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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.

Dual-fuel engines employ precisely metered amounts of a high reactivity fuel (HRF) such as diesel at high injection pressures to burn a low reactivity fuel (LRF) such as natural gas, which is typically fumigated into the intake manifold. Dual fuel engines have demonstrated the ability to achieve extremely low engine-out oxides of nitrogen (NOx) emissions compared to conventional diesel combustion at the expense of unburned hydrocarbon (HC) and carbon monoxide (CO) emissions. At low engine loads, due to low in-cylinder temperatures, oxidation of HC and CO is very challenging. This results in both compromised combustion and fuel conversion efficiencies.

Selecting the optimal gear ratios to determine the best overall lap time for a racing vehicle is the goal of the simulation presented in this paper. Given a discrete set of individual gear ratio and final drive ratio options, the simulation chooses the set of gears and final drive that produce the minimum overall lap time. For example, one vehicle studied in this paper, an F2000 formula car, has 32 ratio choices for four forward gears and a final drive that has three different options. The simulation will iterate through the gear options to find the optimal gear selection for the best lap performance, accounting for various factors that could cause improper selection of gears. The simulation accounts for aerodynamic factors, gear shift time, rolling resistance and tire scrub. All values have been estimated from logged vehicle data, but experimental data can be easily used to help improve the vehicle model.

The Alabama Technology Network, Inc. (ATN) provides technical assistance, management assistance and training that complements workforce and economic development. The ATN center at the University of Alabama in Huntsville (UAH) has focused on lean manufacturing. This paper summarizes the principles of “lean”, presents three phases to implementing lean, and illustrates its application in a training simulation of a setup/changeover reduction. Finally, success stories show how UAH is helping many small and medium size manufacturers improve rapidly using lean techniques.

The natural modes of the ring gear structure commonly used in automotive transmissions are predicted using the finite element approach, and the sensitivities of these modes to boundary conditions between the housing and ring gear are analyzed. The specific boundary conditions of interest include free-free, simply-supports at equally spaced angular points, and discrete and distributed spring elements. For the free-free boundary condition, clear well-defined modes are observed that can be classified into four fundamental groups corresponding to radial inextensional, extensional, out-of-plane bending and pure torsional. However, when other boundary conditions are applied the mode shapes become more complex. For instance, in the simply-supported case the radial inextensional and torsional modes are seen to appear highly distorted. Also, the natural frequencies of these modes are higher than the free-free ones.

A spectral-based substructuring approach applying linear frequency response functions (FRF) is proposed for improving the accuracy of simulating the dynamics of coupled systems. The method also applies a least square singular value decomposition (SVD) scheme to overcome the inherent computational deficiency in the basic substructuring formulation. The computational problem is caused by the magnification of measurement errors during any one of the matrix inversion calculations required for this method. The primary objective of applying this approach is to examine the possibility of analyzing higher frequency response that is normally not possible using conventional modeling technique such as the direct finite and boundary element, and lumped parameter techniques. In this study, additional concepts are also evaluated to quantify the limitations and range of applicability of the proposed substructuring approach for simulating the vibration response of complex powertrain structures.

A multi-coordinate FRF-based inverse substructuring approach is proposed to partition a vehicle system into two or more substructures, which are coupled at discrete interface points. The joint and free substructure dynamic characteristics are then extracted from the coupled system response spectra. Depending on the actual form of the structural coupling terms, three forms of the coupling matrix are assumed here. The most general one constitutes the non-diagonal form, and the other two simpler cases are the block-diagonal and purely diagonal representations that can be used to simplify testing process and overcome computational problems. The paper is focused on the investigation of the durability of these three formulations when the input FRFs are noise contaminated. A finite element model of a simplified vehicle system is used as the case study.

A proposed multi-coordinate spectral-based inverse substructuring approach is applied experimentally to examine the vibration transmissibility through chassis mounts. In this formulation, the vehicle system is partitioned into two substructures. One substructure comprises of the chassis and suspension, while the second one is the body structure and other attached components. The approach yields the free substructure dynamic characteristics that are extracted from the measured coupled system response spectra. The resultant free substructure transfer functions are verified by comparison of the re-synthesized results to the actual vehicle system measurements. A real life vehicle setup is utilized to demonstrate the salient features and capabilities of this approach, which includes the ability to compute the main structure-borne paths, dynamic interactions between the chassis and body, and interior noise and vibration response.

Natural luminosity (NL) and chemiluminescence (CL) imaging diagnostics are employed to investigate fuel-property effects on mixing-controlled combustion, using select research fuels-a #2 ultra-low sulfur emissions-certification diesel fuel (CF) and four of the Fuels for Advanced Combustion Engines (FACE) diesel fuels (F1, F2, F6, and F8)-that varied in cetane number (CN), distillation characteristics, and aromatic content. The experiments were performed in a single-cylinder heavy-duty optical compression-ignition (CI) engine at two injection pressures, three dilution levels, and constant start-of-combustion timing. If the experimental results are analyzed only in the context of the FACE fuel design parameters, CN had the largest effect on emissions and efficiency.