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This paper describes a method to estimate the engine stop position using any production style crank position sensor, while accounting for possible engine rock-back. The approach is based on modeling the engine speed state, achieving robustness and ease of calibration by adapting the rubbing friction model component during the first part of engine coast-down, followed by open-loop modeling when the engine speed has dropped below the sensor signal validity threshold.

This paper presents production Engine Management System algorithms for Estimation and Control of Turbocharged engines with the following qualities; 1) Model based ensuring applicability at all ambient conditions, 2) Does not require Turbine data for calibration 3) Estimation logic form allows reuse for control applying predictive values for response and stability 4) Applies to all Waste-Gate types; passive and active, pneumatic and electrical, 5) Does not require Waste-Gate position measurement 5) Applies to engines with Variable Geometry Turbine.

It is rare for a single technology to have the power to dramatically influence almost every major industry in the world. Nanotechnology falls into this category and offers fundamentally new capabilities to architect a broad array of novel materials, composites and structures on a molecular scale. This technology has the potential to drastically re-define the methods used for developing lighter, stronger, and high-performance structures and processes with unique and non-traditional properties. This paper focuses on some of the automotive applications for nanotechnology and showcases a few of them that are believed to have the highest probability of success in this highly competitive industry. No discussion of nanotechnology is complete without touching upon its health and environmental implications.

In today's dynamic automotive environment, reducing the lead-time to introduce new product technologies to the market place can be a key competitive advantage. Employing proactive risk reduction techniques to define key product and process relationships is essential to enhance the production worthiness of a design while it is still in the advanced development phase of the program. This paper describes how Delphi Powertrain Systems applied the Shainin proactive risk reduction methodology in advanced product development to focus resources on understanding and mitigating the risk associated with the development of a new Delphi ammonia sensor. Organizational and technical strategies to accelerate profound knowledge capture, along with corresponding test results, are presented and discussed.