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A key to shortening the design cycle is to shorten the initial or conceptual design phase. An enabling technology towards this goal is an architecture called the Design Support System (DSS), which is based on the virtual prototype concept. The DSS combines knowledge with hardware and software into a system that is a model for the design process. It produces a virtual prototype of the design and maintains an intelligent design document, which is automatically updated during the design process. A design domain dependent version for automotive design, known as “Automobile Design Support System” (AutoDSS) was developed in the CADTECH Research Lab at the University of Washington.

Measuring the displacements in vehicle seat suspensions and the displacements the seat has to absorb may assist vehicle seat designers in better designing seats to absorb vibrations. Low frequency seat displacement is important in seat design to identify end-stop events and higher frequency shorter displacements are also important since seat components can be optimized to absorb these smaller displacements. Displacements can be directly measured with special instruments, but it would be less complicated if simple, compact accelerometers could be used to measure the seat displacements. This paper compares accelerometer-derived displacement measurements to known displacements derived from sinusoidal physics and field measured random displacements measured with potentiometers. Using known, controlled sinusoidal displacements, three lab-based experiments were conducted to determine how well accelerometers, using double integration, could measure displacements.

Rational design for fire safety necessarily includes consideration of risk tradeoffs that tend to reduce one risk but may increase another. Traditional engineering design criteria can be supplemented with important factors that rely on expertise from other disciplines. Engineering analysis may be able to address reduction in fire risk due to the introduction of new technology, but may not address the social costs associated with this new technology. For example, the resultant increase in vehicle cost may prevent some people from purchasing a vehicle (impacting individuals' lives), may reduce the number of vehicles sold (impacting manufacturers), and may reduce taxes collected (impacting the government). This must be weighed against decreased risk of property damage, injury, and fatality due to fire. In this paper, the methods of benefit-cost analysis from economics were applied to make this evaluation.

EcoCAR 2: Plugging in to the Future (EcoCAR) is North America's premier collegiate automotive engineering competition, challenging students with systems-level advanced powertrain design and integration. The three-year Advanced Vehicle Technology Competition (AVTC) series is organized by Argonne National Laboratory, headline sponsored by the U. S. Department of Energy (DOE) and General Motors (GM), and sponsored by more than 30 industry and government leaders. Fifteen university teams from across North America are challenged to reduce the environmental impact of a 2013 Chevrolet Malibu by redesigning the vehicle powertrain without compromising performance, safety, or consumer acceptability. During the three-year program, EcoCAR teams follow a real-world Vehicle Development Process (VDP) modeled after GM's own VDP. The EcoCAR 2 VDP serves as a roadmap for the engineering process of designing, building and refining advanced technology vehicles.

The University of Washington EcoCAR2 team (UWEC2) is currently in the process of building a Plug-in Hybrid Electric Vehicle (PHEV) for the EcoCAR2 Challenge. This competition challenges 15 universities across North America to reduce the environmental impact of a 2013 Chevrolet Malibu without compromising consumer acceptability. In order to be competitive in EcoCAR2, grid electricity is relied on heavily and the use of the Utility Factor method presented in SAE J2841 - Utility Factor Definitions must be used to compare emissions and consumption results with traditional vehicle results. Powertrain simulation in Autonomie was performed to explore many different hybrid architectures. The simulation results were normalized using the Utility Factor method to reach final architecture and component decisions.