Method for determining optimal placement of electric vehicle chargers

Patent metadata

Field	Value
Publication number	US-2021107372-A1
Application number	US-202017066755-A
Country	US
Kind code	A1
Filing date	Oct 9, 2020
Priority date	Oct 9, 2019
Publication date	Apr 15, 2021
Grant date	—

Abstract

A method for the efficient placement of electric vehicle chargers 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 comprising:
generating a map of a target area, the map comprising one or more nodes, each node corresponding to a geographic portion of the target area, each node containing one or more characteristics of the portion of the target area to which it corresponds; simulating a plurality of trips of a plurality of simulated electric vehicles through the target area, each of the plurality of electric vehicles having a battery, each simulation comprising:
determining a route for the simulated trip, the route comprising a series of nodes from the map;
for each current node in the route:
determining a power profile required for the vehicle to move from a previous node to the current node;
determining depletion of the battery from the previous node to the current node based on the determined power profile;
determining if a state of charge of the battery falls below a predetermined threshold and, if so, determining the nearest node comprising a charger location;
ending the simulation when the state of charge falls below the predetermined threshold or when the vehicle reaches an end node in the route.

2 . The method of claim 1 wherein the map comprises one or more matrices, each cell in each matrix corresponding to a node in the map, each cell in each matrix containing data representing at least one of the one or more characteristics.

3 . The method of claim 1 wherein nodes in the target area which do not contain or are not part of a road are ignored for purposes of the plurality of simulated trips.

4 . The method of claim 1 wherein the power profile required for the vehicle to move from the previous node to the current node is extracted from a power profile for the entire trip.

5 . The method of claim 1 further comprising:
determining a distance travelled as the vehicle moves from the previous node in the route to the current node in the route;
determining a velocity profile of the vehicle as it moves from the previous node to the current node;
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.

6 . The method of claim 5 wherein the velocity profile required for the vehicle to move from the previous node to the current mode is extracted from a velocity profile for the entire trip;

7 . The method of claim 1 wherein the one or more characteristics of each node comprise the location of the node and environmental conditions at the node.

8 . The method of claim 5 wherein the one or more characteristics of each node comprise traffic information and further wherein the velocity profile of the vehicle as it moves from the previous node to the current node is dependent upon the traffic information.

9 . The method of claim 7 , wherein the environmental conditions comprise wind speed, wind direction, elevation and temperature.

10 . The method of claim 1 wherein the route comprises a start node and an end node.

11 . The method of claim 10 wherein the start node and the end node are selected at random or based on the sampling of the distribution.

12 . The method of claim 11 wherein the route is determined using a routing algorithm.

13 . The method of claim 1 wherein the power profile is determined by a vehicle dynamics model.

14 . The method of claim 13 wherein the vehicle dynamics model is specific to a vehicle type and is customized by parameters specifying characteristics of a particular vehicle.

15 . The method of claim 14 wherein the parameters specifying characteristics of the particular vehicle are user-supplied values or are sampled from a distribution.

16 . The method of claim 9 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 for the current node in the route; and
adjusting the power profile required for the vehicle to move from the previous node to the current node based on the wind component.

17 . The method of claim 9 further comprising:
determining a positive or negative elevation change from the previous node in the route to the current node in the route; and
adjusting the power profile required for the vehicle to move from the previous node to the current node based on the elevation change.

18 . The method of claim 9 wherein the depletion of the battery is determined by a battery dynamics model.

19 . The method of claim 18 wherein the depletion of the battery for the current node is determined as a function of the temperature at the current node.

20 . The method of claim 1 , wherein the resolution of the nodes is set by a user-supplied variable.

21 . The method of claim 7 , wherein the one or more characteristics of each node further comprises whether the node is a charger location.

22 . The method of claim 21 wherein the node is a charger location if the node currently contains one or more electric chargers or is identified as a possible location for one or more electric chargers.

23 . The method of claim 21 further comprising:
determining the total number of trips from the plurality of simulated trips for which each node identified as a charger location was a closest node to the vehicle when the state of charge of the battery of the vehicle dropped below the threshold.

24 . The method of claim 23 further comprising:
determining a predetermined number of nodes having the highest total number of trips; and
identifying the predetermined number of nodes as possible locations for charger deployment.

25 . The method of claim 1 wherein the initial state of charge of the battery for each simulated trip is set to a random value.

26 . The method of claim 1 wherein the initial state of charge of the battery for each simulated trip is set by sampling a distribution.

27 . The method of claim 1 wherein a subset of the plurality of simulated trips are run in parallel.

28 . The method of claim 27 wherein the subset of the plurality of simulated trips are run on multiple cores either on the same processor or different processors wherein one core manages a plurality of agents running in the remaining cores, each agent simulating one of the plurality of electric vehicles traversing one of the plurality of simulated trips.

29 . The method of claim 1 further comprising:
creating fleet statistics specifying the performance of a fleet of electric vehicles comprising the plurality of simulated electric vehicles.

30 . The method of claim 1 wherein the number of simulated trips is a user-supplied parameter.

31 . The method of claim 1 further comprising:
determining that the state of charge of the battery has fallen below a low state of charge threshold; and
tracking a number of times the current node contains a vehicle that has fallen below the low state of charge threshold; and
identifying as low state of charge hotspots those nodes having the highest number of times the node contained a vehicle that fell below the low state of charge threshold.

Assignees

• Univ Carnegie Mellon

Inventors

• Viswanathan Venkatasubramanian
• Guttenberg Matthew
• Sripad Shashank

Classifications

• G01C21/3469

  Fuel consumption; Energy use; Emission aspects · CPC title

• Y02T10/64

  Electric machine technologies in electromobility · CPC title

• B60L15/2045

  for optimising the use of energy · CPC title

• B60L2240/12

  Speed · CPC title

• B60L58/13 Primary

  Maintaining the SoC within a determined range · CPC title