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The field of automotive engineering has devoted much research to reduce fuel consumption to attain sustainable energy usage. Friction reductions in powertrain components can improve engine fuel economy. Quantitative accounting of friction is complex because it is affected by many physical aspects such as oil viscosity, temperature, surface roughness and component rotation speed. The purpose of this paper is two-fold: first, to develop a useful tool for evaluating the friction in engine and accessories based on test data; second, to exercise the tool to evaluate the fuel economy gain in a drive cycle for several friction reduction technologies.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

Gas-pressurized space suits are highly resistive to astronaut movement, and this resistance has been previously explained by volume and/or structural effects. This study proposed that an additional effect, pressure effects due to compressing/expanding the internal gas during joint articulation, also inhibits mobility. EMU elbow torque components were quantified through hypobaric testing. Structural effects dominated at low joint angles, and volume effects were found to be the primary torque component at higher angles. Pressure effects were found to be significant only at high joint angles (increased flexion), contributing up to 8.8% of the total torque. These effects are predicted to increase for larger, multi-axis joints. An active regulator system was developed to mitigate pressure effects, and was found to be capable of mitigating repeated pressure spikes caused by volume changes.

A new monitoring system predicts the progression of welding temperature fields during resistance spot welding. The system captures welding voltages and currents to predict contact diameters and simulate temperature fields. The system accurately predicts fusion lines and heat-affected zones. Accuracy holds even for electrode tips used for a few thousand welds of zinc coated steels.

The transportation sector in the United States is a major contributor to global energy consumption and carbon dioxide emission. To assess the future potentials of different technologies in addressing these two issues, we used a family of simulation programs to predict fuel consumption for passenger cars in 2020. The selected technology combinations that have good market potential and could be in mass production include: advanced gasoline and diesel internal combustion engine vehicles with automatically-shifting clutched transmissions, gasoline, diesel, and compressed natural gas hybrid electric vehicles with continuously variable transmissions, direct hydrogen, gasoline and methanol reformer fuel cell hybrid electric vehicles with direct ratio drive, and battery electric vehicle with direct ratio drive.

To obtain realistic noise characteristics from CAA studies of subsonic fans, it is important to prescribe properly constructed turbulent inflow statistics. This is frequently omitted; instead it is assumed that the stochastic characteristics of turbulence, absent at the initial stage, progressively develops as the rotor inflicts the flow field over time and hence that the sound generating mechanism governed by surface pressure fluctuations are asymptotically accounted for. That assumption violates the actual interplay taking place between an ingested flow field and the surface pressure fluctuations exerted by the blades producing noise. The aim of the present study is to examine the coupling effect between synthetically ingested turbulence to sound produced from a subsonic ducted fan. The steady state inflow parameters are mapped from a precursor RANS simulation onto the inflow boundaries of a reduced domain to limit the computational cost.

The effect of blockage due to the presence of the wind tunnel walls has been known since the early days of wind tunnel testing. Today there are several blockage correction methods available for correcting the measured aerodynamic drag. Due to the shape of the test object, test conditions and wind tunnel dimensions the effect on the flow may be different for two cab variants. This will result in a difference in the drag delta between so-called open-road conditions and the wind tunnel. This makes it more difficult to evaluate the performance of two different test objects when they are both tested in a wind tunnel and simulated in CFD. A numerical study where two different cab shapes were compared in both open road condition, and in a digital wind tunnel environment was performed.

A Multi-Objective Optimization (MOO) problem concerning the thermal control problem of Multifunctional Structures (MFSs) is here addressed. In particular the use of Multi-Objective algorithms from an optimization tool and Self-Organizing Maps (SOM) is proposed for the identification of the optimal topological distribution of the heating components for a multifunctional test panel, the Advanced Bread Board (ABB). MFSs are components that conduct many functions within a single piece of hardware, shading the clearly defined boundaries that identify traditional subsystems. Generally speaking, MFSs have already proved to be a disrupting technology, especially in aeronautics and space application fields. The case study exploited in this paper refers to a demonstrator breadboard called ABB. ABB belongs to a particular subset of an extensive family of MFS, that is, of thermo-structural panels with distributed electronics and a health monitoring network.

This paper describes the use of a modified quasi-dimensional spark-ignition engine simulation code to predict the extent of cycle-to-cycle variations in combustion. The modifications primarily relate to the combustion model and include the following: 1. A flame kernel model was developed and implemented to avoid choosing the initial flame size and temperature arbitrarily. 2. Instead of the usual assumption of the flame being spherical, ellipsoidal flame shapes are permitted in the model when the gas velocity in the vicinity of the spark plug during kernel development is high. Changes in flame shape influence the flame front area and the interaction of the enflamed volume with the combustion chamber walls. 3. The flame center shifts due to convection by the gas flow in the cylinder. This influences the flame front area through the interaction between the enflamed volume and the combustion chamber walls. 4. Turbulence intensity is not uniform in cylinder, and varies cycle-to-cycle.

This paper describes a three component strain gage balance designed to measure aerodynamic forces exerted on small automobile models when subjected to turbulence in an experimental wind tunnel. The instrument is described and the details of obtaining values with it are fully explained. Although tests were conducted on these models at quarter-scale Reynolds number, results agree closely with similar tests on larger models. The balance makes practical some unusual preliminary investigations before developing full-scale prototypes.

A linearized lumped parameter heat balance model was developed and is discussed for the general case of resistance welding to see the effects of each parameter on the lobe shape. The parameters include material properties, geometry of electrodes and work piece, weld time and current, and electrical and thermal contact characteristics. These are then related to heat dissipation in the electrodes and the work piece. The results indicate that the ratio of thermal conductivity and heat capacity to electrical resistivity is a characteristic number which is representative of the ease of spot weldability of a given material. The increases in thermal conductivity and heat capacity of the sheet metal increase the lobe width while increases in electrical resistivity decrease the lobe width. Inconsistencies in the weldability of thin sheets and the wider lobe width at long welding times can both be explained by the heat dissipation characteristics.

A one-dimensional model for crevice HC post-flame oxidation is used to calculate and understand the effect of operating parameters and fuel type (propane and isooctane) on the extent of crevice hydrocarbon and the product distribution in the post flame environment. The calculations show that the main parameters controlling oxidation are: bulk burned gas temperatures, wall temperatures, turbulent diffusivity, and fuel oxidation rates. Calculated extents of oxidation agree well with experimental values, and the sensitivities to operating conditions (wall temperatures, equivalence ratio, fuel type) are reasonably well captured. Whereas the bulk gas temperatures largely determine the extent of oxidation, the hydrocarbon product distribution is not very much affected by the burned gas temperatures, but mostly by diffusion rates. Uncertainties in both turbulent diffusion rates as well as in mechanisms are an important factor limiting the predictive capabilities of the model.

Cremer impedance, first proposed by Cremer (Acustica 3, 1953) and then improved by Tester (JSV 28, 1973), refers to the locally reacting boundary condition that can maximize the attenuation of a certain acoustic mode in a uniform waveguide. One limitation in Tester’s work is that it simplified the analysis on the effect of flow by only considering high frequencies or the ‘well cut-on’ modes. This approximation is reasonable for large duct applications, e.g., aero-engines, but not for many other cases of interest, with the vehicle intake and exhaust system included. A recent modification done by Kabral et al. (Acta Acustica united with Acustica 102, 2016) has removed this limitation and investigated the ‘exact’ solution of Cremer impedance for circular waveguides, which reveals an appreciable difference between the exact and classic solution in the low frequency range. Consequently, the exact solution can lead to a much higher low-frequency attenuation level.

An analysis method for characterizing fuel behavior during spark-ignition engine starting has been developed and applied to several sets of start-up data. The data sets were acquired from modern production vehicles during room temperature engine start-up. Two different engines, two control schemes, and two engine temperatures (cold and hot) were investigated. A cycle-by-cycle mass balance for the fuel was used to compare the amount of fuel injected with the amount burned or exhausted as unburned hydrocarbons. The difference was measured as “fuel unaccounted for”. The calculation for the amount of fuel burned used an energy release analysis of the cylinder pressure data. The results include an overview of starting behavior and a fuel accounting for each data set Overall, starting occurred quickly with combustion quality, manifold pressure, and engine speed beginning to stabilize by the seventh cycle, on average.

As vehicles become electrified and more intelligent in terms of sensing, actuation and processing; a number of interesting possibilities arise in controlling vehicle dynamics and driving behavior. Over-actuation with in- wheel motors, all wheel steering and active camber is one such possibility, which facilitate the control strategies that push boundaries in energy consumption and safety. Optimal control can be used to investigate the best combinations of control inputs to an over-actuated system. This paper shows how an optimal control problem can be formulated and solved for an over-actuated vehicle case, and highlights the translation of this optimal solution to a real-world scenario, enabling intelligent means to improve vehicle efficiency. This paper gives an insight into Dynamic Programming (DP) as an offline optimal control method that guarantees the global optimum.

The NOx emission and knock characteristics of a PFI engine operating on ethanol/gasoline mixtures were assessed at 1500 and 2000 rpm with λ =1 under Wide-Open-Throttle condition. There was no significant charge cooling due to fuel evaporation. The decrease in NOx emission and exhaust temperature could be explained by the change in adiabatic flame temperature of the mixture. The fuel knock resistance improved significantly with the gasohol so that ignition could be timed at a value much closer or at MBT timing. Changing from 0% to 100% ethanol in the fuel, this combustion phasing improvement led to a 20% increase in NIMEP and 8 percentage points in fuel conversion efficiency at 1500 rpm. At 2000 rpm, where knocking was less severe, the improvement was about half (10% increase in NIMEP and 4 percentage points in fuel conversion efficiency).

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.