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A new index for evaluating load path dispersion is proposed, using a structural load path analysis method based on the concept of U* , which expresses the connection strength between a load point and an arbitrary point within the structure enables the evaluation of the load path dispersion within the structure by statistical means such as histograms and standard deviations. Presenter Tadashi Naito, Honda R&D Co., Ltd.

When vehicles share certain information wirelessly via Dedicated Short Range Communications (DSRC), they enable a new layer of electronic vehicle safety that, when needed, can generate warnings to drivers and even initiate automatic preventive actions. Vehicle location and velocity provided by Global Navigation Systems (GNSS), including GPS, are key in allowing vehicle path estimation. GNSS is effective in accurately determining a vehicle's location coordinates in most driving environments, but its performance suffers from obstructions in dense urban environments. To combat this, augmentations to GNSS are being contemplated and tested. This testing has been typically done using a reference GNSS system complimented by expensive military-grade inertial sensors, which can still fail to provide adequate reference performance in certain environments.

Given the fast changing market demands, the growing complexity of features, the shorter time to market, and the design/development constraints, the need for efficient and effective verification and validation methods are becoming critical for vehicle manufacturers and suppliers. One such example is fault-tree analysis. While fault-tree analysis is an important hazard analysis/verification activity, the current process of translating design details (e.g., system level and software level) is manual. Current experience indicates that fault tree analysis involves both creative deductive thinking and more mechanical steps, which typically involve instantiating gates and events in fault trees following fixed patterns. Specifically for software fault tree analysis, a number of the development steps typically involve instantiating fixed patterns of gates and events based upon the structure of the code. In this work, we investigate a methodology to translate software programs to fault trees.

Vehicle electrification is shaping the future of automotive mobility in terms of automotive power and propulsion. The market for New Energy Vehicles (HEV/PHEV/REEV/EV) as well as clean vehicle technologies is expected to grow steadily driven by government regulations mandating increased fuel economy and lower emissions. The fastest growth in this market will be in Asia Pacific, most notably China. The Chinese government has made its intentions clear on how important it considers the development and consumer purchase of hybrid and electric vehicles. The mandate is that by year 2012, vehicle manufacturers produce at least 500,000 units (or 5%) per year of their total output as hybrid and/or electric. All Chinese vehicle manufacturers must have at least one HEV or EV model in the market by the same year. Thus far China has invested over US$3.5 billion to stimulate the production of NEVs and the necessary infrastructure to support them.