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Traditional User/Maintenance Manuals provide useful information when dealing with simple machines. However, when dealing with complex systems of systems and highly miniaturized technologies, like UAVs, or with machines with millions of parts, a commercial aircraft is a case in point, new technologies taking advantage of Augmented Reality can rapidly and effectively support the maintenance operations. This paper presents a User/Maintenance Manual based on Augmented Reality to help the operator in the detection of parts and in the sequence to be followed to assemble/disassemble systems and subsystems. The proposed system includes a handheld device and/or an head mounted display or special goggles, to be used by on-site operators, with software management providing data fusion and overlaying traditional 2D user/maintenance manual information with an augmented reality software and appropriate interface.

The aim of this work is to propose modifications to the managing of the 1st generation Common Rail injectors in order to reduce actuation time towards multiple injection strategies. The current Common Rail injector driven by 1st ECU generation is capable of operating under stable conditions with a minimum dwell between two consecutive injections of 1.8 ms. This limits the possibility in using proper and efficient injection strategies for emission control purposes. A previous numerical study, performed by the electro-fluid-mechanical model built up by Matlab-Simulink environment, highlighted different area where injector may be improved with particular emphasis on electronic driving circuit and components design. Experiments carried out at injector Bosch test-bench showed that a proper control of the solenoid valve allowed reducing drastically the standard deviation during the pilot pulses.

The component response synthesis approach utilizing frequency response function (FRF) has been used to analyze the dynamic interaction of two or more vehicle components coupled at discrete interface points. This method is somewhat suitable for computing higher frequency response because experimental component FRFs can be incorporated into the formulation directly. However its calculations are quite sensitive to measurement errors in the FRFs due to the several matrix inversion steps involved. In the past, researchers have essentially used a combined direct inverse and truncated singular valued decomposition (TSVD) technique to ensure a stable calculation, which is typically applied semi-empirically due to the lack of understanding of the influence of measurement error.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

Electrochemical models of lithium ion batteries are today a standard tool in the automotive industry for activities related to the computer-aided engineering design, analysis, and optimization of energy storage systems for electrified vehicles. One of the challenges in the development or use of such models is the need of detailed information on the cell and electrode geometry or properties of the electrode and electrolyte materials, which are typically unavailable or difficult to retrieve by end-users. This forces engineers to resort to “hand-tuning” of many physical and geometrical parameters, using standard cell-level characterization tests. This paper proposes a method to provide information and data on individual electrode performance that can be used to simplify the calibration process for electrochemical models.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

Plug-In Hybrid Vehicles (PHEVs) represent the middle point between Hybrid Electric Vehicles (HEVs) and Electric Vehicles (EVs), thus combining benefits of the two architectures. PHEVs can achieve very high fuel economy while preserving full functionality of hybrids - long driving range, easy refueling, lower emissions etc. These advantages come at an expense of added complexity in terms of available fuel. The PHEV battery is recharged both though regenerative braking and directly by the grid thus adding extra dimension to the control problem. Along with the minimization of the fuel consumption, the amount of electricity taken from the power grid should be also considered, therefore the electricity generation mix and price become additional parameters that should be included in the cost function.

The need to reduce carbon dioxide emissions from motor vehicles pushes the European Union towards drastic choices on future mobility. Despite this, the engines of the “future” have not yet been defined: the choice of engine type will undoubtedly depend on the type of application (journey length, availability of recharging/refueling facilities), practical availability of alternative fuels, and electricity to recharge the batteries. The electrification of vehicles (passenger and transportation cars) may be unsuitable for several aspects: the gravimetric energy density could be too low if the vehicle has to be lightweight, must achieve a high degree of autonomy, or needs a very short refueling time.

As we continue to create ever-lighter road vehicles, the challenge of balancing weight reduction and structural performance also continues. One of the key parts this occurs on is the hood, where lighter materials (e.g. aluminum) have been used. However, the aerodynamic loads, such as hood lift, are essentially unchanged and are driven by the front fascia and front grille size and styling shape. This paper outlines a combination CFD/FEA prediction method for hood deflection performance at high speeds, by using the surface pressures as boundary conditions for a FEA linear static deflection analysis. Additionally, custom post-processing methods were developed to enhance flow analysis and understanding. This enabled the modification of existing test methods to further improve accuracy to real world conditions. The application of these analytical methods and their correlation with experimental results are discussed in this paper.

The Buckeye Bullet set domestic as well as international speed records for electric vehicles in 2004. The next generation of land speed vehicle from Ohio State called the Buckeye Bullet 2 (henceforth the BB2) will again challenge and hopefully achieve several new speed records. The Buckeye Bullet suspension worked relatively well but was found to not be quite optimal for the vehicle. The purpose of the work outlined here was to develop a new front and rear suspension for the BB2 that would be an improvement over the suspension of the original Bullet. Previous to the start of this work part of the suspension had already been designed in the form of an upright/control arm setup. This paper works on taking the suspension to completion from this point of design. Work done includes developing the final design, determining suspension parameters, building an ADAMS model, and testing the ADAMS model.

The Bellanca Skyrocket II, possessor of five world speed records, is a single engine aircraft with high performance that has been attributed to a laminar flow airfoil and an all composite structure. Utilization of composite materials in the Skyrocket II is unique since this selection was made to increase the aerodynamic efficiency of the aircraft. Flight tests are in progress to measure the overall aircraft drag and the wing section drag for comparison with the predicted performance of the Skyrocket. Initial results show the zero lift drag is indeed low, with CDO = 0.016.

The nonlinear behavior of automotive powertrains is mainly due to the presence of backlash between engaging components. In particular, during tip-in or tip-out maneuvers, backlash allows the generation of impacts that negatively affect the vehicle NVH performance. Due to the faster response of electric motors with respect to conventional internal combustion engines, this problem is even more critical for electric vehicles. In order to employ numerical optimal control methods for backlash compensation, the system states have to be known. In this paper, an electric powertrain is modeled as a two-mass oscillator with lumped backlash. This model estimates the system states when in no-contact mode while a Kalman filter that relies only on commonly available speed measurements is active in the contact phase. The powertrain model is validated using experimental data collected during vehicle testing and the online estimated half-shaft torque is shown.

The elastomeric joints (bushings or mounts) in vehicle structural frames are usually described as uncoupled springs (only with diagonal terms) in large scale system models. The off-diagonal terms of an elastomeric joint have been previously ignored as they are often unknown since their properties cannot be measured in a uniaxial elastomer test system. This paper overcomes this deficiency via a scientific study of a laboratory frame that is designed to maintain a high fidelity with real-world vehicle body subframes in terms of natural modes under free boundaries. The steel beam construction of the laboratory frame, with four elastomeric mounts at the corners, permits the development of a highly accurate, yet simple, beam finite element model. This allows for a correlation study between the experiment and model that helps shed light upon the underlying physical phenomenon.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

With the enhancements in vehicle electrification and autonomous vehicles, Traffic systems are also being improved at an accelerated rate to aid the development of improving fuel economy standards. For this to be possible, it is essential that traffic can be accurately modeled and predicted. The existing toolsets are proprietary and expensive and traffic modeling is not a trivial task due to its dependence on various factors such as place, time, and weather. To address these issues, an entirely open-source Software-In-Loop (SIL) fleet-focused traffic modeling toolset has been developed with the ability to take environmental factors with powertrain-in-the-loop into account leveraging Simulation of Urban Mobility (SUMO) and python. The proposed SIL toolset encompasses the creation of a microscopic traffic distribution which accounts for the usual traffic trends of a typical day.

This paper describes the development of a more accurate shock absorber model in order to obtain better vehicle simulation results. Previous shock models used a single spline to represent shock force versus shock velocity curves. These models produced errors in vehicle simulations because the damper characteristics are better represented by the application of a hysteresis loop in the model. Thus, a new damper model that includes a hysteresis loop is developed using Matlab Simulink. The damper characteristics for the new model were extracted from measurements made on a shock dynamometer. The new model better represents experimental shock data. The new shock model is incorporated into two different lumped-parameter vehicle models: one is a three degree-of-freedom vehicle handling model and the other is a seven degree-of-freedom vehicle ride model. The new damper model is compared with the previous model for different shock mileages (different degrees of wear).

A vibration isolator or mount is often modeled by the Voigt model describing uni-axial (longitudinal) motion with frequency-invariant parameters. However, wave effects due to the mass distribution within the isolator are observed as the frequency is increased. Further, flexural stiffness components play an important role, leading to off-axis and coupling effects. Thus, the simplified mount models could lead to erroneous predictions of the dynamic behavior of an overall system such as automotive powertrain or chassis mounting systems. This article compares various approximate isolator models using a multi-dimensional mobility model that is based on the continuous system theory. Harmonic force and moment excitations are separately applied to a rigid body source to investigate the multi-dimensional vibratory behavior. Analysis is however limited to a linear time-invariant system and the mobility synthesis method is utilized to predict the frequency domain behavior.

The importance of fluid-structure interaction (FSI) is of increasing concern in automotive design criteria as automobile hoods become lighter and thinner. This work focuses on computational simulation and analysis of automobile hoods under unsteady aerodynamic loads encountered at typical highway conditions while trailing another vehicle. These driving conditions can cause significant hood vibrations due to the unsteady loads caused by the vortex shedding from the leading vehicle. The study is carried out using coupled computational fluid dynamics (CFD) and computational structural dynamics (CSD) codes. The main goal of this work is to characterize the importance of fluid modeling fidelity to hood buffeting response by comparing fluid and structural responses using both Reynolds-Averaged Navier-Stokes (RANS) and detached eddy simulation (DES) approaches. Results are presented for a sedan trailing another sedan.

Flight tests of a new 13% General Aviation Airfoil - the GA(W)-2 - gloved full span onto the existing wing of a Beech Sundowner have generated chordwise pressure distributions and wake surveys. Section lift, drag and moment coefficients derived from these measurements verify wind tunnel data and theory predicting the performance of this airfoil. The effect of steps, rivets and surface coatings upon the drag of the GA(W)-2 was also evaluated.

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.