and compared were the Ignition Delay (ID) and Flame Lift Off Length (FLOL).

The purpose of the ELEVATE (European Low Emission V4 Automotive Two-stroke Engine) industrial research project is to develop a small, compact, light weight, high torque and highly efficient clean gasoline 2-stroke engine of 120 kW which could industrially replace the relatively big existing automotive spark ignition or diesel 4-stroke engine used in the top of the mid size or in the large size vehicles, including the minivan vehicles used for multi people and family transportation. This new gasoline direct injection engine concept is based on the combined implementation on a 4-stroke bottom end of several 2-stroke engine innovative technologies such as the IAPAC compressed air assisted direct fuel injection, the CAI (Controlled Auto-Ignition) combustion process, the D2SC (Dual Delivery Screw SuperCharger) for both low pressure engine scavenging and higher pressure IAPAC air assisted DI and the ETV (Exhaust charge Trapping Valve).

Turbocharging is playing today a fundamental role not only to improve automotive engine performance, but also to reduce fuel consumption and exhaust emissions for both Spark Ignition and Diesel engines. Dedicated experimental investigations on turbochargers are therefore necessary to assess a better understanding of its performance. The availability of experimental information on turbocharger steady flow performance is an essential requirement to optimize the engine-turbocharger matching, which is usually achieved by means of simulation models. This aspect is even more important when referred to the turbine efficiency, since its swallowing capacity can be accurately evaluated through the measurement of mass flow rate, inlet temperature and pressure ratio across the machine.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

In the current work, a series-hybrid vehicle has been constructed that utilizes a dual-fuel, Reactivity Controlled Compression Ignition (RCCI) engine. The vehicle is a 2009 Saturn Vue chassis and a 1.9L turbo-diesel engine converted to operate with low temperature RCCI combustion. The engine is coupled to a 90 kW AC motor, acting as an electrical generator to charge a 14.1 kW-hr lithium-ion traction battery pack, which powers the rear wheels by a 75 kW drive motor. Full vehicle testing was conducted on chassis dynamometers at the Vehicle Emissions Research Laboratory at Ford Motor Company and at the Vehicle Research Laboratory at Oak Ridge National Laboratory. For this work, the US Environmental Protection Agency Highway Fuel Economy Test was performed using commercially available gasoline and ultra-low sulfur diesel. Fuel economy and emissions data were recorded over the specified test cycle and calculated based on the fuel properties and the high-voltage battery energy usage.

While Low Temperature Combustion (LTC) strategies such as Reactivity Controlled Compression Ignition (RCCI) exhibit high thermal efficiency and produce low NOx and soot emissions, low load operation is still a significant challenge due to high unburnt hydrocarbon (UHC) and carbon monoxide (CO) emissions, which occur as a result of poor combustion efficiencies at these operating points. Furthermore, the exhaust gas temperatures are insufficient to light-off the Diesel Oxidation Catalyst (DOC), thereby resulting in poor UHC and CO conversion efficiencies by the aftertreatment system. To achieve exhaust gas temperature values sufficient for DOC light-off, combustion can be appropriately phased by changing the ratio of gasoline to diesel in the cylinder, or by burning additional fuel injected during the expansion stroke through post-injection.

Knock in a Rotax-914 engine was modeled and investigated using an improved version of the KIVA-3V code with a G-equation combustion model, together with a reduced chemical kinetics model. The ERC-PRF mechanism with 47 species and 132 reactions [1] was adopted to model the end gas auto-ignition in front of the flame front. The model was validated by a Caterpillar SI engine and a Rotax-914 engine in different operating conditions. The simulation results agree well with available experimental results. A new engineering quantified knock criterion based on chemical mechanism was then proposed. Hydroperoxyl radical (HO2) shows obvious accumulation before auto-ignition and a sudden decrease after auto-ignition. These properties are considered to be a good capability for HO2 to investigate engine knock problems.

The accurate prediction of pollutant emissions generated by IC engines is a key aspect to guarantee the respect of the emission regulation legislation. This paper describes the approach followed by the authors to achieve a strict numerical coupling of two different 1D modeling tools in a co-simulation environment, aiming at a reliable calculation of engine-out and tailpipe emissions. The main idea is to allow an accurate 1D simulation of the unsteady flows and wave motion inside the intake and exhaust systems, without resorting to an over-simplified geometrical discretization, and to rely on advanced thermodynamic combustion models and kinetic sub-models for the calculation of cylinder-out emissions. A specific fluid dynamic approach is then used to track the chemical composition along the exhaust duct-system, in order to evaluate the conversion efficiency of after-treatment devices, such as TWC, GPF, DPF, DOC, SCR and so on.

Detailed and fast combustion models are necessary to support design of Diesel engines with low emission and fuel consumption. Over the years, the importance of turbulence chemistry interaction to correctly describe the diffusion flame structure was demonstrated by a detailed assessment with optical data from constant-volume vessel experiments. The main objective of this work is to carry out an extensive validation of two different combustion models which are suitable for the simulation of Diesel engine combustion. The first one is the Representative Interactive Flamelet model (RIF) employing direct chemistry integration. A single flamelet formulation is generally used to reduce the computational time but this aspect limits the capability to reproduce the flame stabilization process. To overcome such limitation, a second model called tabulated flamelet progress variable (TFPV) is tested in this work.

Gasoline, direct injection engines represent one of the most widely adopted powertrain for passenger cars. However, further development efforts are necessary to meet the future fuel consumption and emission standards imposing an efficiency increase and a reduction of particulate matter emissions. Within this context, computational fluid dynamics is nowadays a consolidated tool to support engine design; this work is focused on the development of a set of CFD models for the prediction of combustion in modern GDI engines. The one-equation Weller model coupled with a zero-dimensional approach to handle initial flame kernel growth was applied to predict flame propagation. To account for mixture fraction fluctuations which might lead to the presence of soot precursor species, burned gas chemical composition is computed using tabulated kinetics with a presumed probability density function.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

In this work, the possibility to perform a cold-flow simulation as a way to improve the accuracy of the starting conditions for a combustion simulation is examined. Specifically, a dual-fuel marine engine running on methanol/diesel and natural gas/diesel fueling conditions is investigated. Dual-fuel engines can provide a short-term solution to cope with the more stringent emission legislations in the maritime sector. Both natural gas and methanol appear to be interesting alternative fuels that can be used as main fuel in these dual-fuel engines. Nevertheless, it is observed that combustion problems occur at part load using these alternative fuels. Therefore, different methods to increase the combustion efficiency at part load are investigated. Numerical simulations prove to be very suitable hereto, as they are an efficient way to study the effect of different parameters on the combustion characteristics.

Multiple injection strategies are commonly used in conventional Diesel engines due to the flexibility for optimizing heat-release timing with a consequent improvement in fuel economy and engine-out emissions. This is also desirable in low-temperature combustion (LTC) engines since it offers the potential to reduce unburned hydrocarbon and CO emissions. To better utilize these benefits and find optimal calibrations of split injection strategies, it is imperative that the fundamental processes of multiple injection combustion are understood and computational fluid dynamics models accurately describe the flow dynamics and combustion characteristics between different injection events. To this end, this work is dedicated to the identification of suitable methodologies to predict the multiple injection combustion process.

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

Turbulent Jet Ignition (TJI) represents one of the most effective solution to improve engine efficiency and to reduce fuel consumption and pollutants emission. Even if active prechambers allow a precise control of the air-fuel ratio close to the spark plug and the ignition of ultra-lean mixtures in the main chamber, passive prechambers represent a more attractive solution especially for passenger cars thanks to their simpler and cheaper configuration, which is easier to integrate into existing engines. The main challenge of passive prechambers is to find a geometry that allows to use TJI in the whole engine map, especially in the low load/speed region, without the use of a second sparkplug in the main chamber. To this end, this works reports a CFD study coupled with an experimental investigation to overcome this limitation.