Ford Global Technolgoies, LLC

Ford Global Tech.inc

Imad Hassan Makki

Pankaj Kumar

Hassene Jammoussi

James Michael Kerns

Robert Roy Jentz

Michael James Uhrich

Fling Finn Tseng

Timothy Joseph Clark

Dimitar Petrov Filev

Aed M Dudar

Gopichandra Surnilla

Stephen B Smith

Ross Dykstra Pursifull

Fakhreddine Landolsi

Adam Nathan Banker

Michael Igor Kluzner

Michael Casedy

John Ottavio Michelini

David Karl Bidner

Richard E Soltis

Mrdjan J Jankovic

Hsin-Hsiang Yang

Kenneth John Behr

Jianbo Lu

Kwaku O Prakah-Asante

Davor Hrovat

Steven Joseph Szwabowski

Brent Edward Sealy

Mazen Hammoud

Adithya Pravarun Re Ranga

Shiqi Qiu

Yong-Wha Kim

Joseph Norman Ulrey

Dennis C Reed

Dennis Seung-Man Yang

Russell Randall Pearce

William David Treharne

Clay Wesley Maranville

Ethan D Sanborn

Johannes Geir Kristinsson

Dilip B Patel

Stephen William Magner

Anthony Mario D'Amato

Mark Eifert

Timothy Mark Feldkamp

Tae-Kyung Lee

Alan Gutowski

Eric Matthew Storhok

Finn Finn Tseng

Medville Jay Throop

Mark Thomas Linenberg

Gopichandra Sumilla

Volker Scheer

Brian David Tillman

Joseph Wisniewski

Timothy Robert Gernant

Daniel F Slavin

David W Linden

Gladys Galicia

Chingpo Liu

Thomas Francis Rolewicz, Jr

Bruce C Arnold

Zena Yanqing Yee

Oussama Hattab

Sheida Malekpour

Ed A Schoenberg

John Steven McWilliams

Craig Stephens

Dimitar P Feliv

Hadi Abbas

Xun Tang

Avisek Naug

Gladys G Soriano

Michael James Ulrich

Michael Chol

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to train a generative adversarial network (GAN) to reconstruct a missing portion of an image by determining a reconstructed portion of the image based on data from portions of the image surrounding the missing portion and compare an acquired image with the reconstructed portion of the image to determine a damaged portion. The instructions further include instructions to determine estimated damage based on the damaged portion.

Vehicle damage estimation

A system comprises a processor that is programmed to define a plurality of vehicle groups based on vehicle specification data and define a plurality of sub-groups for each of the vehicle groups based on environmental data and sensor data received from each of a plurality of vehicles. The processor is programmed to adjust fuel tank leak detection classifiers for the sub-groups based on ground truth data. The ground truth data include, for each of the plurality of vehicles, a leak detection status and a leak test result.

Adaptive diagnostic parametrization

Methods, Apparatus, and Articles of Manufacture are disclosed for determining a tread depth status of a tire of a vehicle, including an accelerometer interface to access acceleration data from an accelerometer associated with the tire, the acceleration data including first acceleration data indicative of acceleration in a first direction, second acceleration data indicative of acceleration in a second direction, and third acceleration data indicative of acceleration in a third direction, and a data segmenter to segment the first acceleration data into a first data segment, the second acceleration data into a second data segment, and the third acceleration data into a third data segment based on at least one of an acceleration cycle or a common time interval.

Methods and apparatus to determine tire tread depth

A vehicle heating, ventilation, and air conditioning (HVAC) system including a cabin air filter, a sensor for providing a sensor reading, and a controller for determining a feedback signal from the sensor reading, wherein the controller determines a cabin air filter expected blockage level from the feedback signal. The feedback signal relates to a usage modifier of the cabin air filter, wherein the controller at east partially adjusts the estimated usage the cabin air filter from the usage modifier.

Heating, ventilation, and air conditioning system and a method for detecting cabin air filter usage

A system includes a processor configured to receive a set of user attribute preferences for a trip. The processor is also configured to determine a plurality of trip routes, the routes having variance in a value for at least one user attribute preference as compared to other of the routes. The processor is further configured to present the plurality of routes in a selectable manner, including displaying an attribute value associated with each route and implement navigation for a selected route.

Method and apparatus for route characteristic determination and presentation

Methods and systems are provided for reliably providing a prognosis of the life-expectancy of a vehicle battery. A state of degradation of the battery is predicted based on a rate of convergence of a metric, that is derived from a sensed vehicle operating parameter, towards a defined threshold, determined based on past history of the metric. The predicted state of degradation is then converted into an estimate of time or distance remaining before the component needs to serviced, and displayed to the vehicle operator. Vehicle control and communication strategies may be defined with respect to the predicted state of degradation.

Method for predicting battery life

A system includes a processor configured to receive report of a vehicle part malfunction, along with vehicle travel history covering at least a predefined time period. The processor is also configured to obtain condition data relating to environmental conditions encountered by the vehicle during the travel history. The processor is further configured to compare the obtained condition data to other condition data obtained from other vehicles reporting the same part malfunction. And the processor is configured to create a malfunction likelihood record for the vehicle part, including an association with a condition occurring over a threshold percentage of times with regards to all obtained condition data relating to the part malfunction and an indicator of a likely failure when a vehicle encounters the condition.

Method and apparatus for statistical vehicle element failure analysis

Systems and methods for detecting and reporting vehicle damage events are provided herein. An example method includes detecting any of a key-on or key-off event for a vehicle at a second point in time; in response to detecting the key-on or key-off event, obtaining a current set of images of one or more surfaces of the vehicle using one or more onboard cameras of the vehicle; accessing a baseline set of images for the vehicle obtained at a first point in time that precedes the second point in time; comparing the current set of images to the baseline set of images to determine damage to the one or more surfaces; and presenting a message through a human machine interface of the vehicle that is indicative of the damage.

Systems and methods for detecting and reporting vehicle damage events

Methods and systems are provided for learning fuel injector error for cylinder groups during a deceleration fuel shut-off (DFSO), where all cylinders of an engine are deactivated, sequentially firing each cylinder of a cylinder group, each cylinder fueled via consecutive first and second fuel pulses of differing fuel pulse width from an injector. Based on a lambda deviation between the first and second pulses, a fuel error for the injector and an air-fuel ratio imbalance for each cylinder is learned. Alternatively or additionally, a difference in crankshaft acceleration between the first and second pulses relative to the expected deviation may be used to learn torque error, and adjust fuel injector error and air-ratio imbalance for each cylinder.

Method and system for air-fuel ratio control

A system includes a computer including a processor and a memory, the memory storing instructions executable by the computer to determine a recursive standard deviation and a recursive mean offset of a plurality of steering component angles and to identify a wheel misalignment fault upon determining that the recursive standard deviation is below a deviation threshold and the recursive mean offset is above an offset threshold.

Wheel diagnostic

Methods and systems are provided for diagnosing a shock absorber coupled to a vehicle tire. In one example, a sensor of a tire pressure measurement system coupled inside a tire is used to measure a tire pressure as well as an oscillatory behavior of the tire. A state of health of a shock absorber coupled to the tire is estimated based on the oscillatory behavior.

Method and system for vehicle suspension system

A computer determines that a rate of travel value for a route segment being traversed by a first vehicle exceeds a predetermined threshold. A maneuver is planned for the first vehicle to depart from the route segment based on collected vehicle operating data from one or more second vehicles previously traversing the route segment. The first vehicle is instructed to execute the maneuver to depart the route segment.

Vehicle route navigation

Methods and systems are provided for regulating exhaust flow through an exhaust system of an engine. In one example, a method may include directing exhaust from downstream of a catalytic converter to a compressor storage tank in response to an engine air-fuel ratio deviating from stoichiometry. The stored exhaust may be released from the compressor storage tank to recirculate through the catalytic converter to atmosphere after adjusting an air-fuel ratio of the exhaust in the storage tank and when the catalytic converter is at a target operating temperature.

Method and system for catalytic conversion

Methods and systems are provided for reliably prognosing a vehicle component, such as a vehicle battery or an intake air filter. A state of degradation of the component is recursively predicted by updating, based on a sensed vehicle operating parameter, a previously estimated state of degradation of the component, the parameter selected based on the component being diagnosed, as well as based on past driving history and future driving predictions. The predicted state of degradation is then converted into an estimate of time or distance remaining before the component needs to serviced, and displayed to the vehicle operator.

Method for monitoring component life

A system includes a processor and a memory. The memory stores instructions executable by the processor to, based on a vehicle destination, identify a diagnostic condition and a specified operating pattern of a vehicle component that includes at least one of vehicle propulsion, braking, and steering. The memory stores instructions executable by the processor to operate the vehicle based on the vehicle component and the operating pattern.

Vehicle diagnostic operation

Growing community of inventors

Dearborn Heights, MI, United States of America

Imad Hassan Makki