Locating optimal charge stations
US-2022089056-A1 · Mar 24, 2022 · US
US12005800B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12005800-B2 |
| Application number | US-202318129600-A |
| Country | US |
| Kind code | B2 |
| Filing date | Mar 31, 2023 |
| Priority date | Oct 9, 2019 |
| Publication date | Jun 11, 2024 |
| Grant date | Jun 11, 2024 |
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A method for the efficient management of a fleet of electric vehicles in a target area couples vehicle dynamics and battery dynamics modeling with environmental factors to accurately incorporate the impact that the environment has on the range of the battery into the placement of the chargers by simulating trips of fleets of electric vehicles. The vehicles can be of various types, for example, motorcycles, cars, trucks or aircraft, and will each have their battery state of charge monitored as they traverse a simulated trip through the target area.
Opening claim text (preview).
The invention claimed is: 1. A method for managing a fleet of electric vehicles in a target area, comprising: dividing the target area into one or more geographic portions; assigning one or more nodes to each geographic portion; simulating a plurality of trips of a plurality of simulated electric vehicles through the target area, each trip comprising a series of the nodes between a start node and an end node; tracking, during each simulated trip, depletion of a charge of each simulated electric vehicle, based on a vehicle dynamics model of the electric vehicle and a battery dynamics model of the electric vehicle executed by a computer; and identifying hotspots as areas of the target area wherein the charge of vehicles tends to be below a predetermined threshold. 2. The method of claim 1 wherein the plurality of simulated trips are simulated in parallel using an agent-based electric vehicle simulation framework. 3. The method of claim 1 further comprising: recommending placement of vehicle chargers at or near the identified hotspots. 4. The method of claim 1 further comprising: providing a set of existing charger locations to the simulations; determining which of the existing chargers have the highest utilization; and recommending placement of additional vehicle chargers at the locations of existing charger having the highest utilization. 5. The method of claim 1 further comprising: performing an optimization to determine an optimal placement of chargers such that demand of the fleet is met and economic impact of the charger installation is minimized; and recommending placement of chargers based on the optimization. 6. The method of claim 5 wherein metrics regarding the cost of installing and servicing each charger is provided to the optimization. 7. The method of claim 1 further comprising: placing chargers for the fleet of electric vehicles at locations that optimize the fleet statistics. 8. The method of claim 7 wherein the fleet statistics are optimized to maximize fleet utilization. 9. The method of claim 1 wherein the start node and end node for each of the plurality of simulated trips is randomly-selected. 10. The method of claim 1 wherein a route between the start node and the end node is determined by a routing algorithm. 11. The method of claim 1 wherein the fleet statistics include energy used per mile. 12. The method of claim 1 further comprising: determining a power profile required for the vehicle to move from node to node in the series of nodes. 13. The method of claim 12 further comprising: determining depletion of the charge from node to node based on the determined power profile. 14. The method of claim 13 wherein the power profile is determined by the dynamics model wherein the dynamics model is specific to a vehicle type and is customized by parameters specifying characteristics of a particular vehicle. 15. The method of claim 12 further comprising: determining a distance travelled as the vehicle moves from node to node in the series of nodes; determining a velocity profile of the vehicle as it moves from node to node; and determining the power profile required for the vehicle to move from the previous node to the current node, the power profile based on the distance travelled and the velocity profile. 16. The method of claim 15 wherein the velocity profile of the vehicle as it moves from node to node is dependent upon traffic information. 17. The method of claim 12 further comprising: determining a positive or negative wind component in the direction of travel of the vehicle based on the wind speed and the wind direction stored each node; and adjusting the power profile required for the vehicle to move from node to node based on the wind component. 18. The method of claim 12 further comprising: determining a positive or negative elevation change from node to node; and adjusting the power profile required for the vehicle to move from node to node based on the elevation change. 19. The method of claim 1 wherein the charge depletion for each node is determined as a function of the temperature at the node.
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