Ford Global Technolgoies, LLC

Farshad Harirchi

Devang Bhalchandra Dave

Ryan J O'Gorman

Stuart C Salter

Katherine Howard-Cone

John Paul Bogema

James Matthew Marcicki

Justin Carmen Campanaro

John Joseph Virga

David McCreadie

Santhoji Rao Katare

Ryan O'gorman

Mohamed Asper

Harrison Wood

Vamsee Krishna Batchu

Chandar Mathalai

Eric Tyler Denlinger

Devang Davé

A vehicle comprising includes a traction battery and a controller. The controller, responsive to an interval exceeding a predefined threshold and a predicted net loss in energy, charges the traction battery such that the traction battery acquires energy in an amount at least equal to the predicted net loss in energy. The interval defines a confidence level that a predicted net change in energy stored by the traction battery will occur as a result of use of the vehicle between a current charge location of the vehicle and a next charge location of the vehicle. The amount is based on the interval such that the amount increases as the interval decreases.

Confidence-based vehicle charge control

The disclosure describes systems and methods that are configured to measure and generate parking environment data including locations of parking spaces and their occupancy status, and to use the parking environment data to find an unoccupied parking space for a vehicle. In particular, a system is configured to determine the location and occupancy status of parking spaces based on parking environment data received from a vehicle, and to determine a location of an unoccupied parking space based on a database of parking environment data.

Systems and methods for locating a parking space

A controller may, after receiving indication that an electric utility provider will reduce power supplied during an upcoming period of time, increase a cost of charge energy for vehicles that charge at a rate at least equal to a threshold rate during the upcoming period of time. The controller may also decrease the cost of charge energy for vehicles that avoid charging or charge at a rate less than the threshold rate during the upcoming period of time.

Electric vehicle charging aggregation

A vehicle charging system includes a vehicle propelled by an electric machine powered by a chargeable energy storage system. The charging system also includes a controller programmed to predict at least one upcoming plug-in event based on historical charging data, and define a plug-in routine based on a plurality of upcoming plug-in events. The controller is also programmed to set a charging schedule to coincide with the plug-in routine such that a target state of charge (SOC) is achieved at a conclusion of each of the plurality of upcoming plug-in events. Each target SOC corresponding to a plug-in event is based on minimizing a charging energy cost of the plug-in routine and an expected energy depletion ahead of a next subsequent plug-in event.

Vehicle charging control systems and methods

A vehicle includes a controller that sends a charge request defining a charge location to a charge donor vehicle for vehicle-to-vehicle charging, responsive to not detecting a charge cable that satisfies the charge request in the vehicle and the charge donor vehicle, sends a borrow request including the charge location to a charge cable donor vehicle, and responsive to confirmation from the charge donor vehicle and charge cable donor vehicle, directs the vehicle to drive to the charge location.

Vehicle to vehicle charge cable acquisition

Approaches for predicting parameters contributing to engine emissions are described. In an example, the values of control parameters may be obtained from the vehicle sensors. Based on the obtained values of the control parameters, estimated emission value may be determined pertaining to a correlation criterion reflecting a predetermined relationship between the obtained control parameter and engine emission. Further, the contribution index of each of the individual control parameters may be identified. Further, based on the estimated emission value and the contribution index, aggregated emission value corresponding to the exhausted emission from the engine for particular trip may be calculated.

Engine emission prediction system

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Ann Arbor, MI, United States of America

Farshad Harirchi