Ford Global Technolgoies, LLC

Christopher Leon Jones

David Alfred Ostrowski

David Michael Herman

Jacob Martin Povirk

Charles Krysztof

Leopoldo Urbina

Antonio Stranges

Sheida Malekpour

Andrew Christipher Posa

Sanjay Abhyankar

Methods and systems are provided for selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle on a road segment that includes one or more road attributes associated with increased levels of anxiety. In one example, selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle includes determining a driver classification for a driver operating the vehicle; predicting an anxiety level of the driver at an upcoming traffic condition, based on the driver classification; and selectively inhibiting an upcoming engine idle-stop event based on the predicted anxiety level of the driver.

Methods and systems for an adaptive stop-start inhibitor

A computer includes a processor and a memory storing instructions executable by the processor to generate an operation parameter histogram for each of a plurality of vehicle operation parameters, operate a test vehicle according to the operation parameter histograms, input each operation parameter histogram and a plurality of test vehicle environment data to a machine learning program, output from the machine learning program a classification for each operation parameter histogram from the machine learning program, input the classifications to a predictive damage model of a three-dimensional schematic of a vehicle component, and adjust one of a size or a shape of the three-dimensional schematic based the output of the predictive damage model. The operation parameter histograms are based on collected data about operation of a plurality of vehicles. Each operation parameter histogram includes an array of elements. Each element is a number of data points for one of the operation parameters that are within a specified range. Each classification represents a type of environment and a type of test vehicle use.

Enhanced component dimensioning

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Detroit, MI, United States of America

Christopher Leon Jones