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In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks (i.e., gross vehicle weight greater than 4,536 kg). The Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed by the Federal Motor Carrier Safety Administration (FMCSA) to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Visual warnings have been shown to be effective, assuming the following driver is looking directly at the warning display or has his/her eyes drawn to it. A visual warning can be placed where it is needed and it can be designed so that its meaning is nearly unambiguous. FMCSA contracted with the Virginia Tech Transportation Institute (VTTI) to investigate potential benefit of additional rear warning-light configurations as rear-end crash countermeasures for heavy trucks.

Under the borderline autoignition conditions experienced during cold-starting of diesel engines, the amount and composition of residual gases may play a deterministic role. Among the intermediate species produced by misfiring and partially firing cycles, formaldehyde (HCHO) is produced in significant enough amounts and is sufficiently stable to persist through the exhaust and intake strokes to kinetically affect autoignition of the following engine cycle. In this work, the effect of HCHO addition at various phases of autoignition of n-heptane-air mixtures is kinetically modeled. Results show that HCHO has a retarding effect on the earliest low-temperature heat release (LTHR) phase, largely by competition for hydroxyl (OH) radicals which inhibits fuel decomposition. Conversely, post-LTHR, the presence of HCHO accelerates the occurrence of high-temperature ignition.

Fuel wall impingement commonly occurs in small-bore diesel engines. Particularly during engine starting, when wall temperatures are low, the evaporation rate of fuel film remaining from previous cycles plays a significant role in the autoignition process that is not fully understood. Pre-injection chemiluminescence (PIC), resulting from low-temperature oxidation of evaporating fuel film and residual gases, was measured over 3200 μsec intervals at the end of the compression strokes, but prior to fuel injection during a series of starting sequences in an optical diesel engine. These experiments were conducted to determine the effect of this parameter on combustion phasing and were conducted at initial engine temperatures of 30, 40, 50 and 60°C, at swirl ratios of 2.0 and 4.5 at 1000 RPM. PIC was determined to increase and be highly correlated with combustion phasing during initial cycles of the starting sequence.

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.

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.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Path planning and re-planning for serial 6 degree of freedom (DOF) robotic systems is challenging due to complex kinematic structure and application conditions which affects the robot's tool frame position, orientation and singularity avoidance. These three characteristics represent the key elements for production planning and layout design of the automated manufacturing systems. The robot trajectory represents series of connected points in 3D space. Each point is defined with its position and orientation related to the robot's base frames or predefined user frame. The robot will move from point to point using the desired motion type (linear, arc, or joint). The trajectory planning requires first to check if robot can reach the selected part(s). This can be simply done by placing the part(s) inside the robot's work envelope. The robot's work envelope represents a set of all robots' reachable points without considering their orientation.

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.

Vehicle analytical models are often favorable due to describing the physical phenomena associated with vehicle operation following from the principles of physics, with explainable mathematical trends and with extendable modeling to other types of vehicle. However, no experimentally validated analytical model has been developed as yet of diesel engine fuel consumption rate. The present paper demonstrates and validates for trucks and light commercial vehicles an analytical model of supercharged diesel engine fuel consumption rate. The study points out with 99.6% coefficient of determination that the average percentage of deviation of the steady speed-based simulated results from the corresponding field data is 3.7% for all Freeway cycles. The paper also shows with 98% coefficient of determination that the average percentage of deviation of the acceleration-based simulated results from the corresponding field data under negative acceleration is 0.12 %.

This paper presents experimental investigations of determining and analyzing low-frequency, low-SNR (Signal to Noise Ratio) noise sources of an automobile by using a new technology known as Sound Viewer. Such a task is typically very difficult to do especially at low or even negative SNR. The underlying principles behind the Sound Viewer technology consists of a passive SODAR (Sonic Detection And Ranging) and HELS (Helmholtz Equation Least Squares) method. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, etc.

This paper presents experimental investigations of diagnosing and analyzing the low-frequency, low- SNR (Signal to Noise Ratio) noise sources of three motorcycles using a hybrid technology that consists of a passive SODAR (Sonic Detection And Ranging) and modified HELS (Helmholtz Equation Least Squares) methods. The former enables one to determine the precise locations of multiple sound sources in 3D space simultaneously over the entire frequency range that is consistent with a measurement microphone in non-ideal environment, where there are random background noise and unknown interfering signals. The latter enables one to reconstruct all acoustic quantities such as the acoustic pressure, acoustic intensity, time-averaged acoustic power, radiation patterns, and sound transmission paths through arbitrarily shaped vibrating structures.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.

With the mass movement toward electrification and renewable technologies, the scope of innovation of electrification has gone beyond the automotive industry into areas such as electric motorcycle applications. This paper provides a discussion of the methodology and complexities of converting an internal combustion motorcycle to an electric motorcycle. In developing this methodology, performance goals including, speed limits, range, weight, charge times, as well as riding styles will be examined and discussed. Based on the goals of this paper, parts capable of reaching the performance targets are selected accordingly. Documentation of the build process will be presented along with the constraints, pitfalls, and difficulties associated with the process of the project. The step-by-step process that is developed can be used as a guideline for future build and should be used as necessary.

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).

The Dimensional Model of Driver Demand is extended to include Auditory-Vocal (i.e., pure “voice” tasks), and Mixed-Mode tasks (i.e., a combination of Auditory-Vocal mode with visual-only, or with Visual-Manual modes). The extended model was validated with data from 24 participants using the 2014 Toyota Corolla infotainment system in a video-based surrogate driving venue. Twenty-two driver performance metrics were collected, including total eyes-off-road time (TEORT), mean single glance duration (MSGD), and proportion of long single glances (LGP). Other key metrics included response time (RT) and miss rate to a Tactile Detection Response Task (TDRT). The 22 metrics were simplified using Principal Component Analysis to two dimensions. The major dimension, explaining 60% of total variance, we interpret as the attentional effects of cognitive demand. The minor dimension, explaining 20% of total variance, we interpret as physical demand.

Automated driving functionalities delivered through Advanced Driver Assistance System (ADAS) have been adopted more and more frequently in consumer vehicles. The development and implementation of such functionalities pose new challenges in safety and functional testing and the associated validations, due primarily to their high demands on facility and infrastructure. This paper presents a rather unique Vehicle-in-the-Loop (VIL) test setup and methodology compared those previously reported, by combining the advantages of the hardware-in-the-loop (HIL) and traditional chassis dynamometer test cell in place of on-road testing, with a multi-agent real-time simulator for the rest of test environment.

The Hotelling multivariate control chart and the sample generalized variance |S| are used to monitor the mean and dispersion of vehicle build vision data including the pallet information to identify the non-conforming pallets that are used in body shops of FCA US LLC assembly plants. An iterative procedure and the Gaussian mixture model (GMM) are used to rank the non-conforming or bad pallets in the order of severity. The Hotelling multivariate T2 test statistic along with Mason-Tracy-Young (MYT) signal decomposition method is used to identify the features that are affected by the bad pallets. These algorithms were implemented in the Advanced Pallet Analysis module of the FCA US software Body Shop Analysis Toolbox (BSAT). The identified bad pallets are visualized in a scatter plot with a different color for each of the top bad pallets. The run chart of an affected feature confirms the bad pallet by highlighting data points from the bad pallet.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

Fast and accurate characterization of stability regions and operational range with respect to pull-in voltage and displacement is critical in the design and development of MEMS resonators and switches. This paper presents a mathematical and computational procedure for modeling and analysis of static and dynamic instabilities of capacitive microdevices employing resonant microbeams. The mathematical model consists of a nonlinear microbeam under distributed electrostatic actuation and squeeze film damping. The coupled system is described by the nonlinear beam equation and a modified compressible Reynolds equation to account for the rarefied gas in the narrow gap between the microbeam and substrate. The Differential Quadrature Method (DQM) is used to discretize partial differential equations of motion and solve for static deflection, natural frequencies, static pull-in voltage, and quality factors for various encapsulation air pressures and applied DC voltages.

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.