Gm Global Technolgoy Operations, Inc.

Jeffrey Morgan Alden

Daniel J Reaume

John Stilianos Agapiou

Soheil Samii

Pulak Bandyopadhyay

Chen Zhou

Fangming Gu

Eric A Steinhilper

Andrew R Camden

Patrick M Hilber

Matthew Allen Dzurka

Aloysius Anagonye

A method for optimizing inter-vehicle order and distance includes communicating vehicle characteristics representative of a first and at least one second vehicle as the first vehicle approaches the at least one second vehicle. Based on the vehicle characteristics, a position in a driving order of the first vehicle with respect to the at least one second vehicle is selected and executed. A real-time fuel economy is recorded as the vehicle in the trailing position moves from a maximum following distance to a minimum following distance from the vehicle in the lead position. Based on at least the recorded real-time fuel economy, an optimal inter-vehicle distance between the vehicles in the lead and trailing positions is selected and executed.

Method for optimizing inter-vehicle distance and equitably sharing fuel benefits in a vehicle platoon

A process for analyzing a sub-model associated with a full system model as often depicted as an influence diagram. The process includes defining the sub-model as a collection of entities where some entities are calculation entities and some are data entities. The process converts the calculation entities in the sub-model that depend on entities in the fall model outside of the sub-model to temporary data entities. Further, the process deletes any data entity in the sub-model from which any converted temporary data entity depends. The process also determines if there are any isolated cycles in the sub-model, and, if so, which of the entities in the isolated cycle will be an output entity.

Automatic reconfiguration of system sub-models for independent analysis

A multistage machining process includes a plurality of stations. Workpiece feature quality is predicted based on decomposition of the machining process into sources of variation, reticulation of the machining process into machining stations and error models that account for significant contributions to feature quality including from categorical sources of variation.

Predictive modeling of machining line variation

A method for providing a functional visualization of a spreadsheet. The method includes correlating spreadsheet cells with both data entities and calculation entities in an influence diagram, and then automatically updating the entities in the influence diagram in response to changes made to the spreadsheet, or automatically updating the spreadsheet in response to changes made to the entities in the influence diagram. The method includes identifying one or more cells in a spreadsheet as a data cell or a calculation cell, and then identifying corresponding data entities and calculation entities in the influence diagram. The entities in the influence diagram can have predetermined attributes (color, shape, images, etc.) depending on their function. Next, the method includes positioning the entities in the influence diagram by employing user interaction to configure the entities in a visually pleasing manner, or positioning the entities by employing an automatic design layout algorithm to determine the configuration of the entities. Once the equivalent influence diagram is generated for the particular spreadsheet, the method detects any change in the cells of the spreadsheet or any change in the entities of the influence diagram, and then updates the entities in the influence diagram or the spreadsheet corresponding to the detected change in the spreadsheet or influence diagram to maintain a functional equivalence between the spreadsheet and influence diagram.

Functional visualization of spreadsheets

A data analysis tool that provides a technique for visualizing changes of a system model. The analysis tool includes constructing an influence diagram consisting of a series of calculation entities and data entities interconnected by arrows, where the entities correspond to parameters of a system model being analyzed. Input values are assigned to each of the data entities for a particular scenario, and the corresponding values are computed for the calculation entities. A new scenario is implemented by changing one or more of the input values to the data entities, thus providing different results for some or all of the calculation entities. A mathematical function is applied to each entity to modify its appearance based on the values of the entities for current or other scenarios. Changes to each entity from the input of the new scenario can be in a variety of forms, such as size of the entity, color of the entity, shading of the entity, etc. Additionally, the arrows that connect the various entities can also be modified in appearance based on the new values of the entities for the new scenario. A rapid replay of the sequence of diagrams so generated provides a useful visual animating of system response to changing inputs and assists in controlling and improving the system under study.

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Ann Arbor, MI, United States of America

Jeffrey Morgan Alden