US-20260124949-A1 - DUAL-STAGE MULTIDAY CHARGING CONTROL

US20260124949A1US 20260124949 A1US20260124949 A1US 20260124949A1US-20260124949-A1

Abstract

A system includes multiple charging stations, multiple fleet electric vehicles, and a computer. The charging stations are provided at a facility. The fleet electric vehicles are charged by the charging stations per a schedule. The fleet electric vehicles are operational to perform multiple tasks on multiple routes dispersed over multiple days. The computer is in communication with the charging stations and is operational to generate the schedule to charge the fleet electric vehicles over the multiple days with a two-stage process. The schedule is based on a first number of the charging stations ready to charge, a second number of the fleet electric vehicles ready to be charged, a plurality of state-of-charges in the fleet electric vehicles upon arrival and already present at the facility, and a plurality of energy consumption levels associated with the plurality of routes.

Inventors

Daniel Urieli
KLAUS TRANGBAEK
Yaron Veksler
Evi Cohen

Assignees

GM Global Technology Operations LLC

Dates

Publication Date: 20260507
Application Date: 20241107

Claims (20)

1 . A system comprising: a plurality of charging stations provided at a facility; a plurality of fleet electric vehicles that are charged by the plurality of charging stations per a schedule, wherein: the plurality of fleet electric vehicles are operational to perform a plurality of tasks on a plurality of routes dispersed over a plurality of days; and a computer in communication with the plurality of charging stations and operational to generate the schedule to charge the plurality of fleet electric vehicles over the plurality of days with a two-stage process, wherein the schedule is based on: a first number of the plurality of charging stations ready to charge; a second number of the plurality of fleet electric vehicles ready to be charged; a plurality of state-of-charges in the plurality of fleet electric vehicles upon arrival at the facility and already present at the facility; and a plurality of energy consumption levels associated with the plurality of routes.
2 . The system according to claim 1 , wherein the two-stage process comprises: a first stage operational to perform a plurality of searches in a combinatorial search tree to determine a complete assignment mapping of the plurality of fleet electric vehicles suited to perform the plurality of tasks; and a second stage operational to perform a scheduling process that determines the schedule for charging the plurality of fleet electric vehicles over the plurality of days based on the complete assignment mapping.
3 . The system according to claim 2 , wherein the computer is further operational to: minimize the plurality of state-of-charges in the plurality of fleet electric vehicles upon departure from the facility to accomplish the plurality of tasks based on the complete assignment mapping and the schedule.
4 . The system according to claim 2 , wherein the complete assignment mapping is flexible to trade off a peak demand charging value and a time-of-use charging value while satisfying the plurality of tasks.
5 . The system according to claim 2 , wherein the computer is further operational to: solve a value-minimizing aggregate for the complete assignment mapping with the scheduling process.
6 . The system according to claim 2 , wherein: a number of candidate complete assignment mappings is less than a total number of possible complete assignment mappings in the combinatorial search tree.
7 . The system according to claim 2 , wherein the computer is further operational to: skip one or more conflicting tasks among the plurality of tasks in the plurality of searches.
8 . The system according to claim 2 , wherein the computer is further operational to: skip completion of one or more partial candidate complete assignment mappings that utilize higher peak power than a previously found candidate complete assignment mapping during the plurality of searches to determine the complete assignment mapping.
9 . The system according to claim 2 , wherein the computer is further operational to: finalize the complete assignment mapping; and perform the scheduling process a single time in response to the complete assignment mapping as finalized.
10 . The system according to claim 2 , wherein the computer is further operational to present the schedules in a human readable form.
11 . A method for dual-stage multiday charging control comprising: providing a plurality of charging stations at a facility; generating a schedule to charge a plurality of fleet electric vehicles over a plurality of days by performing a two-stage process, wherein: the plurality of fleet electric vehicles are operational to perform a plurality of tasks on the plurality of routes dispersed over the plurality of days; and the schedule is based on: a first number of the plurality of charging stations ready to charge; a second number of the plurality of fleet electric vehicles ready to be charged; a plurality of state-of-charges in the plurality of fleet electric vehicle upon arrival at the facility and already present at the facility; and a plurality of energy consumption levels associated with a plurality of routes; and charging the plurality of fleet electric vehicles with the plurality of charging stations based on the schedule.
12 . The method according to claim 11 , wherein the two-stage process comprises: performing a plurality of searches in a combinatorial search tree in a first stage to determine a complete assignment mapping of the plurality of fleet electric vehicles suited to perform the plurality of tasks; and performing a scheduling process in a second stage that determines the schedule for charging the plurality of fleet electric vehicles over the plurality of days based on the complete assignment mapping.
13 . The method according to claim 12 , further comprising: minimizing the plurality of state-of-charges in the plurality of fleet electric vehicles upon departure from the facility to accomplish the plurality of tasks based on the complete assignment mapping and the schedule.
14 . The method according to claim 12 , wherein the complete assignment mapping is flexible to trade off a peak demand charging value and a time-of-use charging value while satisfying the plurality of tasks.
15 . The method according to claim 12 , further comprising: solving a value-minimizing aggregate for the complete assignment mapping with the scheduling process.
16 . The method according to claim 12 , wherein: a number of candidate complete assignment mappings is less than a total number of possible complete assignment mappings in the combinatorial search tree.
17 . The method according to claim 12 , further comprising: skipping one or more conflicting tasks among the plurality of tasks in the plurality of searches.
18 . The method according to claim 12 , further comprising: skipping completion of one or more partial candidate complete assignment mappings that utilize higher peak power than a previously found candidate complete assignment mapping during the plurality of searches to determine the complete assignment mapping.
19 . The method to claim 12 , further comprising: finalizing the complete assignment mapping; and performing a final scheduling process a single time in response to the finalizing of the complete assignment mapping.
20 . A facility comprising: a plurality of charging stations operational to charge a plurality of fleet electric vehicles per a schedule, wherein the plurality of fleet electric vehicles are operational to perform a plurality of tasks on a plurality of routes dispersed over a plurality of days; and a computer in communication with the plurality of charging stations and operational to generate the schedule to charge the plurality of fleet electric vehicles over the plurality of days with a two-stage process, wherein the schedule is based on: a first number of the plurality of charging stations ready to charge; a second number of the plurality of fleet electric vehicles ready to be charged; a plurality of state-of-charges in the plurality of fleet electric vehicle upon arrival at the facility and already present at the facility; and a plurality of energy consumption levels associated with the plurality of routes; and wherein the two-stage process comprises: a first stage operational to perform a plurality of searches in a combinatorial search tree to determine a complete assignment mapping of the plurality of fleet electric vehicles suited to perform the plurality of tasks; and a second stage operational to perform a scheduling process that determines the schedule to charge the plurality of fleet electric vehicles over the plurality of days based on the complete assignment mapping.

Description

INTRODUCTION The present disclosure relates to a system and a method for dual-stage multiday charging control for a fleet of electric vehicles. Ownership of a fleet of electric vehicles comes with an issue of how to determine a charging schedule for the electric vehicles. The charging schedule may be composed of time-of-use charging and peak power demand charging, each having certain advantages and disadvantages. Charging an electric vehicle during a peak power demand time of a day is less value optimal than charging the electric vehicle during a low power demand time. Accordingly, those skilled in the art continue with research and development efforts in the field of charging management of electric vehicles. SUMMARY A system is provided herein. The system includes a plurality of charging stations provided at a facility, a plurality of fleet electric vehicles, and a computer. The plurality of fleet electric vehicles are charged by the plurality of charging stations per a schedule. The plurality of fleet electric vehicles are operational to perform a plurality of tasks on a plurality of routes dispersed over a plurality of days. The computer is in communication with the plurality of charging stations and is operational to generate the schedule to charge the plurality of fleet electric vehicles over the plurality of days with a two-stage process. The schedule is based on a first number of the plurality of charging stations ready to charge, a second number of the plurality of fleet electric vehicles ready to be charged, a plurality of state-of-charges in the plurality of fleet electric vehicles upon arrival at the facility and already present at the facility, and a plurality of energy consumption levels associated with the plurality of routes. In one or more embodiments of the system, the two-stage process includes a first stage operational to perform a plurality of searches in a combinatorial search tree to determine a complete assignment mapping of the plurality of fleet electric vehicles suited to perform the plurality of tasks, and a second stage operational to perform a scheduling process that determines the schedule for charging the plurality of fleet electric vehicles over the plurality of days based on the complete assignment mapping. In one or more embodiments of the system, the computer is further operational to minimize the plurality of state-of-charges in the plurality of fleet electric vehicles upon departure from the facility to accomplish the plurality of tasks based on the complete assignment mapping and the schedule. In one or more embodiments of the system, the complete assignment mapping is flexible to trade off a peak demand charging value and a time-of-use charging value while satisfying the plurality of tasks. In one or more embodiments of the system, the computer is further operational to solve a value-minimizing aggregate for the complete assignment mapping with the scheduling process. In one or more embodiments of the system, a number of candidate complete assignment mappings is less than a total number of possible complete assignment mappings in the combinatorial search tree. In one or more embodiments of the system, the computer is further operational to skip one or more conflicting tasks among the plurality of tasks in the plurality of searches. In one or more embodiments of the system, the computer is further operational to skip completion of one or more partial candidate complete assignment mappings that utilize higher peak power than a previously found candidate complete assignment mapping during the plurality of searches to determine the complete assignment mapping. In one or more embodiments of the system, the computer is further operational to finalize the complete assignment mapping, and perform the scheduling process a single time in response to the complete assignment mapping as finalized. In one or more embodiments of the system, the computer is further operational to present the schedules in a human readable form. A method for dual-stage multiday charging control is provided herein. The method includes providing a plurality of charging stations at a facility, and generating a schedule to charge a plurality of fleet electric vehicles over a plurality of days by performing a two-stage process. The plurality of fleet electric vehicles are operational to perform a plurality of tasks on the plurality of routes dispersed over the plurality of days. The schedule is based on a first number of the plurality of charging stations ready to charge, a second number of the plurality of fleet electric vehicles ready to be charged, a plurality of state-of-charges in the plurality of fleet electric vehicle upon arrival at the facility and already present at the facility, and a plurality of energy consumption levels associated with a plurality of routes. The method includes charging the plurality of fleet electric vehicles with the plurality of charging stations based on the schedule. In on