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Prior work in the literature have shown that pre-chamber spark plug technologies can provide remarkable improvements in engine performance. In this work, three passively fueled pre-chamber spark plugs with different pre-chamber geometries were investigated using in-cylinder high-speed imaging of spectral emission in the visible wavelength region in a single-cylinder direct-injection spark-ignition gasoline engine. The effects of the pre-chamber spark plugs on flame development were analyzed by comparing the flame progress between the pre-chamber spark plugs and with the results from a conventional spark plug. The engine was operated at fixed conditions (relevant to federal test procedures) with a constant speed of 1500 revolutions per minute with a coolant temperature of 90 oC and stoichiometric fuel-to-air ratio. The in-cylinder images were captured with a color high-speed camera through an optical insert in the piston crown.

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.

Strain-rate sensitivity has been neglected in the simulation of the traditional stamping process because the strain rate typically does not significantly impact the forming behavior of sheet metals in such a quasi-static process, and traditional crank or link mechanical presses lack the flexibility of slide motion. However, the recent application of servo drive presses in stamping manifests improvement in formability and reduction of springback, besides increased productivity and energy savings. An accurate simulation of servo stamping entails constitutive models with strain-rate sensitivity. This study evaluated a few strain rate-sensitive models including the power-law model, the linear power-law model, the Johnson-Cook model, and the Cowper-Symonds model through the exercise of fitting these models to the experimental data of a deep draw quality (DDQ) steel.

With ongoing concerns about the elevated levels of ambient air pollution in urban areas and the contribution from heavy-duty diesel vehicles, hybrid electric vehicles are considered as a potential solution as they are perceived to be more fuel efficient and less polluting than their conventional engine counterparts. However, recent studies have shown that real-world emissions may be substantially higher than those measured in the laboratory, mainly due to operating conditions that are not fully accounted for in dynamometer test cycles. At the U.S. EPA National Fuel and Vehicle Emissions Laboratory (NVFEL) the in-use criteria emissions and energy efficiency of heavy-duty class 8 vehicles (up to 36280 kg) can be evaluated under controlled conditions in the heavy-duty chassis dynamometer test.

Connected vehicles (CVs) have situational awareness that can be exploited for control and optimization of the powertrain system. While extensive studies have been carried out for energy efficiency improvement of CVs via eco-driving and planning, the implication of such technologies on the thermal responses of CVs (including those of the engine and aftertreatment systems) has not been fully investigated. One of the key challenges in leveraging connectivity for optimization-based thermal management of CVs is the relatively slow thermal dynamics, which necessitate the use of a long prediction horizon to achieve the best performance. Long-term prediction of the CV speed, unlike the short-range prediction based on vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communications-based information, is difficult and error-prone.

This work investigates the potential improvements in vehicle fuel economy possible by optimizing gear shift strategies to leverage a novel boosting device, an electrically assisted variable speed supercharger (EAVS), also referred to as a power split supercharger (PSS). Realistic gear shift strategies, resembling those commercially available, have been implemented to control upshift and downshift points based on torque request and engine speed. Using a baseline strategy from a turbocharged application of a MY2015 Ford Escape, a vehicle gas mileage of 34.4 mpg was achieved for the FTP75 drive cycle before considering the best efficiency regions of the supercharged engine.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

Large-eddy simulations (LES) of a motoring single-cylinder engine with transparent combustion chamber (TCC-II) are carried out using a commercially available computer code, CONVERGE. Numerical predictions are compared with high-speed particle image velocimetry (PIV) measurements. Predictions of two spatial discretization schemes, namely, numerically stabilized central difference scheme (CDS) and fully upwind scheme are compared. Four different subgrid scale (SGS) models; a non-eddy viscosity dynamic structure turbulence (DST) model of Pomraning and Rutland, one-equation eddy-viscosity (1-Eqn) model of Menon et al., a zeroequation eddy-viscosity model of Vreman, and the zeroequation standard Smagorinsky model are employed on two different grid configurations. Additionally, simulations are also performed by deactivating the LES SGS models. It is found that the predictions when using the numerically stabilized CDS are significantly better than using the fully upwind scheme.

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

Previous work done at the University of Michigan shows the capability of the vacuum-insulated catalytic converter (VICC) to retain heat during soak and the resulting benefits in reducing cold start emissions. This paper provides an improved version of the design which overcomes some of the shortcomings of the previous model and further improves the applicability and benefits of VICC. Also, newer materials have been evaluated and their effects on heat retention and emissions have studied using the 1-D after treatment model. Cold start emissions constitute around 60% to 80% of all the hydrocarbon and CO emissions in present day vehicles. The time taken to achieve the catalyst light-off temperature in a three-way catalytic converter significantly affects the emissions and fuel efficiency. The current work aims at developing a method to retain heat in catalytic converter, thus avoiding the need for light-off and reducing cold start emissions effectively.

Numerous studies have demonstrated the benefits of ethanol in increasing the thermal efficiency of gasoline-fueled spark ignition engines via the higher enthalpy of vaporization and higher knock resistance of ethanol compared with gasoline. This study expands on previous work by considering a split fuel injection strategy with a boosted direct injection spark ignition engine fueled with E0 (100% by volume reference grade gasoline; with research octane number = 91 and motor octane number = 83), E100 (100% by volume anhydrous ethanol), and various splash-blends of the two fuels. Experiments were performed using a production 3-cylinder Ford Ecoboost engine where two cylinders were de-activated to create a single-cylinder engine with a displacement of 0.33 L. The engine was operated over a range of loads with boosted intake manifold absolute pressure (MAP) from 1 bar to 1.5 bar.

Pre-chambers are a means to enable lean burn combustion strategies which can increase the thermal efficiency of gasoline spark ignition internal combustion engines. A new engine concept is evaluated in this work using computational simulations of non-reacting flow. The objective of the computational study was to evaluate the feasibility of several engine design configurations combined with fuel injection strategies to create local fuel/air mixtures in the pre-chambers above the ignition and flammability limits, while maintaining lean conditions in the main combustion chamber. The current work used computational fluid dynamics to develop a novel combustion chamber geometry where the flow was evaluated through a series of six design iterations to create ignitable mixtures (based on fuel-to-air equivalence ratio, ϕ) using fuel injection profiles and flow control via the piston, cylinder head, and pre-chamber geometry.

This paper addresses scheduling of quantized power levels (including part load operation and startup/shutdown periods) for a propane powered solid oxide fuel cell (SOFC) hybridized with a lithium-ion battery for a tracked mobile robot. The military requires silent operation and long duration missions, which cannot be met by batteries alone due to low energy density or with combustion engines due to noise. To meet this need we consider an SOFC operated at a few discrete power levels where maximum system efficiency can be achieved. The fuel efficiency decreases during transients and resulting thermal gradients lead to stress and degradation of the stack; therefore switching power levels should be minimized. Excess generated energy is used to charge the battery, but when it’s fully charged the SOFC should be turned off to conserve fuel.

Design of military vehicle needs to meet often conflicting requirements such as high mobility, excellent fuel efficiency and survivability, with acceptable cost. In order to reduce the development cost, time and associated risk, as many of the design questions as possible need to be addressed with advanced simulation tools. This paper describes a methodology to design a fuel efficient powerpack unit for a series hybrid electric military vehicle, with emphasis on the e-machine design. The proposed methodology builds on previously published Finite element based analysis to capture basic design features of the generator with three variables, and couples it with a model reduction technique to rapidly re-design the generator with desired fidelity. The generator is mated to an off the shelf engine to form a powerpack, which is subsequently evaluated over a representative military drive cycles.

Advanced engine combustion strategies, such as HCCI and SACI, allow engines to achieve high levels of thermal efficiency with low levels of engine-out NOx emissions. To maximize gains in fuel efficiency, HCCI combustion is often run at lean operating conditions. However, lean engine operation prevents the conventional TWC after-treatment system from reaching legislated tailpipe emissions due to oxygen saturation. One potential solution for handling this challenge without the addition of costly NOx traps or on-board systems for urea injection is the passive TWC-SCR concept. This concept includes the integration of an SCR catalyst downstream of a TWC and the use of periods of rich or stoichiometric operation to generate NH3 over the TWC to be stored on the SCR catalyst until it is needed for NOx reduction during subsequent lean operation.

Injecting liquid water into a fuel/air charge is a means to reduce NOx emissions. Such strategies are particularly important to hydrogen internal combustion engines, as engine performance (e.g., maximum load) can be limited by regulatory limits on NOx. Experiments were conducted in this study to quantify the effects of direct injection of water into the combustion chamber of a port-fueled, hydrogen IC engine. The effects of DI water injection on NOx emissions, load, and engine efficiency were determined for a broad range of water injection timing. The amount of water injected was varied, and the results were compared with baseline data where no water injection was used. Water injection was a very effective means to reduce NOx emissions. Direct injection of water into the cylinder reduced NOx emissions by 95% with an 8% fuel consumption penalty, and NOx emissions were reduced by 85% without any fuel consumption penalty.

This paper is on the development process of a hydraulic hybrid passenger vehicle. A subcompact passenger vehicle is chosen for modification into a series hydraulic hybrid with the aim of achieving a fuel economy of 100 MPG (2.35 L/100km) on the Urban Dynamometer Driving Schedule (UDDS). This work develops a methodology for simultaneously designing a powertrain and power management strategy of a series hydraulic hybrid. The design process was initiated by developing a system level model validated using engine and hydraulic pump/motor testing by the US EPA at the National Vehicle and Fuel Efficiency Laboratory (NVFEL). Parametric studies were performed in order to determine the size of the pump/motors and accumulators. Several candidate engines were tested and the system models were used to determine which one could provide the best fuel economy while meeting performance constraints.

This simulation study explores the potential synergy between the HCCI engine system and three hybrid electric vehicle (HEV) configurations, and proposes the supervisory control strategy that maximizes the benefits of combining these two technologies. HCCI operation significantly improves fuel efficiency at part load, while hybridization aims to reduce low load/low speed operation. Therefore, a key question arises: are the effects of these two technologies additive or overlapping? The HEV configurations include two parallel hybrids with varying degrees of electrification, e.g. with a 5kW integrated starter/motor (“Mild”) and with a 10 kW electric machine (“Medium”), and a power-split hybrid. The engine is a dual-mode, SI-HCCI system and the engine map reflects the impact of HCCI on brake specific fuel consumption.

At the forefront of intelligent vehicle technologies are vehicle-to-vehicle communication (V2V) and vehicle-infrastructure integration (VII). Their capabilities can be added to currently-available systems, such as adaptive cruise control (ACC), to drastically decrease the number and severity of collisions, to ease traffic flow, and to consequently improve fuel efficiency and environmental friendliness. There has been extensive government, industry, and academic involvement in developing these technologies. This paper explores the capabilities and challenges of vehicle-based technology and examines ways that policymakers can foster implementation at the federal, state, and local levels.