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A new realistic motion control algorithm for digital human models is presented in this paper based on the principle of effort minimization. The proposed algorithm is developed through an innovative mathematical model to make the applications more flexible and more global, especially for the visualization of human motions in automotive assembly operations. The central idea of this unique model is to interpret the solution of the homogeneous Lagrange equation for a mannequin as the origin of dynamic motion. Furthermore, a digital human possesses about 42 joints over the main body except the head, fingers and toes, and offers a large room of kinematic redundancy. We have found 14 new 3-D independent motion markers assigned over the human body to constitute a Cartesian coordinate system, under which a minimum-effort based dynamic control scheme is developed using a state-feedback linearization procedure.

With the increasing emphasis on Systems Engineering, there is a need to ensure that Electrical/Electronic (E/E) Systems Endurance Testing of vehicles, in a real world environment, prior to Production Launch, is performed in a manner and at a technological level that is commensurate with the high level of electronics and computers in contemporary vehicles. Additionally, validating the design and performance of individual standalone electronic systems and modules “on the bench” does not guarantee that all the permutations and combinations of real-world hardware, software, and driving conditions are taken into account. Traditional Proving Ground (PG) vehicle testing focuses mainly on powertrain durability testing, with only a simple checklist being used by the PG drivers as a reminder to cycle some of the electrical components such as the power window switches, turn signals, etc.

The Hybrid III family of dummies is used to estimate the response of an occupant during a crash. One recent area of interest is the response of the neck during air bag loading. The biomechanical response of the Hybrid III dummy's neck was based on inertial loading during crash events, when the dummy is restrained by a seat belt and/or seat back. Contact loading resulting from an air bag was not considered when the Hybrid III dummy was designed. This paper considers the effect of air bag loading on the 5th percentile female Hybrid III dummies. The response of the neck is presented in comparison to currently accepted biomechanical corridors. The Hybrid III dummy neck was designed with primary emphasis on appropriate flexion and extension responses using the corridors proposed by Mertz and Patrick. They formulated the mechanical performance requirements of the neck as the relationship between the moment at the occipital condyles and the rotation of the head relative to the torso.

This paper utilizes GPS tracked multiday travel activities to estimate the temporal distribution of electricity loads and assess battery electric vehicle (BEV) grid impacts at a significant market penetration level. The BEV load and non-PEV load vary by time of the day and day of the week. We consider two charging preferences: home priority assumes BEV drivers prefer charging at home and would not charge at public charging stations unless the state of charge (SOC) of the battery is not sufficient to cover the way back to home; and charging priority does not require drivers to defer charging to home and assumes drivers will utilize the first available charging opportunity. Both home and charging priority scenarios show an evening peak demand. Charging priority scenario also shows a morning peak on weekdays, possibly due to workplace charging.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

We report a chemical sensing technology composed of engineered bioluminescent bacteria placed on an integrated microluminometer. The bacteria have been engineered to luminesce when the targeted compound is metabolized, while the microluminometer detects, processes, and then reports the magnitude of this optical signal. In this work we report our progress in the development of these biosensors and present data from our prototypes.

We report a chemical sensing technology composed of engineered bioluminescent bacteria placed on an integrated microluminometer. The bacteria have been engineered to luminesce when the targeted compound is metabolized, while the microluminometer detects, processes, and then reports the magnitude of this optical signal. In this work we report our progress in the development of these biosensors and present data from our early prototypes.

The durability of fuel tank straps is essential for vehicle safety. Extensive physical tests are conducted to verify designs for durability. Due to the complexity of the loads and the fuel-to-tank interaction, computer-aided-engineering (CAE) simulation has had limited application in this area. This paper presents a CAE method for fuel tank strap durability prediction. It discusses the analytical loads, modeling of fuel-to-tank interaction, dynamic analysis methods, and fatigue analysis methods. Analysis results are compared to physical test results. This method can be used in either a fuel-tank-system model or a full vehicle model. It can give directional design guidance for fuel tank strap durability in the early stages of product development to reduce vehicle development costs.

This paper contains a review of methods for deriving risk curves from biomechanical data obtained from impact experiments on human surrogates. It covers many of the problems and pitfalls of obtaining realistic human risk curves from impact experiments. The strength and weakness of both parametric and non-parametric methods are evaluated. The limitations of standard analysis of censored impact test data are presented. Methods are given for determining risk curves from both doubly censored data and data obtained from impacts to body regions in which there are more than one mechanism of injury. A detailed set of examples is presented in which different experimental data are analyzed using the Consistent Threshold method and the logistic approach. Finally risk curves for published data are presented for the femur, head, thorax, and neck.

In internal combustion engines, liquid fuel injection is one of the most prevalent means of fuel delivery and air-fuel mixture preparation. The behavior of the fuel spray and wall film is a key factor in determining air-fuel mixing and hence combustion and emissions. A comprehensive model for the liquid fuel spray has been developed in conjunction with the one-dimensional gas flow code WAVE. The model includes droplet dynamics and evaporation, spray-wall impingement, wall film dynamics and evaporation. The fuel injector can be placed in the manifold, inlet port or cylinder. Liquid fuel droplets are injected with a prescribed size distribution, and their subsequent movement and vaporization are modeled via the discrete particle approach, frequently used in multi-dimensional CFD codes. This approach ensures conservation of mass, momentum and energy between the gas and liquid phases.

Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) networks within the Intelligent Transportation System (ITS) lead to safety and mobility improvements in vehicle road traffic. This paper presents case studies that support the realization of the ITS architecture as an evolutionary process, beginning with driver information systems for enhancing feedback to the users, semi-autonomous control systems for improved vehicle system management, and fully autonomous control for improving vehicle cooperation and management. The paper will also demonstrate how the automotive, telecom, and data and service providers are working together to develop new ITS technologies.

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

It is rare for an attempt towards optimization at the fleet-level when consideration is given to the sheer number of seemingly unpredictable interactions among vehicles and infrastructure in congested urban areas. To close the gap, we introduce a simulation based framework to explore the impact of speed synchronization on fuel economy improvement for fleets in traffic. The framework consists of traffic and vehicle modules. The traffic module is used to simulate driver behavior in urban traffic; and the vehicle module is employed to estimate fuel economy. Driving schedule is the linkage between these two modules. To explore the impact, a connected vehicle technology sharing vehicle speed information is used for better fuel economy of a fleet including six vehicles. In all scenarios analyzed, the leading vehicle operates under the EPA Urban Dynamometer Driving Schedule (UDDS), while the other five vehicles follow the leader consecutively.

The pulse severities from various vehicle impact tests need to be assessed during the impact structure development and targeting stage to assure that the occupants can meet the injury criteria as required. The conventional method using TTZV (time to zero velocity), TDC (total dynamic crush), and G1/G2 (two stage averaged pulse) is often unable to give a quick and clear answer to the question being raised. A simple numerical tool is developed here to assess the pulse severity with a single parameter in which the severity is expressed as the amount of chest travel under a certain target restraint curve or chest A-D curve. The tool is applied to several front impact vehicle pulses to show the effectiveness. The new method developed here can be used to assess the pulse severity in an easy and objective way along with conventional parameters.

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving.

Exhaust durability is an important measure of quality, which can be predicted using CAE with accurate mount loads. This paper proposes an innovative method to calculate these loads from measured mount accelerations. A Chrysler vehicle was instrumented with accelerometers at both ends of its four exhaust mounts. The vehicle was tested at various durability routes or events at DaimlerChrysler Proving Grounds. These measured accelerations were integrated to obtain their velocities and displacements. The differences in velocities and displacements at each mount were multiplied by its damping and stiffness rates to obtain the mount load. The calculation was conducted for all three translational directions and for all events. The calculated mount loads are shown within reasonable range. Along with CAE, it is suggested to explore this method for exhaust durability development.

The Young's modulus, hardness, and fracture toughness of barium titanate dielectric ceramics in three commercially available multilayer capacitors (MLCs) were measured in-situ using indentation and a mechanical properties microprobe. The three MLCs were equivalent in size (0805), capacitance (0.1 μF) and dielectric type (X7R). The Young's modulus and hardness of the dielectric ceramics in the three MLCs were similar, while there were statistically significant differences in their fracture toughnesses. The results provide insight into the assessment of MLC mechanical reliability, and show that equivalent electrical MLC rating is not necessarily a guarantee that the dielectric ceramics in them will exhibit equivalent mechanical performance.

A new multi-layer co-extruded in-color Ionomer film is developed to provide an alternative decoration process to replace paint on Dodge Neon Fascias. The Ionomer film provides a high-gloss “class-A” surface in both non-metallic and metallic colors that match the car body paint finish. Using the Ionomer film to decorate fascias reduces cost; eliminates VOCs; increases manufacturing flexibility and improves performance (weatherability and durability). The molding process consists of thermoforming a film blank and injection molding Polypropylene or TPO behind the film. The paper will include the background, the benefits, the technology development objectives, the film materials development, tooling optimization, film fascia processing (co-extrusion; thermoforming and injection molding) and validation testing of the film.

Automobiles of the future will be forced to travel further on a tank of fuel while discharging lower levels of pollutants. Currently, the United States uses in excess of 18 million barrels of petroleum per day. Sixty-six percent is used in the transportation of people and goods. Highway vehicles currently account for just under two-thirds of the nation's gasoline consumption, and about one-third of the total United States energy usage [1] while contributing a significant amount to the annual U.S. air pollutant burden. In 1997, 57.5% of the carbon monoxide, 29.8% of the nitrogen oxides, 27.2% of the volatile organic compounds, and 23.8% of the carbon dioxide came from highway vehicles [2] The U.S. government has supported R&D pertinent to highway vehicles since the early 1960's, to mitigate these problems.

This study will analyze existing procedures and commercially available testing equipment for low temperature impact testing of plastic materials. The results of this analysis will be used to identify continuous improvement opportunities and develop recommended practices for low temperature impact testing to support ongoing efforts to meet related durability and performance needs of automotive components.