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A new and unique electric vehicle powertrain model based on bidirectional power flow for propel and regenerative brake power capture is developed and applied to production battery electric vehicles. The model is based on a Willans line model to relate power input from the battery and power output to tractive effort, with one set of parameters (marginal efficiency and an offset loss) for the bidirectional power flow through the powertrain. An electric accessory load is included for the propel, brake and idle phases of vehicle operation. In addition, regenerative brake energy capture is limited with a regen fraction (where the balance goes to friction braking), a power limit, and a low-speed cutoff limit. The purpose of the model is to predict energy consumption and range using only tractive effort based on EPA published road load and test mass (test car list data) and vehicle powertrain parameters derived from EPA reported unadjusted UDDS and HWFET energy consumption.

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is ready to compete in the Year 3 Final Competition for EcoCAR 2: Plugging into the Future. The team is confident in the reliability of their vehicle, and expects to finish among the top schools at Final Competition. During Year 3, the team refined the vehicle while following the EcoCAR 2 Vehicle Development Process (VDP). Many refinements came about in Year 3 such as the implementation of a new rear subframe, the safety analysis of the high voltage (HV) bus, and the integration of Charge Sustaining (CS) control code. HEVT's vehicle architecture is an E85 Series-Parallel Plug-In Hybrid Electric Vehicle (PHEV), which has many strengths and weaknesses. The primary strength is the pure EV mode and Series mode, which extend the range of the vehicle and reduce Petroleum Energy Usage (PEU) and Greenhouse Gas (GHG) emissions.

In the past few years, the price of petroleum based fuels, especially vehicle fuels such as gasoline and diesel, have been increasing at a significant rate. Consequently, there is much more consumer interest related to reducing fuel consumption of conventional and hybrid electric vehicles (HEVs). The “pulse and glide” (PnG) driving strategy is first applied to a conventional vehicle to quantify the fuel consumption benefits when compared to steady state speed (cruising) conditions over the same time and distance. Then an HEV is modeled and tested to investigate if a hybrid system can further reduce fuel consumption with the proposed strategy. Note that the HEV used in this study has the advantage that the engine can be automatically shut off below a certain speed (∼40 mph, 64 kph) at low loads, however a driver must shut off the engine manually in a conventional vehicle to apply this driving strategy.

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech has achieved the Year 2 goal of producing a 65% functional mule vehicle suitable for testing and refinement, while maintaining the series-parallel plug-in hybrid architecture developed during Year 1. Even so, further design and expert consultations necessitated an extensive redesign of the rear powertrain and front auxiliary systems packaging. The revised rear powertrain consists of the planned Rear Traction Motor (RTM), coupled to a single-speed transmission. New information, such as the dimensions of the high voltage (HV) air conditioning compressor and the P2 motor inverter, required the repackaging of the hybrid components in the engine bay. The P2 motor/generator was incorporated into the vehicle after spreading the engine and transmission to allow for the required space.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2005 - 2007 Challenge X advanced technology vehicle competition series, sponsored by General Motors Corporation, the U.S. Department of Energy, and Argonne National Lab. This report documents the Equinox REVLSE (Renewable Energy Vehicle, the Larsen Special Edition) design and specifies how it meets the Vehicle Technical Specifications (VTS) set by Challenge X and HEVT through simulation and test results. The report also documents the vehicle control development process, specifies the control code generation, demonstrates an analysis of hybrid powertrain losses, and presents the REVLSE vehicle balance in its intended market.

A crucial step to designing and building more efficient vehicles is modeling powertrain energy consumption. While accurate modeling is indeed key to effective and efficient design, a fundamental understanding of the powertrain and auxiliary systems that contribute to the energy consumption of a vehicle is equally as important. This paper presents a methodology that has been packaged into a tool, called VTool (short for Vehicle Tool), which can be used to estimate the energy consumption of a vehicle powertrain. The method is intrinsically designed to foster understanding of the vehicle powertrain as it relates to energy consumption and losses while still providing reasonably accurate results. This paper briefly explains the methodology of VTool and demonstrates the capability of VTool as a design tool by presenting 4 example exercises.

This paper describes a three part analysis to characterize the interaction between the female upper extremity and a helicopter cockpit side airbag system and to develop dynamic hyperextension injury criteria for the female elbow joint. Part I involved a series of 10 experiments with an original Army Black Hawk helicopter side airbag. A 5th percentile female Hybrid III instrumented upper extremity was used to demonstrate side airbag upper extremity loading. Two out of the 10 tests resulted in high elbow bending moments of 128 Nm and 144 Nm. Part II included dynamic hyperextension tests on 24 female cadaver elbow joints. The energy source was a drop tower utilizing a three-point bending configuration to apply elbow bending moments matching the previously conducted side airbag tests. Post-test necropsy showed that 16 of the 24 elbow joint tests resulted in injuries.

Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired for providing quick, high-level estimations for a BEV without requiring extensive vehicle and computational resources. Therefore, the goal of this paper is to create a simple, yet reliable vehicle model, that can estimate the energy consumption of most electric vehicles on the market by using parameter normalization techniques. These vehicle parameters include the vehicle test weight and performance to obtain a unified net Willans line to describe the input/output power using a linear relationship.

Safety and minimal transit time are vital during transportation of essential commodities and passengers, especially in winter conditions. Icy roads are the worst driving conditions with the least available friction, leaving valuable cargo and precious human lives at stake. The study investigates the available friction at the tire-ice interface due to changes in key operational parameters. Experimental analysis of tractive performance of tires on ice was carried out indoor, using the terramechanics rig located at the Advanced Vehicle Dynamics Laboratory (AVDL) at Virginia Tech. The friction-slip ratio curves obtained from indoor testing were inputted into TruckSIM, defining tire behavior for various ice scenarios and then simulating performance of trucks on ice. The shortcomings of simulations in considering the effects of all the operational parameters result in differences between findings of indoor testing and truck performance simulations.

Nano-silver sintered bonding was carried out at 275°C and under 3MPa pressures, and soldering in a vacuum reflowing oven to reduce voiding. Both joints are subject to large shear stresses due to the mismatch in coefficients of thermal expansion (CTE) between the chip and the substrate. In this study, residual stresses in the chip-on-substrate assemblies were determined by measuring the bending curvatures of the bonded structures. An in-house optical setup measured the bending curvatures using a thin-film stress measurement technique. From the measured bending curvatures and the mechanical properties of the constituent materials, residual stresses were calculated. The thermo-mechanical reliabilities of both joining techniques were tested by thermal cycling. The chip assemblies were cycled between -40°C and 125°C (100 minutes of cycle time, 10 minutes of dwell time) and the changes in their bending curvatures were measured.

Mechanical and thermal properties of the rubber compounds of a tire play an important role in the overall performance of the tire when it is in contact with the terrain. Although there are many studies conducted on the properties of the rubber compounds of the tire to improve some of the tire characteristics such as the wear of the tread, there is a limited number of studies that focused on the performance of the tire when it is in contact with ice. This study is a part of a more comprehensive project looking into tire-ice performance and modeling. A significant part of this study is the experimental investigation of the effect of rubber compounds on tire performance in contact with ice. For this, four tires have been selected for testing. Three of them are completely identical in all tire parameters (such as tire dimensions), except for the rubber compounds. Several tests were conducted for the chosen tires in three modes: free rolling, braking, and traction.

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.

Ride control of military vehicles is challenging due to varied terrain and mission requirements such as operating weight. Achieving top speeds on rough terrain is typically considered a key performance parameter, which is always constrained by ride discomfort. Many military vehicles using passive suspensions suffer with compromised performance due to single tuning solution. To further stretch the performance domain to achieving higher speeds on rough roads, semi-active suspensions may offer a wide range of damping possibilities under varying conditions. In this paper, various semi-active control strategies are examined, and improvements have been made, particularly, to the acceleration-driven damper (ADD) strategy to make the approach more robust for varying operating conditions. A seven degrees of freedom ride model and a quarter-car model were developed that were excited by a random road process input modeled using an auto-regressive time series model.

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.

The incorporation of reliability theory into a fatigue analysis algorithm is studied. This probabilistic approach gives designers the ability to quantify “real world” variations existing in the material properties, geometry, and loading of engineering components. Such information would serve to enhance the speed and accuracy of current design techniques. An automobile wheel assembly is then introduced as an example of the applications of this durability/reliability design package.

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].

Modern fatigue analysis techniques, that can provide reliable estimates of the service performance of components and structures, are finding increasing use in vehicle development programs. A major objective of such efforts is the prediction of the field performance of a fleet of vehicles as influenced by the host of design, manufacturing, and performance variables. An approach to this complex problem, based on the incorporation of probability theory in established life prediction methods, is presented. In this way, quantitative estimates of the lifetime distribution of a population are obtained based on anticipated, or specified, variations in component geometry, material processing sequences, and service loading. The application of this approach is demonstrated through a case study of an automotive transmission component.

3D digital human modeling (DHM) tools for vehicle packaging facilitate ergonomic design and evaluation based on anthropometry, comfort, and force analysis. It is now possible to quickly predict postures and positions for drivers with selected anthropometry based on ergonomics principles. Despite their powerful visual representation technology for human movements and postures, these tools are still questioned with regard to the validity of the output they provide, especially when predictions are made for different populations. Driving postures and positions of two populations (i.e. North Americans and Koreans) were measured in actual and mock-up SUVs to investigate postural differences and evaluate the results provided by a DHM tool. No difference in driving postures was found between different stature groups within the same population. Between the two populations, however, preferred angles differed for three joints (i.e., ankle, thigh, and hip).

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is excited about the opportunity to apply for participation in the next Advanced Vehicle Technology Competition. EcoCAR 3 is a new four year competition sponsored by the Department of Energy and General Motors with the intention of promoting sustainable energy in the automotive sector. The goal of the competition is to guide students from universities in North America to create new and innovative technologies to reduce the environmental impact of modern day transportation. EcoCAR 3, like its predecessors, will give students hands-on experience in designing and implementing advanced technologies in a setting similar to that of current production vehicles.

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.