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Active safety systems will have a great impact in the next generation of vehicles. This is partly originated by the increasing consumer's interest for safety and partly by new traffic safety laws. Control actions in the vehicle are based on an extensive environment model which contains information about relevant objects in vehicle surroundings. Sensor data fusion integrates measurements from different surround sensors into this environment model. In order to avoid system malfunctions, high reliability in the interpretation of the situation, and therefore in the environment model, is essential. Hence, the main idea of data fusion is to make use of the advantages of using multiple sensors and different technologies in order to fulfill these requirements, which are especially high due to autonomous interventions in vehicle dynamics (e. g. automatic emergency braking).

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.

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.

Modeling the tire forces and moments (F&M) generation, during combined slip maneuvers, which involves cornering and braking/driving at the same time, is essential for the predictive vehicle performance analysis. In this study, a new semi-empirical method is introduced to estimate the tire combined slip F&M characteristics based on flat belt testing machine measurement data. This model is intended to be used in the virtual tire design optimization process. Therefore, it should include high accuracy, ease of parameterization, and fast computational time. Regression is used to convert measured F&M into pure slip multi-dimensional interpolant functions modified by weighting functions. Accurate combined slip F&M predictions are created by modifying pure slip F&M with empirically determined shape functions. Transient effects are reproduced using standard relaxation length equations. The model calculates F&M at the center of the contact patch.

Plug-in Hybrid Electric Vehicles (PHEVs) have demonstrated the potential to provide significant reduction in fuel use across a wide range of dynamometer test driving cycles. Companies and research organizations are involved in numerous research activities related to PHEVs. One of the current unknowns is the impact of driving behavior and standard test procedure on the true benefits of PHEVs from a worldwide perspective. To address this issue, five different PHEV powertrain configurations (input split, parallel, series, series-output split and series-parallel), implemented on vehicles with different all-electric ranges (AERs), were analyzed on three different standard cycles (i.e., Urban Dynamometer Driving Schedule, Highway Fuel Economy Test, and New European Driving Cycle). Component sizes, manufacturing cost, and fuel consumption were analyzed for a midsize car in model year 2020 through the use of vehicle system simulations.

Models for off-road vehicles, such as farm equipment and military vehicles, require an off-road tire model in order to properly understand their dynamic behavior on off-road driving surfaces. Extensive literature can be found for on-road tire modeling, but not much can be found for off-road tire modeling. This paper presents an off-road tire model that was developed for use in vehicle handling studies. An on-road, dry asphalt tire model was first developed by performing rolling road force and moment testing. Off-road testing was then performed on dirt and gravel driving surfaces to develop scaling factors that explain how the lateral force behavior of the tire will scale from an on-road to an off-road situation. The tire models were used in vehicle simulation software to simulate vehicle behavior on various driving surfaces. The simulated vehicle response was compared to actual maximum speed before sliding vs. turning radius data for the studied vehicle to assess the tire model.

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.

Engine Start/Stop systems reduce CO₂ emissions by turning off the combustion engine at vehicle standstill. This avoids the injection of fuel that would otherwise be needed simply to overcome internal combustion engine losses. As a next development step, engine losses at higher vehicle speeds are to be addressed. During deceleration, state-of-the-art engine technology turns off fuel injection as soon as the driver releases the gas pedal, thus the combustion engine is motored by the vehicle. The engine's drag torque could be desired by the driver, e.g., as a brake assist during downhill driving. However, quite frequently the driver wishes to coast at almost constant speed. Similar to Start/Stop operation, in such situations fuel is injected to simply overcome the combustion engine's drag torque. An operation mode referred to as "Free-Wheeling" reduces CO₂ emissions under such coasting conditions by disconnecting the combustion engine from the powertrain and by turning it off.

This study evaluated the accuracy of 75 Event Data Recorders (EDRs) extracted from model year 2010-2012 Chrysler, Ford, General Motors, Honda, Mazda, and Toyota vehicles subjected to side-impact moving deformable barrier crash tests. The test report and vehicle-mounted accelerometers provided reference values to assess the EDR reported change in lateral velocity (delta-v), seatbelt buckle status, and airbag deployment status. Our results show that EDRs underreported the reference lateral delta-v in the vast majority of cases, mimicking the errors and conclusions found in some longitudinal EDR accuracy studies. For maximum lateral delta-v, the average arithmetic error was −3.59 kph (−13.8%) and the average absolute error was 4.05 kph (15.9%). All EDR reports that recorded a seatbelt buckle status data element correctly recorded the buckle status at both the driver and right front passenger locations.

The use of virtual prototyping early in the design stage of a product has gained popularity due to reduced cost and time to market. The state of the art in vehicle simulation has reached a level where full vehicles are analyzed through simulation but major difficulties continue to be present in interfacing the vehicle model with accurate powertrain models and in developing adequate formulations for the contact between tire and terrain (specifically, scenarios such as tire sliding on ice and rolling on sand or other very deformable surfaces). The proposed work focuses on developing a ground vehicle simulation capability by combining several third party packages for vehicle simulation, tire simulation, and powertrain simulation. The long-term goal of this project consists in promoting the Digital Car idea through the development of a reliable and robust simulation capability that will enhance the understanding and control of off-road vehicle performance.

Because Plug-in Hybrid Electric Vehicles (PHEVs) substitute electrical power from the utility grid for fuel, they have the potential to reduce petroleum use significantly. However, adoption of PHEVs has been hindered by expensive, low-energy batteries. Recent improvements in Li-ion batteries and hybrid control have addressed battery-related issues and have brought PHEVs within reach. The FreedomCAR Office of Vehicle Technology has a program that studies the potential benefit of PHEVs. This program also attempts to clarify and refine the requirements for PHEV components. Because the battery appears to be the main technical barrier, both from a performance and cost perspective, the main efforts have been focused on that component. Working with FreedomCAR energy storage and vehicle experts, Argonne National Laboratory (Argonne) researchers have developed a process to define the requirements of energy storage systems for plug-in applications.

Hybrid Electric Vehicle (HEV) owners have reported significantly lower fuel economy than the published estimates. Under on-road driving conditions, vehicle acceleration, speed, and stop time differ from those on the normalized test procedures. To explain the sensitivity, several vehicles, both conventional and hybrid electric, were tested at Argonne National Laboratory. The tests demonstrated that the fuel economy of Prius MY04 was more sensitive to drive-cycle variations. However, because of the difficulty in instrumenting every component, an in-depth analysis and quantification of the reasons behind the higher sensitivity was not possible. In this paper, we will use validated models of the tested vehicles and reproduce the trends observed during testing. Using PSAT, the FreedomCAR vehicle simulation tool, we will quantify the impact of the main component parameters, including component efficiency and regenerative braking.

Developed by the U.S. Environmental Protection Agency (EPA), the Multi-scale mOtor Vehicle Emission Simulator (MOVES) is used to estimate inventories and projections through 2050 at the county or national level for energy consumption, nitrous oxide (N2O), and methane (CH4) from highway vehicles. To simulate a large number of vehicles and fleets on numerous driving cycles, EPA developed a binning technique characterizing the energy rate for varying Vehicle Specific Power (VSP) under predefined vehicle speed ranges. The methodology is based upon the assumption that the vehicle behaves the same way for a predefined vehicle speed and power demand. While this has been validated for conventional vehicles, it has not been for advanced vehicle powertrains, including hybrid electric vehicles (HEVs) where the engine can be ON or OFF depending upon the battery State-of-Charge (SOC).

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).

Argonne National Laboratory (Argonne) and Idaho National Laboratory (INL), working with the FreedomCAR and Fuels Partnership, lead activities in vehicle dynamometer and fleet testing as well as in modeling activities. By using Argonne’s Advanced Powertrain Research Facility (APRF), the General Motors (GM) Tahoe 2-mode was instrumented and tested in the 4-wheel-drive test facility. Measurements included both sensors and controller area network (CAN) messages. In this paper, we describe the vehicle instrumentation as well as the test results. On the basis of the analysis performed, we discuss the vehicle model developed in Argonne’s vehicle simulation tool, the Powertrain System Analysis Toolkit (PSAT), and its comparison with test data. Finally, on-road vehicle data, performed by INL, is discussed and compared with the dynamometer results.

Rising fuel costs, increased regulations, and heightened customer sensitivity to energy efficiency has prompted the evaluation of numerous powertrain technology improvements to introduce into production. The actual impact of such technologies can differ broadly, depending on the technology or application. To evaluate the fuel consumption impact, various baseline vehicles have been created and simulated by using Argonne National Laboratory's vehicle modeling and simulation tool, the Powertrain Systems Analysis Toolkit (PSAT). This paper provides a quantitative evaluation of several technologies or combinations of technologies. First, we assess the impact of single technologies, including vehicle/chassis characteristics, such as weight, aerodynamics, or rolling resistance. Next, we consider advanced powertrain technologies, ranging from dieselization to transmissions with a higher gear number, and hybridization.

In this paper a yaw stability control algorithm along with an emergency roll control strategy have been developed. The yaw stability controller and emergency roll controller were both developed using linear two degree-of-freedom vehicle models. The yaw stability controller is based on Lyapunov stability criteria and uses vehicle lateral acceleration and yaw rate measurements to calculate the corrective yaw moment required to stabilize the vehicle yaw motion. The corrective yaw moment is then applied by means of a differential braking strategy in which one wheel is selected to be braked with appropriate brake torque applied. The emergency roll control strategy is based on a rollover coefficient related to vehicle static stability factor. The emergency roll control strategy utilizes vehicle lateral acceleration measurements to calculate the roll coefficient. If the roll coefficient exceeds some predetermined threshold value the emergency roll control strategy will deploy.

Rear-end crashes involving heavy trucks occur with sufficient frequency that they are a cause of concern within regulatory agencies. In 2006, there were approximately 23,500 rear-end crashes involving heavy trucks which resulted in 135 fatalities. As part of the Federal Motor Carrier Safety Administration's (FMCSA) goal of reducing the overall number of truck crashes, the Enhanced Rear Signaling (ERS) for Heavy Trucks project was developed to investigate methods to reduce or mitigate those crashes where a heavy truck has been struck from behind by another vehicle. Researchers also utilized what had been learned in the rear-end crash avoidance work with light vehicles that was conducted by the National Highway Traffic Safety Administration (NHTSA) with Virginia Tech Transportation Institute (VTTI) serving as the prime research organization. ERS crash countermeasures investigated included passive conspicuity markings, visual signals, and auditory signals.

This paper analyzes fuel economy benefits of direct hydrogen and gasoline reformer fuel cell vehicles, with special focus on cold-start impacts on these fuel cell based vehicles. Comparing several existing influential studies reveals that the most probable estimates from these studies differ greatly on the implied benefits of both types of fuel cell vehicles at the tank-to-wheel level (vehicle-powertrain efficiency and/or specific power), leading to great uncertainties in estimating well-to-wheel fuel energy and/or greenhouse gas (GHG) emission reduction potentials. This paper first addresses methodological issues to influence the outcome of these analyses. With one exception, we find that these studies consistently ignore cold-start and warm-up issues, which play important roles in determining both energy penalties and start-up time of fuel cell vehicles. To better understand cold-start and warm-up behavior, this paper examines approaches and results based on two available U.S.

This study involves the battery requirements for a fuel cell-powered hybrid electric vehicle. The performances of the vehicle [a 3200-lb (1455-kg) sedan], the fuel cell, and the battery were evaluated in a vehicle simulation. Most of the attention was given to the design and performance of the battery, a lithium-ion, manganese spinel-graphite system of 75-kW power to be used with a 50-kW fuel cell. The total power performance of the system was excellent at the full operating temperatures of the fuel cell and battery. The battery cycling duty is very moderate, as regenerative braking for the Federal Urban Driving Schedule and the Highway Fuel Economy Test cycles can do all charging of the battery. Cold start-up at 20°C is straightforward, with full power available immediately.