CPC B60L 53/66 (2019.02) [B60H 1/0073 (2019.05); B60L 53/60 (2019.02); G06N 3/045 (2023.01); G06N 20/00 (2019.01); H02J 7/0048 (2020.01); H02J 7/0071 (2020.01); B60L 2240/34 (2013.01); B60L 2250/14 (2013.01); B60L 2260/46 (2013.01); B60L 2260/58 (2013.01)] | 20 Claims |
1. A system, comprising:
a memory device; and
one or more hardware processors configured by machine-readable instructions for scheduling pre-departure charging for electric vehicles, the one or more hardware processors configured to:
predict a user-departure time based on a first machine learning prediction model, wherein the user-departure time represents when a user initiates driving an electric vehicle;
determine a cabin temperature to be set for the user at the user-departure time based on a second machine learning prediction model;
determine a battery-temperature of a battery of the electric vehicle to be set at the user-departure time based on a third machine learning prediction model;
determine a present charge level of a battery of the electric vehicle;
compute a charging start-time to start charging the battery based on one or more attributes of a charging station to which the electric vehicle is coupled, and based on the user-departure time, the cabin temperature, and the battery-temperature; and
start charging the battery at the charging start-time.
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