Bayerische Motoren Werke Aktiengesellschaft

Henry Pease

Adam Langton

Sean Batir

Anderson Vankayala

A system preconditions a battery pack of a vehicle to support fast charging. The system detects a trigger that that indicates the vehicle will be traveling or the battery pack of the vehicle has been reduced to a predetermined capacity. The system collects a plurality of samples of location data of the vehicle. The system predicts a destination of the vehicle based on the samples. The system determines a propensity of a user to charge the vehicle based on previous charging behavior of the user. The system determines a confidence score of the predicted destination and the determined propensity. The system determines whether to schedule preconditioning of the battery pack based on the confidence score meeting a threshold.

Intelligent preconditioning for high voltage electric vehicle batteries

A computing system can facilitate cooperation between a utility and a fleet of vehicles. The system can receive a charging requirement from a vehicle. The charging requirement can be based on an available power output capacity of a battery pack of the vehicle. The system can receive solar ramp data from a utility. The solar ramp data can be based on an anticipated power output of a solar energy source. The system can determine a charge plan based on the charging requirement and the solar ramp data and specify a timing of charging or discharging the vehicle. The system can transmit the charge plan to the vehicle. The system can receive load data from the vehicle based on supply or consumption of power by the vehicle and the charge plan.

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San Francisco, CA, United States of America

Henry Pease