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Studying the kinetic and kinematics of the rim-tire combination is very important in full vehicle simulations, as well as for the tire design process. Tire maneuvers are either quasi-static, such as steady-state rolling, or dynamic, such as traction and braking. The rolling of the tire over obstacles and potholes and, more generally, over uneven roads are other examples of tire dynamic maneuvers. In the latter case, tire dynamic models are used for durability assessment of the vehicle chassis, and should be studied using high fidelity simulation models. In this study, a three-dimensional finite element model (FEM) has been developed using the commercial software package ABAQUS. The purpose of this study is to investigate the tire dynamic behavior in multiple case studies in which the transient characteristics are highly involved.

The road profile has been shown to have significant effects on various vehicle conditions including ride, handling, fatigue or even energy efficiency; as a result it has become a variable of interest in the design and control of numerous vehicle parts. In this study, an integrated state estimation algorithm is proposed that can provide continuous information on road elevation and profile variations, primarily to be used in active suspension controls. A novel tire instrumentation technology (smart tire) is adopted together with a sensor couple of wheel attached accelerometer and suspension deflection sensor as observer inputs. The algorithm utilizes an adaptive Kalman filter (AKF) structure that provides the sprung and unsprung mass displacements to a sliding-mode differentiator, which then yields to the estimation of road elevations and the corresponding road profile along with the quarter car states.

Minimizing the stress concentrations around cutouts in a plate is often a design problem, especially in the Aerospace industry. A problem of optimizing spatially varying fiber paths in a symmetric, linear orthotropic composite laminate with a cutout, so as to achieve minimum stress concentration under remote unidirectional tensile loading is of interest in this study. A finite element (FE) model is developed to this extent, which constraints the fiber angles while optimizing the fiber paths, proving essential in manufacturing processes. The idea to be presented could be used to derive fiber paths that would drastically reduce the Stress Concentration Factor (SCF) in a symmetric laminate by using spatially varying fibers in place of unidirectional fibers. The model is proposed for a four layer symmetric laminate, and can be easily reproduced for any number of layers.

Dynamic game theory brings together different features that are keys to many situations in control design: optimization behavior, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely, the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degree of freedom (DOF) vehicle handling performance model is put into discrete form to develop the game equations of motion.

A graphical user interface (GUI) toolbox called Vehicle System Simulator (VSS) is developed in MATLAB to ease the use of this vehicle model and hopefully encourage its widespread application in the future. This toolbox uses the inherent MATLAB discrete-time solvers and is mainly based on Level-2 s-function design. This paper describes its built-in vehicle dynamics model based on multibody dynamics approach and nonlinear tire models, and traction/braking control systems including Cruise Control and Differential Braking systems. The built-in dynamics model is validated against CarSim 8 and the simulation results prove its accuracy. This paper illustrates the application of this new MATLAB toolbox called Vehicle System Simulator and discusses its development process, limitations, and future improvements.

Rational design for fire safety necessarily includes consideration of risk tradeoffs that tend to reduce one risk but may increase another. Traditional engineering design criteria can be supplemented with important factors that rely on expertise from other disciplines. Engineering analysis may be able to address reduction in fire risk due to the introduction of new technology, but may not address the social costs associated with this new technology. For example, the resultant increase in vehicle cost may prevent some people from purchasing a vehicle (impacting individuals' lives), may reduce the number of vehicles sold (impacting manufacturers), and may reduce taxes collected (impacting the government). This must be weighed against decreased risk of property damage, injury, and fatality due to fire. In this paper, the methods of benefit-cost analysis from economics were applied to make this evaluation.

Modern thermal propulsion systems (TPS) as part of hybrid powertrains are becoming increasingly complex. They have an increased number of components in comparison to traditionally powered vehicles leading to increased demand in packaging requirements. Many of the components in these systems relate to achieving efficiency gains, weight saving and pollutant reduction. This includes turbochargers and diesel or gasoline particulate filters for example and these are known to be very sensitive to inlet boundary conditions. When overcoming packaging requirements, sub-optimal flow distributions throughout the TPS can easily occur. Moreover, the individual components are often designed in isolation assuming relatively flat and artificially quiescent inlet flow conditions in comparison to those they are actually presented with. Thus, some of the efficiency benefits are lost through reduced component aerodynamic efficiency.

In applications ranging from design of customized vehicle interiors to virtual testing of biomedical devices, the processes of modeling, design and analysis involve the simultaneous treatment of artifacts (i.e., parts designed by humans) and anatomical structures. An inherent conflict arises because the geometric descriptions are completely different. Artifact descriptions are typically the output of computer-aided design (CAD) software and consist of a collection of parametric patches that comprise the boundary of the artifact. In stark contrast, the native description of an anatomical structure typically consists of an image stack obtained using a volumetric scanning technology such as computed tomography (CT) or magnetic resonance imaging (MRI). Current practice for simultaneously dealing with both categories of entities involves working primarily in the world of CAD.

The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle. This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data.

In modern aircraft power systems, active power converters are promising replacements for transformer rectifier units concerning efficiency and weight. To assess the benefits of active power converters, converter design and optimization should be carefully done under the operation requirements of aircraft applications: electromagnetic interference (EMI) standards, power quality standards, etc. Moreover, certain applications may have strict limits on other converter specifications: weight, size, converter loss, etc. This paper presents the methodology for performance optimization of different active power converters (active front-ends, isolated DC/DC converters and three-phase isolated converters) for aircraft applications. Key methods for power converter component (e.g. inductors, semiconductor devices, etc.) performance optimization and loss calculation are introduced along with the converter optimization procedure.

This paper studies the effect of different longitudinal load conditions, roundabout cross-sectional geometry, and different semi-truck pneumatic suspension systems on roll stability in roundabouts, which have become more and more popular in urban settings. Roundabouts are commonly designed in their size and form to accommodate articulated heavy vehicles (AHVs) by evaluating such affects as off-tracking. However, the effect of the roadway geometry in roundabouts on the roll dynamics of semi-tractors and trailers are equally important, along with their entry and exit configuration. , Because the effect of the roundabout on the dynamics of trucks is further removed from the immediate issues considered by roadway planner, at times they are not given as much consideration as other roadway design factors.

This study investigates using driver prediction to anticipate energy usage over a 160-meter look-ahead distance for a series, plug-in, hybrid-electric vehicle to improve conventional thermostatic powertrain control. Driver prediction algorithms utilize a hidden Markov model to predict route and a regression tree to predict speed over the route. Anticipated energy consumption is calculated by integrating force vectors over the look-ahead distance using the predicted incline slope and vehicle speed. Thermostatic powertrain control is improved by supplementing energy produced by the series generator with regenerative braking during events where anticipated energy consumption is negative, typically associated with declines or decelerations.

Binder jetting of sand molds and cores for metal casting provides a scalable and efficient means of producing metal components with complex geometric features made possible only by Additive Manufacturing. Topology optimization software that can mathematically determine the optimum placement of material for a given set of design requirements has been available for quite some time. However, the optimized designs are often not manufacturable using standard metal casting processes due to undercuts, backdraft and other issues. With the advent of binder-based 3D printing technology, sand molds and cores can be produced to make these optimized designs as metal castings.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently modeling and bench testing powertrain components for a parallel plug-in hybrid electric vehicle (PHEV). The custom powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. The engine, a General Motors (GM) L83 5.3L V8 with Active Fuel Management (AFM) from a 2014 Silverado, is of particular importance for vehicle integration and functionality. The engine is one of two torque producing components in the powertrain. AFM allows the engine to deactivate four of the eight cylinders which is essential to meet competition goals to reduce petroleum energy use and greenhouse gas emissions. In-vehicle testing is performed with a 2014 Silverado on a closed course to understand the criteria to activate AFM. Parameters required for AFM activation are monitored by recording vehicle CAN bus traffic.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended range hybrid electric vehicle. The competition requires participating teams to re-engineer a stock crossover utility vehicle donated by GM. The result of this design process is an Extended Range Electric Vehicle (EREV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design has achieved an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an all-electric range of 87 km (54 miles) [1].

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012 - 2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption, WTW greenhouse gas and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP), HEVT will design, build, and refine an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle. In year 1 of the competition, HEVT has designed a powertrain to meet and exceed the goals of the competition.

The Unmanned Ground Vehicle Competition is jointly sponsored by the SAE, the Association for Unmanned Vehicle Systems (AUVS), and Oakland University. College teams, composed of both undergraduate and graduate students, build autonomous vehicles that compete by navigating a 139 meter outdoor obstacle course. The course, which includes a sand pit and a ramp, is defined by painted continuous or dashed boundary lines on grass and pavement. The obstacles are arbitrarily placed, multi-colored plastic-wrapped hay bales. The vehicles must be between 0.9 and 2.7 meters long and less than 1.5 meters wide. They must be either electric-motor or combustion-engine driven and must carry a 9 kilogram payload. All computational power, sensing and control equipment must be carried on board the vehicle. The technologies employed are applicable in Intelligent Transportation Systems (ITS).

As automotive manufacturers continue to increase their use of thermoplastics for interior components (due to cost, weight, …), the potential for frictionally incompatible materials contacting each other, resulting in squeaks and rattles, will also increase. This will go counter to the increased customer demand for quieter interiors. To address this situation, Ford's Advanced Vehicle Technology Squeak and Rattle Prevention Engineering Department and Virginia Tech have developed a tester that can measure friction as a function of relative sliding velocity during frictional instabilities such as stick slip. The Ford/VT team is developing a polymeric material pairing database that will be used as a guide for current and future designs to eliminate potential squeak concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, an analytical model will be developed as a tool to predict frictional behavior.