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Consumers design different PHEVs than expert analysts assume. Experts almost uniformly assume PHEVs that offer true all-electric driving for 10 to 60 miles; consumers are more likely to design PHEVs that do not offer true all-electric driving and have short ranges over which they use grid-electricity. Thus consumers? PHEV designs are less expensive. These consumer PHEV designs do, or don?t, produce lower GHG emissions than experts? PHEVs over the next ten years. The devil is in the details, i.e., which powerplant emissions to assign to new electricity demand: marginal or average. If (based on marginal powerplant emissions) it makes almost no difference whether we sell consumer-designed or expert-assumed PHEVs over the next ten years, yet as the grid continues to de-carbonize all-electric PHEV designs emerge as clearly the better option, there is a trajectory we could be on from blended, ?short range? PHEVs to all-electric ?long range? PHEVs.

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.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An integral part of this System is an Intervention Strategy that uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. Through this strategy, the driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models. This work develops one means to alter the future vehicle states: modulating the driver's brake commands. This control strategy must be considered in relationship to changes in the throttle commands. Three key elements of this strategy are developed in this work.

A Location-Aware Adaptive Vehicle Dynamics System (LAAVDS) is developed to assist the driver in maintaining vehicle handling capabilities through various driving maneuvers. An Intervention Strategy uses a novel measure of handling capability, the Performance Margin, to assess the need to intervene. The driver's commands are modulated to affect desired changes to the Performance Margin in a manner that is minimally intrusive to the driver's control authority. Real-time implementation requires the development of computationally efficient predictive vehicle models which is the focus of this work. This work develops one means to alter the future vehicle states: modulating the driver's throttle commands. First, changes to the longitudinal force are translated to changes in engine torque based on the current operating state (torque and speed) of the engine.

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.

For (benchmark) tests it is not only useful to study the acoustic performance of the whole vehicle, but also to assess separate components such as the engine. Reflections inside the engine bay bias the acoustic radiation estimated with sound pressure based solutions. Consequently, most current methods require dismounting the engine from the car and installing it in an anechoic room to measure the sound emitted. However, this process is laborious and hard to perform. In this paper, two particle velocity based methods are proposed to characterize the sound radiated from an engine while it is still installed in the car. Particle velocity sensors are much less affected by reflections than sound pressure microphones when the measurements are performed near a radiating surface due to the particle velocity's vector nature, intrinsic dependency upon surface displacement and directivity of the sensor. Therefore, the engine does not have to be disassembled, which saves time and money.

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.

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 %.

In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.

An important trend among vehicle NVH engineers is the production of attractive engine acceleration sound quality for the enhancement of a vehicle's image and performance. In addition, customers have increasing interest and enjoyment in customizing their cars to reflect their personal taste and preferences. The PESS (Personalized Engine Sound System) has been developed for making a unique and individually customizable vehicle concept. The system allows the customers an opportunity to create a variety of engine sounds in a single vehicle using active sound design technology. In this system, three different engine sound concepts are pre-defined, Dynamic, Sporty, and Extreme. Each of the engine sounds can then be adjusted with parameters that determine the timbre, such as main order, rumble, and high order. In addition, the pedal position during acceleration has also been used as a parameter to further personalize the experience.

This Study describes about the development of new concept' rear wheel guards for the reduction of Road Noise in the passenger vehicles. The new wheel guards are proposed by various frequency chamber concept and different textile layers concept. Two wheel guards were verified by small cabin resonance and vehicle tests. Through new developing process without vehicle test, Result of road noise will be expected if this concepts and materials of wheel guard are applied into automotive vehicle. As this concept consider tire radiation noise frequency and multilayers sound control multilayers, 2 concepts reduced road noise from 0.5 to 1.0dB. The proposed method of part reverberant absorption is similar to results of vehicle tests by part absorption index. Furthermore, optimization of frequency band in wheel guards will reduce more 0.5 dB noises. As a result of the application of Aimed Helmholtz and Multilayers concept, this paper classifies reduction of the road noise, cost and weights.

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).

Pressure variation during engine combustion generates torque fluctuation that is delivered through the driveline. Torque fluctuation delivered to the tire shakes the vehicle body and causes the body components to vibrate, resulting in booming noise. HKMC (Hyundai Kia Motor Company)’s TMED (Transmission Mounted Electric Device) type generates booming noises due to increased weight from the addition of customized hybrid parts and the absence of a torque converter. Some of the improvements needed to overcome this weakness include reducing the torsion-damper stiffness, adding dynamic dampers, and moving the operation point of the engine from the optimized point. These modifications have some potential negative impacts such as increased cost and sacrificed fuel economy. Here, we introduce a method of reducing lock-up booming noise in an HEV at low engine speed.

A semi-empirical index to evaluate the noise propensity of brake friction materials is introduced. The noise propensity index (NPI) is based on the ratio of surface and matrix stiffness of the friction material, fraction of high-pressure contact plateaus on the sliding surface, and standard deviation of the surface stiffness of the friction material that affect the amplitude and frequency of the stick-slip oscillation. The correlation between noise occurrence and NPI was examined using various brake linings for commercial vehicles. The results obtained from reduced-scale noise dynamometer and vehicle tests indicated that NPI is well correlated with noise propensity. The analysis of the stick-slip profiles also indicated that the surface property affects the amplitude of friction oscillation, while the mechanical property of the friction material influences the propagation of friction oscillation after the onset of vibration.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

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.

Human expert drivers have the unique ability to combine correlated sensory inputs with repetitive learning to build complex perceptive models of the vehicle dynamics as well as certain key aspects of the tire-ground interface. This ability offers significant advantages for navigating a vehicle through the spatial and temporal uncertainties in a given environment. Conventional traction control algorithms utilize measurements of wheel slip to help insure that the wheels do not enter into an excessive slip condition such as burnout. This approach sacrifices peak performance to ensure that the slip limits are generic enough suck that burnout is avoided on a variety of surfaces: dry pavement, wet pavement, snow, gravel, etc. In this paper, a novel approach to traction control is developed using an anthropomimetic control synthesis strategy.

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.