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This paper presents a feedback linearization control technique as applied to a Roll Simulator. The purpose of the Roll Simulator is to reproduce in-field rollovers of ROVs and study occupant kinematics in a laboratory setting. For a system with known parameters, non-linear dynamics and trajectories, the feedback linearization algorithm cancels out the non-linearities such that the closed-loop dynamics behave in a linear fashion. The control inputs are computed values that are needed to attain certain desired motions. The computed values are a form of inverse dynamics or feed-forward calculation. With increasing system eigenvalue, the controller exhibits greater response time. This, however, puts a greater demand on the translational actuator. The controller also demonstrates that it is able to compensate for and reject a disturbance in force level.

This paper documents the vehicle response of a tractor-semitrailer following a sudden air loss (Blowout) in a steer axle tire while traveling at highway speeds. The study seeks to compare full-scale test data to predicted response from detailed heavy truck computer vehicle dynamics simulation models. Full-scale testing of a tractor-semitrailer experiencing a sudden failure of a steer axle tire was conducted. Vehicle handling parameters were recorded by on-board computers leading up to and immediately following the sudden air loss. Inertial parameters (roll, yaw, pitch, and accelerations) were measured and recorded for the tractor and semitrailer, along with lateral and longitudinal speeds. Steering wheel angle was also recorded. These data are presented and also compared to the results of computer simulation models. The first simulation model, SImulation MOdel Non-linear (SIMON), is a vehicle dynamic simulation model within the Human Vehicle Environment (HVE) software environment.

Objectives. Examination of head injuries in the Pedestrian Crash Data Study (PCDS) indicates that many pedestrian head injuries are induced by a combination of head translation and rotation. The Simulated Injury Monitor (SIMon) is a computer algorithm that calculates both translational and rotational motion parameters relatable head injury. The objective of this study is to examine how effectively HIC and three SIMon correlates predict the presence of either their associated head injury or any serious head injury in pedestrian collisions. Methods. Ten reconstructions of actual pedestrian crashes documented by the PCDS were conducted using a combination of MADYMO simulations and experimental headform impacts. Linear accelerations of the head corresponding to a nine-accelerometer array were calculated within the MADYMO model's head simulation.

This paper presents the results of an in-depth study of the measurement of occupant kinematic response on the S-E-A Roll Simulator. This roll simulator was built to provide an accurate and repeatable test procedure for the evaluation of occupant protection and restraint systems during roll events within a variety of occupant compartments. In the present work this roll simulator was utilized for minimum-energy, or threshold type, rollover events of recreational off-highway vehicles (ROVs). Input profiles for these tests were obtained through a separate study involving autonomous full vehicle tests [1]. During simulated roll events anthropomorphic test device (ATD) responses were measured using on-board high speed video, an optical three-dimensional motion capture system (OCMS) and an array of string potentiometers.

A two-degree-of-freedom Roll Simulator has been developed to study the occupant kinematics of Recreational Off-Highway Vehicles (ROVs). To validate the roll simulator, test data was collected on a population of ROVs on the market today. J-turn maneuvers were performed to find the minimum energy limits required to tip up the vehicles. Two sets of tests were performed: for the first set, 10 vehicles were tested, where the motion was limited by safety outriggers to 10-15 degrees of roll; and for the second set, three of these vehicles were re-tested with outriggers removed and the vehicle motion allowed to reach 90 degrees of roll. These quarter-turn rollover tests were performed autonomously using an Automatic Steering Controller (ASC) and a Brake and Throttle Robot (BTR). Lateral and longitudinal accelerations as well as roll rate and roll angle were recorded for all tests.

The effectiveness of the Helmholtz resonator as a narrow band acoustic attenuator, particularly at low frequencies, makes it a highly desirable component in a wide variety of applications, including engine breathing systems. The present study investigates the influence of mean flow grazing over the neck of such a configuration on its acoustic performance both computationally and experimentally. Three-dimensional unsteady, turbulent, and compressible Navier-Stokes equations are solved by using the Pressure-Implicit-Splitting-of-Operators algorithm in STAR-CD to determine the time-dependent flow field. The introduction of mean flow in the main duct is shown to reduce the peak transmission loss and shift the fundamental resonance frequency to a higher value.

When developing a new engine control strategy, some of the important issues are cost, resource minimization, and quality improvement. This paper outlines how a model based approach was used to develop an engine control strategy for an Extended Range Electric Vehicle (EREV). The outlined approach allowed the development team to minimize the required number of experiments and to complete much of the control development and calibration before implementing the control strategy in the vehicle. It will be shown how models of different fidelity, from map-based models, to mean value models, to 1-D gas dynamics models were generated and used to develop the engine control system. The application of real time capable models for Hardware-in-the-Loop testing will also be shown.

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.

The EcoCAR Challenge team at The Ohio State University has designed an extended-range electric vehicle capable of 50 miles all-electric range via a 22 kWh lithium-ion battery pack, with range extension and limited parallel operation supplied by a 1.8 L dedicated E85 engine. This vehicle is designed to drastically reduce fuel consumption, while meeting Tier II Bin 5 emissions standards. This vehicle design is implemented in a GM crossover utility vehicle as part of the EcoCAR Challenge. This paper explains the implementation of the vehicle's control strategy in order to maintain high efficiency and improve drivability. The vehicle control strategy employs both distinct operating modes and an Equivalent Consumption Minimization Strategy (ECMS) to find the most efficient operating point. The ECMS strategy does an online search for the most efficient torque split in order to meet the driver's command.

Torsional stiffness properties were developed for both a 53-foot box trailer and a 28-foot flatbed control trailer based on experimental measurements. In order to study the effect of torsional stiffness on the dynamics of a heavy truck vehicle dynamics computer model, static maneuvers were conducted comparing different torsional stiffness values to the original rigid vehicle model. Stiffness properties were first developed for a truck tractor model. It was found that the incorporation of a torsional stiffness model had only a minor effect on the overall tractor response for steady-state maneuvers up to 0.4 g lateral acceleration. The effect of torsional stiffness was also studied for the trailer portion of the existing model.

In order to evaluate a human surrogate, the human and surrogate response must be defined. The purpose of this study was to evaluate the response of cadaver subjects to blunt impacts to the frontal bone, nasal bone and maxilla. Force-displacement corridors were developed based on the impact response of each region. Variation in the force-displacement response of the cadaver subjects due to the occurrence of fracture and fracture severity was demonstrated. Additionally, impacts were performed at matched locations using the Facial and Ocular CountermeasUre Safety (FOCUS) headform. The FOCUS headform is capable of measuring forces imposed onto facial structures using internal load cells. Based on the tests performed in this study, the nasal region of the FOCUS headform was found to be the most sensitive to impact location. Due to a wide range in geometrical characteristics, the nasal impact response varied significantly, resulting in wide corridors for human response.

Friction plays an important role in the deep drawing process. Previous research shows friction condition can be tailored by applying micro-textures on tooling surfaces. A friction model is proposed to reveal the mechanism of altering friction condition by configuring micro-texture. A discrete friction concept is proposed to improve drawability of sheet metal and demonstrates numerically on a non-symmetric geometry drawing process.

In 2007, a software model of a Roll Stability Control (RSC) system was developed based on test data for a Volvo tractor at NHTSA's Vehicle Research and Test Center (VRTC). This model was designed to simulate the RSC performance of a commercially available Electronic Stability Control (ESC) system. The RSC model was developed in Simulink and integrated with the available braking model (TruckSim) for the truck. The Simulink models were run in parallel with the vehicle dynamics model of a truck in TruckSim. The complete vehicle model including the RSC system model is used to simulate the behavior of the actual truck and determine the capability of the RSC system in preventing rollovers under different conditions. Several simulations were performed to study the behavior of the model developed and to compare its performance with that of an actual test vehicle equipped with RSC.

Validation was performed on an existing heavy truck vehicle dynamics computer model with roll stability control (RSC). The first stage in this validation was to compare the response of the simulated tractor to that of the experimental tractor. By looking at the steady-state gains of the tractor, adjustments were made to the model to more closely match the experimental results. These adjustments included suspension and steering compliances, as well as auxiliary roll moment modifications. Once the validation of the truck tractor was completed for the current configuration, the existing 53-foot box trailer model was added to the vehicle model. The next stage in experimental validation for the current tractor-trailer model was to incorporate suspension compliances and modify the auxiliary roll stiffness to more closely model the experimental response of the vehicle. The final validation stage was to implement some minor modifications to the existing RSC model.

This paper describes a method to evaluate vehicle stability and controllability when the vehicle operates in the nonlinear range of lateral dynamics. The method is applied to open-loop steering maneuvers as well as closed-loop path-following maneuvers. Although path-following maneuvers are more representative of real world driving intent, they are usually considered inappropriate for objective assessment because of repeatability and accuracy issues. The automated test driver (ATD) can perform path-following maneuvers accurately and with good repeatability. This paper discusses the usefulness of application of the automated test drivers and path-following maneuvers. The dynamic mode of instability is not directly obtained from measurable outputs such as yawrate and lateral acceleration as in open-loop maneuvers. A few metrics are defined to quantify deviation from desired or ideal behavior in terms of observed “unexpected” lateral force and moment.

This paper is a printed listing of public domain vehicle center-of-gravity (CG) location measurements conducted on behalf of the National Highway Traffic Safety Administration (NHTSA). This paper is an extension of the 1999 SAE paper titled “Measured Vehicle Inertia Parameters - NHTSA's Data Through November 1998” ( 1 ). The previous paper contained data for 496 vehicles. This paper includes data for 528 additional vehicles tested as part of NHTSA's New Car Assessment Program (NCAP) for year 2001 through year 2008 ( 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ). The previous data included center-of-gravity location and mass moments-of-inertia for nearly all of the entries. The NCAP involves only the CG location measurements; so the vehicles listed in this paper do not have inertia data. This paper provides a brief discussion of the entries provided in the tabular listings as well as the accuracy of CG height measurements.

A novel approach to control the output voltage of the generator on a hybrid electric vehicle is proposed in this paper. In addition to the voltage control, for safety reason, it is desirable to control the current of the generator when the machine is running. In order to control the current, the reference voltage is translated to reference current by an estimator. Then current convergence is ensured by controlling the excitation voltage. Thus the over-current is prevented in the system. The rate of convergence of the voltage tracking is discussed. Robustness of the control algorithm against parameter variation is also analyzed and compared with conventional approach. Simulation results show that the safety objective is achieved without sacrificing output performance of the generator.

Design charts which predict acoustic absorption of porous insulators were verified experimentally using the two-microphone technique to measure the normal incidence absorption coefficient of three glass fiber materials in two different arrangements - a single-layer sample and a single layer in front of an air space, each backed by a rigid termination. The specific flow resistivities of the materials ranged from 2,000 to 52,000 mks rayls/m. Experimentally determined absorption coefficients were in agreement with those predicted by the design charts. The results indicate that these charts could be a useful tool in designing sound absorbers for practical applications.

In this paper, we will present parametric results of performing dynamic analysis of layshaft gear trains typically used in automotive transmissions with emphasis on the vibratory response due to transmission error excitation. A three-dimensional multiple degrees of freedom lumped parameter dynamic model of a generic layshaft type geared rotor system (with three parallel rotating shafts coupled by two sets of gear pairs) has been formulated analytically. The model includes the effects of both rotational and translational displacements of each gears, and bounce and pitch motions of the counter-shaft. The natural frequencies and mode shapes are computed numerically by solving an eigenvalue problem derived from applying harmonic solutions to the equations of motion. The complete set of mode shapes are then used in forced response calculations based on the modal expansion method to predict gear accelerations, dynamic transmission errors, mesh force and bearing loads.

This paper presents an evaluation of a vehicle dynamics model intended to be used for the National Advanced Driving Simulator (NADS). Dynamic validation for high performance simulation is not merely a comparison between experimental and simulation plots. It involves strong insight of vehicle's subsystems mechanics, limitations of the mathematical formulations, and experimental predictions. Lateral, longitudinal, and ride dynamics are evaluated using field test data, and analytical diagnostics. The evaluation includes linear and non-linear range of vehicle dynamics response.