Method for managing electric vehicles

Patent metadata

Field	Value
Publication number	US-2023241995-A1
Application number	US-202318129600-A
Country	US
Kind code	A1
Filing date	Mar 31, 2023
Priority date	Oct 9, 2019
Publication date	Aug 3, 2023
Grant date	—

Abstract

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.

First claim

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; determining, for each trip, depletion of a charge of the electric vehicle; and creating fleet statistics specifying the performance of a fleet of electric vehicles comprising the plurality of simulated electric vehicles.

2 . The method of claim 1 wherein the plurality of simulated trips are simulated in parallel.

3 . The method of claim 1 further comprising:
identifying hotspots within the target area based on a state of charge for each simulated vehicle.

4 . The method of claim 3 further comprising:
tracking simulated vehicles for a remainder of their route when the state of charge for each vehicle falls below a predetermined threshold;
wherein the hotspots are identified as areas of the target area wherein the state of charge of vehicles tends to be below the predetermined threshold.

5 . The method of claim 4 further comprising:
recommending placement of vehicle chargers at or near the identified hotspots.

6 . The method of claim 4 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.

7 . The method of claim 4 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.

8 . The method of claim 7 wherein metrics regarding the cost of installing and servicing each charger is provided to the optimization.

9 . The method of claim 1 further comprising:
placing chargers for the fleet of electric vehicles at locations that optimize the fleet statistics.

10 . The method of claim 9 wherein the fleet statistics are optimized to maximize fleet utilization.

11 . The method of claim 1 wherein the start node and end node for each of the plurality of simulated trips is randomly-selected.

12 . The method of claim 1 wherein a route between the start node and the end node is determined by a routing algorithm.

13 . The method of claim 1 wherein the fleet statistics include energy used per mile.

14 . 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.

15 . The method of claim 14 further comprising:
determining depletion of the charge from node to node based on the determined power profile.

16 . The method of claim 14 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.

17 . The method of claim 16 wherein the velocity profile of the vehicle as it moves from node to node is dependent upon traffic information.

18 . The method of claim 15 wherein the power profile is determined by a vehicle dynamics model specific to a vehicle type and is customized by parameters specifying characteristics of a particular vehicle.

19 . The method of claim 14 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.

20 . The method of claim 14 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.

21 . The method of claim 1 wherein the charge depletion is determined by a battery dynamics model.

22 . The method of claim 21 wherein the charge depletion for each node is determined as a function of the temperature at the node.

Assignees

• Univ Carnegie Mellon

Inventors

• Viswanathan Venkatasubramanian
• Guttenberg Matthew
• Sripad Shashank

Classifications

• B60L53/62 Primary

  in response to charging parameters, e.g. current, voltage or electrical charge · CPC title

• B60L53/66

  Data transfer between charging stations and vehicles · CPC title

• G01C21/3469

  Fuel consumption; Energy use; Emission aspects · CPC title

• B60L58/13 Primary

  Maintaining the SoC within a determined range · CPC title

• B60L53/30

  Constructional details of charging stations · CPC title