Search Results

The development of the WorldSID 50th percentile male dummy was initiated in 1997 by the International Organization for Standardization (ISO/SC12/TC22/WG5) with the objective of developing a more biofidelic side impact dummy and supporting the adoption of a harmonized dummy into regulations. More than 45 organizations from all around the world have contributed to this effort including governmental agencies, research institutes, car manufacturers and dummy manufacturers. The first production version of the WorldSID 50th male dummy was released in March 2004 and demonstrated an improved biofidelity over existing side impact dummies. Full-scale vehicle tests covering a wide range of side impact test procedures were performed worldwide with the WorldSID dummy. However, the vehicle safety performance could not be assessed due to lack of injury risk curves for this dummy. The development of these curves was initiated in 2004 within the framework of ISO/SC12/TC22/WG6 (Injury criteria).

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Efforts by vehicle manufacturers to reduce road testing have resulted in an increased reliance on the simulation methods for loads measurement and validation, including increased emphasis on methods to characterize and digitally represent test road inputs. Accurate terrain models are especially important in the case of large dynamic road inputs, and for evaluation of vehicle suspension loads and durability. In contrast to direct terrain topology measurement, methods to estimate test road input using only vehicle suspension measurements and a tire dynamic model will be presented. Applications of terrain models for generic simulation and testing will also be discussed.

Competitive pressures, globalization of markets, and integration of new materials and technologies into heavy vehicle suspension systems have increased demand for durability validation of new designs. Traditional Proving Ground and on-road testing for suspension development have the limitations of extremely long test times, poor repeatability and the corresponding difficultly in getting good engineering level data on failures. This test approach requires a complete vehicle driven continuously over severe Proving Ground events for extended periods. Such tests are not only time consuming but also costly in terms of equipment, maintenance, personnel, and fuel. Ideally multiple samples must be tested to accumulate equivalent millions of kilometers of operation in highly damaging environments.

A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification. The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage. Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations. As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage.

A unified approach to collision warning due to in-lane and neighboring traffic is presented. It is based on the concept of velocity obstacles, and is designed to alert the driver of a potential front collision and against attempting a dangerous lane change maneuver. The velocity obstacle represents the set of the host velocities that would result in collision with the respective static or moving vehicle. Potential collisions are simply determined when the velocity vector of the host vehicle penetrates the velocity obstacle of a neighboring vehicle. The generality of the velocity obstacle and its simplicity make it an attractive alternative to competing warning algorithms, and a powerful tool for generating collision avoidance maneuvers. The velocity obstacle-based warning algorithm was successfully tested in simulations using real sensor data collected during the Automotive Collision Avoidance System Field Operational Test (ACAS FOT) [10].

The focus of this research effort was to develop a technique to measure the cyclic variability of the mass injected by fuel injectors. Successful implementation of the measurement technique introduced in this paper can be used to evaluate injectors and improve their designs. More consistent and precise fuel injectors have the potential to improve fuel efficiency, engine performance, and reduce emissions. The experiments for this study were conducted at the Michigan State University Automotive Research Experiment Station. The setup consists of a fuel supply vessel pressurized by compressed nitrogen, a Dantec laser Doppler anemometry (LDA) system to measure the centerline velocity of fuel, a quartz tube for optical access, and a Cosworth IC 5460 to control the injector. The detector on the LDA system is capable of resolving Doppler bursts as short as 6μs, depending on the level of seeding, thus giving a detailed time/velocity profile.

With Statistical Energy Analysis (SEA) proven to be a powerful tool for airborne noise analysis, the capability of predicting the exterior sound field around a vehicle at high frequencies (the load case in the SEA analysis) is of particular interest to OEMs and suppliers. This paper employs the High Frequency Boundary Element Method (HFBEM) to simulate the scattered exterior sound field distribution due to a monopole source. It is shown that the proposed method is able to efficiently predict the spatial and frequency averaged sound pressure levels reasonably well up to 10 kHz, even at points in the near field of the vehicle body.

The sound field in a vehicle is one of the most complex environments being a mixture of multiple, correlated and uncorrelated sound sources. The simulation of vehicle interior sound has traditionally been produced by combining multiple test results where the influence of one source is enhanced while the other sources are suppressed, such as towing the vehicle on a rough surface for road noise, or measuring noise in a wind tunnel. Such methods are costly and provide inherent inaccuracies due to source contamination and lack of synchronization between sources. In addition they preclude the addition of analytical predictions into the simulation. The authors propose an alternative approach in which the component sounds are decomposed or separated from a single operating measurement and which provide the basis for accurate sound synthesis.

A set of functions for characterizing the mechanical properties of a steering “short gear” is described. They cover the kinematic, stiffness, assist, and friction performance of a power assisted (or manual) steering gear from the input shaft to the inner ends of the tie rods. Their use in describing the performance of a generalized steering gear is described. They have particular application to describing the steering feel performance of a vehicle. They can be used to specify the steering subsystem performance for desired steering feel for a given vehicle. They can also be used for experimental characterization of steering subsystems, can be used in vehicle dynamics simulations, and can be synthesized from a set of vehicle level performance targets. Along with their description, their use in simulation and methods to synthesize their values are described.

The CY2000 cornerstone goal of the Partnership for a New Generation of Vehicles (PNGV) is the demonstration in CY 2000 of a 5-passenger vehicle with fuel economy of up 80 mpg (3 l/100km). As a PNGV partner, GM will demonstrate a technology-demonstration concept vehicle, the Precept, having a lightweight aluminum-intensive body, hybrid-electric propulsion system and a portfolio of efficient vehicle technologies. This paper describes: 1) the strategy for the vehicle design including mass requirements, 2) the selection of dual axle application of regenerative braking and electric traction, and 3) the complementary perspective on energy management strategy. This paper outlines information developed through systems analysis that drove technology selections. The systems analyses relied on vehicle simulation models to estimate fuel economy associated with technology selections. Modeling analyses included consideration of both federal test requirements and more severe driving situations.

Sound absorption is one way to control noise in automotive passenger compartments. Fibrous or porous materials absorb sound in a cavity by dissipating energy associated with a propagating sound wave. The objective of this study was to evaluate the acoustic performance of a cotton fiber absorbing material in comparison to a new polypropylene fibrous material, called ECOSORB ®. The acoustical evaluation was done using measurements of material properties along with sound pressure level from road testing of a fully-assembled vehicle. The new polypropylene fibrous material showed significant advantages over the cotton fiber materials in material properties testing and also in-vehicle measurements. In addition to the performance benefits, the polypropylene absorber provided weight savings over the cotton fiber material.

The wheel force transducer has been proven to be a cost and time effective tool for vehicle load data acquisition and simulation testing. The accuracy of wheel force transducers is typically given in terms of a static calibration, or a quasi-static system generated load case. The actual use of a wheel force transducer often involves high speed rotation, varying camber and steer of the tire on the vehicle, and other dynamic and rim related variations which deviate from the standard laboratory calibration. The Flat-Trac proves to be an excellent tool in the design process and evaluation of the wheel force transducer because it accurately controls and simulates the loading of a rotating wheel assembly. Through Flat-Trac System testing, issues that are critical to the use, accuracy, and integrity of data acquired through a wheel force transducer can be evaluated.

A major challenge facing the vehicle simulation test laboratory is correlating (and thereby validating) the simulated “test track” with the In-service environment. This simulation is key to the use of data for durability analysis from the integrated design and testing engineering process. Presented here is an approach to integrating road simulation test and fatigue life analysis that produces needed results for test, design and analysis engineers. The core of the analysis is a fatigue-based “rig-to-road” comparison for an on-highway vehicle using strain-time data acquired at fatigue sensitive locations. The cyclic and fatigue damaging content of the field and simulation profiles are compared quantitatively for purposes of validating the laboratory lest, and to illustrate a method of reporting this validation to design and analysis engineers.

This study assesses the understanding and recognition, by U.S. drivers, of the 25 automotive ISO symbols specified in SAE Standard J1048. A two-part survey was administered to 505 volunteers at a Secretary of State's office located in a Detroit suburb. Percentage results for symbol understanding indicated low levels of understanding for many symbols; percentage results for symbol recognition were generally much higher for all symbols. The effects of gender, age, and education level on the percentage results are summarized.