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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.

Intersection crashes are a frequent and dangerous crash mode in the U.S. Emerging Intersection Advanced Driver Assistance Systems (I-ADAS) aim to assist the driver to mitigate the consequences of vehicle-to-vehicle crashes at intersections. In support of the design and evaluation of such intersection assistance systems, characterization of the road, environment, and drivers associated with intersection crashes is necessary. The objective of this study was to characterize intersection crashes using nationally representative crash databases that contained all severity, serious injury, and fatal crashes. This study utilized four national crash databases: the National Automotive Sampling System, General Estimates System (NASS/GES); the NASS Crashworthiness Data System (CDS); and the Fatality Analysis Reporting System (EARS) and the National Motor Vehicle Crash Causation Survey (NMVCCS).

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.

Vehicle stability is maintained by proper interactions between the driver and vehicle stability control system. While driver describes the desired target path by commanding steering angle and acceleration/deceleration rates, vehicle stability controller tends to stabilize higher dynamics of the vehicle by correcting longitudinal, lateral, and roll accelerations. In this paper, a finite-horizon optimal solution to vehicle stability control is introduced in the presence of driver's dynamical decision making structure. The proposed concept is inspired by Nash strategy for exactly known systems with more than two players, in which driver, commanding steering wheel angle, and vehicle stability controller, applying compensated yaw moment through differential braking strategy, are defined as the dynamic players of the 2-player differential linear quadratic game.

This study undertakes an investigation of the effect of battery charge balance in hybrid electric vehicles (HEVs) on EPA fuel economy label values. EPA's updated method was fully implemented in 2011 and uses equations which weight the contributions of fuel consumption results from multiple dynamometer tests to synthesize city and highway estimates that reflect average U.S. driving patterns. For the US06 and UDDS cycles, the test results used in the computation come from individual phases within the overall certification driving cycles. This methodology causes additional complexities for hybrid vehicles, because although they are required to be charge-balanced over the course of a full drive cycle, they may have net charge or discharge within the individual phases. As a result, the fuel consumption value used in the label value calculation can be skewed.

One seminal question that faces a vehicle's driver (either human or computer) is predicting the capability of the vehicle as it encounters upcoming terrain. A Performance Margin (PM) is defined in this work as the ratio of the required tractive effort to the available tractive effort for the front and rear respectively. This simple definition stems from and incorporates many traditional handling metrics and is robust in its scope of applicability. The PM is implemented in an Intervention Strategy demonstrating its use to avoid situations in which the vehicle exceeds its handling capabilities. Results from a design case study are presented to show the potential efficacy of developing a PM-based control system.

This paper presents a system designed to develop a high-resolution map of public roads by capturing high-resolution surface images. Unlike conventional system, the proposed system applies a field programmable gate array (FPGA) to synchronize camera, Inertial Measurement Unit (IMU), and Global Positioning System (GPS) by using FPGA’s high clock frequency and flexibility to multiple devices. The proposed system, which can be mounted on a regular vehicle, contains a Complementary Metal–Oxide–Semiconductor (CMOS) camera which can achieve 0.006 ms shutter speed and 150 fps frame rate. This camera’s high shutter speed and high frame rate can help capturing images with overlapping region at fast driving speed so that no area is missing from road surface image capturing.

The objective of this work is to provide a relatively simple battery energy storage and loss model that can be used for technology screening and design/sizing studies of hybrid electric vehicle powertrains. The model dynamic input requires only power demand from the battery terminals (either charging or discharging), and outputs internal battery losses, state-of-charge (SOC), and pack temperature. Measured data from a vehicle validates the model, which achieves reasonable accuracy for current levels up to 100 amps for the size battery tested. At higher current levels, the model tends to report a higher current than what is needed to create the same power level shown through the measured data. Therefore, this battery model is suitable for evaluating hybrid vehicle technology and energy use for part load drive cycles.

Restrictions on track testing, combined with advances in technology, have contributed to an increased dependence on sensors and data acquisition for diagnosing problems and improving performance in motorsports vehicles. This dependence has created a new set of challenges for race engineers to collect quality data from a vehicle at the track. Successful 7- or 8-post shaker rig testing is highly dependent on the quality of the data acquired at the track. An improperly configured data acquisition system can actually be worse than a faulty sensor. This paper highlights a few of the most common problems in motorsports data acquisition: aliasing and sample rate selection. The effects of these problems are described for typical suspension sensors such as accelerometers, shock potentiometers, load cells, and laser ride height sensors. An experimental case study is presented to explain the implications of these problems.

This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

This study outlines a protocol for image data collection acquired from human volunteers. The data set will serve as the foundation of a consolidated effort to develop the next generation full-body Finite Element Analysis (FEA) models for injury prediction and prevention. The geometry of these models will be based off the anatomy of four individuals meeting extensive prescreening requirements and representing the 5th and 50th percentile female, and the 50th and 95th percentile male. Target values for anthropometry are determined by literature sources. Because of the relative strengths of various modalities commonly in use today in the clinical and engineering worlds, a multi-modality approach is outlined. This approach involves the use of Computed Tomography (CT), upright and closed-bore Magnetic Resonance Imaging (MRI), and external anthropometric measurements.

This study pertains to motion control algorithms using statistical calculations based on relative displacement measurements, in particular where the rattle space is strictly limited by fixed end-stops and a load leveling system that allows for roll to go undetected by the sensors. One such application is the cab suspension of semi trucks that use widely-spaced springs and dampers and a load leveling system that is placed between the suspensions, near the center line of the cab. In such systems it is possible for the suspension on the two sides of the vehicle to settle at different ride heights due to uneven loading or the crown of the road. This paper will compare the use of two moving average signals (one positive and one negative) to the use of one root mean square (RMS) signal, all calculated based on the relative displacement measurement.

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.

The performance of five different skyhook control methods is studied experimentally, using a quarter-car rig. The control methods that are analyzed include: skyhook control, groundhook control, hybrid control, displacement skyhook, and relative displacement skyhook. Upon evaluating the performance of each method in frequency domain for various control conditions, they are compared with each other as well as with passive damping. The results indicate that no one control method outperforms other control methods at both the sprung and unsprung mass natural frequencies. Each method can perform better than the other control methods in some respect. Hybrid control, however, comes close to providing the best compromise between different dynamic demands on a primary suspension. The results indicate that hybrid control can offer benefits to both the sprung and unsprung mass with control gain settings that provide equal contributions from skyhook control and groundhook control.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently developing a control strategy for a parallel plug-in hybrid electric vehicle (PHEV). The hybrid powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. Fuzzy rule sets determine the torque split between the motor and the engine using the accelerator pedal position, vehicle speed and state of charge (SOC) as the input variables. The torque producing components are a 280 kW V8 L83 engine with active fuel management (AFM) and a post-transmission (P3) 100 kW custom motor. The vehicle operates in charge depleting (CD) and charge sustaining (CS) modes. In CD mode, the model drives as an electric vehicle (EV) and depletes the battery pack till a lower state of charge threshold is reached. Then CS operation begins, and driver demand is supplied by the engine operating in V8 or AFM modes with supplemental or loading torque from the P3 motor.

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.

The more electric aircraft (MEA) concept has gained popularity in recent years. As the main building blocks of advanced aircraft power systems, multi-converter power electronic systems have advantages in reliability, efficiency and weight reduction. The pulsed power load has been increasingly adopted--especially in military applications--and has demonstrated highly nonlinear characteristics. Consequently, more design effort needs to be placed on power conversion units and energy storage systems dealing with this challenging mission profile: when the load is on, a large amount of power is fed from the power supply system, and this is followed by periods of low power consumption, during which time the energy storage devices get charged. Thus, in order to maintain the weight advantage of MEA and to keep the normal functionality of the aircraft power system in the presence of a high-peak pulsed power load, this paper proposes a novel multidisciplinary weight optimization technique.

Tire-pavement interaction noise (TPIN) is a dominant source for passenger cars and trucks above 40 km/h and 70 km/h, respectively. TPIN is mainly generated from the interaction between the tire and the pavement. In this paper, twenty-two passenger car radial (PCR) tires of the same size (16 in. radius) but with different tread patterns were tested on a non-porous asphalt pavement. For each tire, the noise data were collected using an on-board sound intensity (OBSI) system at five speeds in the range from 45 to 65 mph (from 72 to 105 km/h). The OBSI system used an optical sensor to record a once-per-revolution signal to monitor the vehicle speed. This signal was also used to perform order tracking analysis to break down the total tire noise into two components: tread pattern-related noise and non-tread pattern-related noise.

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].

This paper focuses on stability of automotive supervisory control systems (ASCSs). It serves to introduce the concept of stability with respect to an entire ASCS. The realm of ASCSs is categorized and a brief description of pre-existing classical methods of stability analysis is presented. With the concept then having been fully introduced, an approach to evaluating stability of a key category of ASCS, the rule-based deterministic ASCS, is presented. This approach, cited from unrelated modern literature concerning stability of deterministic finite state machines, is novel in that its original target research area was not specifically automotive engineering.