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This paper includes analysis results for the control strategy of the Peugeot 3008 Hybrid4, a diesel-electric hybrid vehicle, under different thermal conditions. The analysis was based on testing results obtained under the different thermal conditions in the Advanced Powertrain Research Facility (APRF) at Argonne National Laboratory (ANL). The objectives were to determine the principal concepts of the control strategy for the vehicle at a supervisory level, and to understand the overall system behavior based on the concepts. Control principles for complex systems are generally designed to maximize the performance, and it is a serious challenge to determine these principles without detailed information about the systems. By analyzing the test results obtained in various driving conditions with the Peugeot 3008 Hybrid4, we tried to figure out the supervisory control strategy.

Preliminary work was conducted in the casting of magnesium using the lost foam casting process. The lost foam or expendable pattern casting (EPC) process is capable of making extremely complicated part shapes at acceptable soundness levels and with low manufacturing costs. Standard test shapes were used to determine the ability of the magnesium to fill the mold and to assess the types of defects encountered. This paper will briefly explain how this project evolved including the developmental strategies formed, the products selected, the casting trials performed, and the casting results.

Previous studies and on-road driving by consumers have shown that Hybrid Electric Vehicle fuel economy is very dependent on driver demand in both vehicle speed and vehicle acceleration [1]. The emerging technology of Plug-In Hybrid Vehicles (PHEV) may prove to also be more sensitivity to aggressive driver demand as compared to conventional internal combustion engine vehicles. This is due to the exceptional ability of the PHEV to minimize fuel consumption at mid to low power levels by the significant use of electric propulsion which enables engine downsizing. As vehicle speed and acceleration increase so does the power demand on the powertrain. The fuel consumption is directly affected by this increase in power demand level. To examine the fuel consumption impact of changing driver characteristics on PHEV’s, testing is conducted on two vehicles (parallel PHEV and power-split PHEV) on a four wheel chassis dynamometer at Argonne’s Advanced Powertrain Research Facility.

The Society of Automotive Engineers Fatigue Design & Evaluation Committee [SAE FD&E] is actively working on a total life project for weldments, in which the welding residual stress is a key contributor to an accurate assessment of fatigue life. Physics-based welding process simulation and various types of residual stress measurements were pursued to provide a representation of the residual stress field at the failure location in the fatigue samples. A well-controlled and documented robotic welding process was used for all sample fabrications to provide accurate inputs for the welding simulations. One destructive (contour method) residual stress measurement and several non-destructive residual stress measurements-surface X-ray diffraction (XRD), energy dispersive X-ray diffraction (EDXRD), and neutron diffraction (ND)-were performed on the same or similarly welded samples.

A sustainable activity is one that is economically attractive, environmentally friendly and provides a beneficial service to society in a safe and responsible manner. Having a sustainable operation is a target that today’s industries are striving to attain. The automotive industry and its products are major users of natural resources and a source of greenhouse emissions. In order to reduce its energy consumption and greenhouse emissions the industry is using more lightweighting materials in manufacturing its products. These materials include polymers, composites, aluminum and magnesium. The increased interest in hybrid vehicles will increase the need for new materials such as lithium, cobalt and nickel. At the same time, regulations are calling for recycling more of the obsolete vehicles. Replacing the steel, which is recyclable, with lighter materials will result in a reduction in the recycling rate of vehicles unless the lightweighting materials are recycled.

This work details two approaches for evaluating transmission warming technology: experimental dynamometer testing and development of a simplified transmission efficiency model to quantify effects under varied real world ambient and driving conditions. Two vehicles were used for this investigation: a 2013 Ford Taurus and a highly instrumented 2011 Ford Fusion (Taurus and Fusion). The Taurus included a production transmission warming system and was tested over hot and cold ambient temperatures with the transmission warming system enabled and disabled. A robot driver was used to minimize driver variability and increase repeatability. Additionally the instrumented Fusion was tested cold and with the transmission pre-heated prior to completing the test cycles. These data were used to develop a simplified thermally responsive transmission model to estimate effects of transmission warming in real world conditions.

A fully instrumented Tesla Model 3 was used to collect thousands of hours of real-world automated driving data, encompassing both Autopilot and Full Self-Driving modes. This comprehensive dataset included vehicle operational parameters from the data busses, capturing details such as powertrain performance, energy consumption, and the control of advanced driver assistance systems (ADAS). Additionally, interactions with the surrounding traffic were recorded using a perception kit developed in-house equipped with LIDAR and a 360-degree camera system. We collected the data as part of a larger program to assess energy-efficient driving behavior of production connected and automated vehicles. One important aspect of characterizing the test vehicle is predicting its car-following behavior. Using both uncontrolled on-road tests and dedicated tests with a lead car performing set speed maneuvers, we tuned conventional adaptive cruise control (ACC) equations to fit the vehicle’s behavior.