SYSTEM AND METHOD FOR VEHICLE FLEET CHARGING OPTIMIZATION

Abstract

Method for managing vehicle charging for a vehicle charging system comprising a plurality of vehicle chargers and a plurality of vehicle paths extending between them, enabling vehicles to travel from one of the vehicle chargers to another, the method comprising: detecting (500) a failed vehicle charger; using processing switching logic, determining (510) an optimal vehicle path between the failed vehicle charger and an available vehicle charger; and providing (520) an instruction to a first vehicle to move from the failed vehicle charger to the available vehicle charger along the determined optimal vehicle path, the first vehicle being an autonomous vehicle, the determining further comprising: determining a plurality of vehicle paths between the failed vehicle charger and the available vehicle charger;Determining a shortest of the plurality of vehicle paths; and selecting the shortest of the vehicle paths as the determined shortest of the plurality of vehicle paths, wherein determining a plurality of vehicle paths further includes determining which vehicle paths of the determined plurality of vehicle paths do not intersect a vehicle path of the plurality of vehicle paths intended for another vehicle, and wherein determining a shortest of the plurality of vehicle paths further includes determining the shortest of the plurality of vehicle paths from the vehicle paths of the determined plurality of vehicle paths that do not intersect a vehicle path of the plurality of vehicle paths intended for another vehicle.

Description

INTRODUCTION

[0001] The present disclosure is generally directed to charging systems for electric vehicles. More specifically, the present disclosure is directed to fleet charging optimization in charging systems for electric vehicles. SUMMARY

[0002] Electric vehicles have recently gained increasing acceptance, as they offer many significant advantages over conventional vehicles powered by internal combustion engines. For example, many argue that electric vehicles offer reduced reliance on fossil fuels, as well as simpler and more reliable vehicles with lower maintenance costs. However, electric vehicles also present significant challenges. For instance, organizations using fleets of electric vehicles may utilize fleet charging depots to charge their vehicles. Such depots can be quite large, employing anywhere from ten to hundreds of chargers, depending on the fleet size. In particular, if depot chargers experience non-trivial failure rates (e.g., as a result of heavy use), the result is lost charging time and the need to move vehicles from failed chargers to functioning ones.

[0003] Accordingly, systems and procedures for an electric vehicle fleet management system are described herein that optimally reroutes vehicles from charger failures by determining optimal or shortest routes between failed chargers and available working chargers, so that vehicles at failed chargers can be optimally moved to working chargers to continue charging. In some embodiments, a controller can use data analytics and machine learning algorithms to predict when a charger will fail (e.g., based on high usage and the number of failures in past instances) and proactively send instructions to move a vehicle to a working charger, while simultaneously flagging the failed charger for repair.Charging depots can be mapped and modeled as a graph network of nodes and edges representing possible vehicle paths between failed and functioning chargers. Graphical route planning methods can then be used to determine the shortest of these paths. Shortest paths can be implemented to guide vehicles more quickly to available chargers and reduce the impact of failed chargers on fleet charging time. For example, route guidance instructions can be issued to drivers, or instructions can be given to autonomous electric vehicles to follow the specified shortest paths.

[0004] In some embodiments of the disclosure, shortest paths for different vehicles are checked for intersection paths to prevent potential collisions between vehicles traveling to different chargers simultaneously. In some embodiments, intersection paths can be discarded, and the nearest shortest paths for such vehicles can be selected instead. Although this may result in slightly longer travel times from failed to functioning chargers, this reduction in efficiency can be offset by the increased safety and vehicle availability provided by collision avoidance.

[0005] In some embodiments of the disclosure, systems and methods are described herein for an electric vehicle fleet management system that further manages the charging of an electric vehicle fleet according to the number of available chargers (taking into account any chargers that have failed), the number of vehicles that need to be charged, and their charging times. As an example, a fleet management system can generate a priority list of vehicles that need to be moved to a functioning charger to ensure they are charged in a timely manner. Vehicles can then be moved from chargers when they are sufficiently charged, with other vehicles being moved into these now available chargers in order of the priority list. In this way, fleet management systems can ensure that enough vehicles are sufficiently charged to complete all necessary tasks.

[0006] In some embodiments, these fleet management systems can also move vehicles from chargers and move other vehicles along certain shortest paths, as described above, via the list of now available chargers. That is, for each sufficiently charged vehicle being moved away from a charger and each vehicle being moved to that now available charger, as described above via the priority list, systems of embodiments of the disclosure can determine shortest paths as described above and move these vehicles accordingly. Furthermore, systems of embodiments of the disclosure can also determine such shortest potentially intersecting paths, thereby avoiding collisions. List of characters

[0007] The foregoing and other functions and advantages of the disclosure will become clear when considering the following detailed description in conjunction with the accompanying drawings, in which the same reference numerals consistently refer to the same parts and in which: Fig. 1 is a conceptual top view of an exemplary vehicle loading system constructed according to some embodiments of the disclosure; Fig. 2 an abstraction of the exemplary vehicle charging system of Fig. 1 is, which illustrates the operation according to some embodiments of the disclosure; Fig. 3 and Fig. Four exemplary trees of vehicle paths are derived, according to some embodiments of the disclosure, from the abstraction of Fig. 2 are drawn; Fig. 5 is a flowchart illustrating an exemplary process for optimally diverting vehicles from vehicle charger failures according to some embodiments of the disclosure; Fig. 6 is a flowchart illustrating an exemplary process for collision avoidance in the event of vehicle charger failures according to some embodiments of the disclosure; Fig. 7 is a flowchart illustrating an exemplary process for managing a multi-vehicle loading operation according to some embodiments of the present disclosure; and Fig. 8 is a block diagram of an illustrative device for performing optimal vehicle path rerouting as a result of vehicle charger failures according to some embodiments of the disclosure. DETAILED DESCRIPTION

[0008] In one embodiment, the disclosure relates to systems and methods for a computer-based process that minimizes the impact of vehicle charger failures on fleet charging times. Failed chargers are detected, and shortest paths between these failed chargers and available chargers are determined. Vehicles are then routed along these shortest paths from the failed chargers to available chargers. Paths can also be determined to avoid collisions between vehicles when multiple vehicles need to be moved simultaneously.

[0009] Additionally, in some embodiments of the disclosure, vehicles are prioritized for charging according to arbitrary factors, such as their current charge level, the desired or required charge level, and the like. If chargers fail, vehicles can then be moved from these failed chargers to available chargers in order of priority, in order to better ensure a sufficiently charged fleet.

[0010] Fig. Figure 1 is a conceptual top view of an exemplary vehicle charging system constructed according to some embodiments of the disclosure. Here, a vehicle charging system 100, which may be a fleet charging depot, includes at least one transformer 110 electrically coupled to a number of charging stations 130. Each charging station 130 includes a charging device for electrically connecting to and charging an electric vehicle 120, as well as a physical space such as a box or parking space for receiving a vehicle 120 while it is connected to the charging device. While the exemplary system 100 of Fig. Including 115 charging stations 130 arranged in a 3 × 5 configuration, the system 100 in embodiments of the disclosure can include any number of transformers 110 in electrical communication with any number of charging stations 130 for charging any number of electric vehicles 120. The operations of the charging stations 130 can each be controlled by a controller 330, which can be in electronic communication with them and which can include a processor such as any suitable digital computing device, as described below, which executes instructions for vehicle fleet charging optimization according to methods and processes of any embodiments of the disclosure.

[0011] While the controller 330 is shown having connections only to transformers 110, in some embodiments the controller 330 can couple with the charging stations 130, which includes data and other communication channels.

[0012] In operation, vehicles 120 can be parked at any charging station 130, where they can remain while charging. The charging stations 130 can be arranged and spaced to provide paths between them, allowing vehicles 120 to move from one charging station 130 to another and / or to move in or out of the system 100, such as when vehicles 120 enter or leave the system 100 facility when sufficiently charged. Paths can be arranged in any way between one or more charging stations 130 and can be represented by path segments 140 to 240 connected at nodes 250 to 320. Here, nodes 250 to 320 can simply be representations of physical locations where two path segments 140 to 240 meet.

[0013] Accordingly, the vehicle 120 can be moved along all paths (partially represented by path segments 140 to 240) to or from any charging station 130. In particular, and by way of example, the charger can be connected to the charging station 130 where the vehicle 120 is located. Fig. 1 is located, fail. Accordingly, vehicle 120 can be moved from this charging station 130 to another available charging station 130. In this example, the second charging station 130 on the right in the top row of charging stations can be used. Fig. 1 be empty or available, and vehicle 120 can accordingly be moved there along the shortest path in between, e.g., along path segments 160, 170, 180, 190, 200, 210, 220, 230, 240 in that order (i.e., through nodes 250, 260, 270, 280, 290, 300, 310, 320 in that order). While it can be observed that vehicle 120 moves into the second right-hand charging station 130 of the top row of Fig. Since 1 can be moved along any other path, the path represented by path segments 160, 170, 180, 190, 200, 210, 220, 230, 240 in this order can be considered the shortest possible path for this arrangement of charging stations 130 and thus enable the most time-efficient charging time at the destination station 130.

[0014] Fig. 2 is an abstraction of the exemplary vehicle charging system of Fig. 1, which illustrates the operation according to some embodiments of the disclosure. In this example, each charging station 130 can be occupied by a vehicle 120, except for stations * 1 and *2, i.e., the leftmost and second-to-right charging stations 130 of the top row in the view of Fig. Two charging stations are free and available for charging a vehicle. Furthermore, charging stations X1 and X2 can be considered out of service, so vehicles located at stations X1 and X2 should be moved to stations *1 and *2. Additionally, in this example, vehicles can move between stations 130 along any set of path segments H1 to H18, V1 to V19, as shown.

[0015] In some embodiments of the disclosure, the shortest paths between the failed stations X1, X2 and available stations *1, *2 can be determined, and vehicles can be sent to the available stations *1, *2 along these shortest paths. Such shortest paths can be determined in any way. In some embodiments, there can be multiple shortest paths. It is understood that if either the shortest path or the multiple shortest paths are unavailable, the next shortest path (e.g., n+1, where n is equal to the previous unavailable path) is identified.In some embodiments of the disclosure, shortest paths can be determined using an approach similar to a first depth-first search, with graph structures such as trees constructed to represent all possible paths between each failed station X1, X2 and each available station *1, *2, and the branches of these trees traversed in spatial order until a shortest path ending at an available station *1, *2 is found.

[0016] Fig. 3 and Fig. Four are exemplary trees of vehicle paths, derived from the abstraction of Fig. Figure 2 illustrates the shortest path determination according to some embodiments of the disclosure. As above, the tree diagrams of each path between each failed station X1, X2 and each available station *1, *2 can be drawn, with each branch of the tree representing a different unique path. Fig. Figure 3 illustrates a tree of paths between the failed station X1 and the available stations *1 and *2. The tree representation of Fig. 3 can be drawn by traversing every possible path from the failed station X1 and recording its path segments in sequence. For example, the paths can extend left and right starting from station X1 (in the view of Fig. 2), i.e., paths can begin by traversing path segment V2, then either path segment H1 or H2. The leftmost branch thus extends along the leftmost outer edge of the path layout of Fig. 2 to station * 1, following path H1 - V1 - V8 - V10 - V12 - H13 - V15. Another path may diverge after segment H13 towards station *2, following branch H14 - H15 - H16 - V18. The next branch may diverge after segment V8, following the middle line of Fig. 2 extend and upwards to station *2, following path H7 - H8 - H9 - H10 - H11 - H12 - V11 - V13 - H18 - H17 - V18. The next branch may diverge after segment H12, extending downwards and along the lower line of Fig. 2 extend, following path V9 - V7 - H6 - H5 - H4 - H3 - H2 - H1.... It can be observed that this path runs along the far left edge of Fig. 2 continues to both stations * 1 and *2, although it is longer than previously described paths.

[0017] In some embodiments of the disclosure, such paths can simply be followed and added to the tree in their entirety, even though it can already be observed that they are longer than other paths. However, in other embodiments of the disclosure, such paths can be terminated or removed from the tree based on arbitrary criteria indicating that they do not follow a shortest path. For example, paths that exceed a certain predetermined length or number of path segments can be pruned or removed from the tree. This predetermined length might be, for example, a length greater than a previously determined branch or path, a preset path length threshold, or any other value indicating an excessively long and therefore unsuitable path. Alternatively, paths that have a significant segment (e.g.,Path segments larger than a predetermined number of path segments) that extend spatially in one direction away from each of the target stations * 1 or *2, are discarded or removed from the tree.

[0018] The rightmost paths taken from segment V2 can be determined similarly, whereby a path from segment V2 extends to the right and along the far right edge of the path layout of Fig. 2 extends upwards to station *2, following the path H2 - H3 - H4 - H5 - H6 - V7 - V9 - V11 - V13 - H18 - H17 - V18. Another path diverges after segment V9 and extends along the middle row of Fig. 2, then upwards to station * 1, following the path H12 - H11 - H10 - H9 - H8 - H7 - V10 - V12 - H13 - V15. Another path diverges from this one after segment H7, extending downwards and following the path V8 - V1 - H1 - H2, and so on. As above, it can be observed that this last path continues to form a path that is longer than the previously described paths. This path can therefore be traced in its entirety and added to the tree, even though it can already be observed that it is longer than other paths. Alternatively, this path can be pruned or removed from the tree based on any criteria, such as its excessive length.

[0019] After forming, each branch of the tree can be... Fig. 3 are traversed in sequence, e.g., from left to right, to determine the shortest path or branch leading to station *1 or *2. For example, a system can analyze the tree structure of Fig. 3. Analyze by first traversing the leftmost path or branch of the tree, which is described as a path with a length of 8 segments and ending at station *1. The system can then traverse the path or branch closest to the leftmost path that diverges from the leftmost path after segment H13. This path can be determined to have a length of 11 segments and end at station *2. The system can then traverse the next path to the right in Fig. The system traverses path 3 to determine that it has a length of 16 segments, ending at station *2. The system can then traverse the next path to the right (branching from the previous path after segment H12), calculating its length or determining that its length is excessive, as above. For the remaining paths, ordered from left to right, it can similarly be determined that they have 1) an excessive length, 2) a length of 18 segments ending at station *1, and 3) a length of 13 segments ending at station *2. Accordingly, the shortest path found is the leftmost path with a length of 8 segments, extending from station X1 to station *1. That is, the shortest path from station X1 to either station *1 or *2 extends along the leftmost edge of the graph of Fig. 2, to end at station * 1.

[0020] Fig. Figure 4 illustrates a tree of paths between the failed station X2 and the available stations *1, *2. As in Fig. 3 can the tree structure of Fig. 4. The possible paths between station X2 and each available station *1, *2 can be constructed by plotting them. For example, a first path from station X2 can be constructed along the middle horizontal path of Fig. Continue to the left at segment 2 and, after segment H7, downwards, following the path V20 - H10 - H9 - H8 - H7 - V8 - V1 - H1 - H2 - H3, etc. As described above, it can be observed that this path continues to form a path that can be considered excessively long. This path can therefore be traced in its entirety and added to the tree, even though it can be observed to be longer than other paths. Alternatively, this path can be pruned or removed from the tree (or not added) based on any criteria, such as its excessive length. The next path can be the one that continues upwards after segment H7 to station *1, following the path V10 - V12 - H13 - V15. The remaining paths extend to the right from station X2 instead of to the left and can be determined and plotted similarly to the previous paths. This includes the path H2 - H3 - V9 - V7 - H6 - H5, etc.and the path H2 - H3 - V8 - V13 - H18 - H17 - V18, which ends at station *2. Accordingly, the shortest path found is the rightmost path in . Fig. 4, which has a length of 8 segments and ends at station *2.

[0021] In this way, it can be observed that for this exemplary arrangement of charging stations, the shortest route for a vehicle located at station X1 is path V2 - H1 - V1 - V8 - V10 - V12 - H13 - V15 to the available station *1, and the shortest path for a vehicle located at station X2 is path V20 - H2 - H3 - V8 - V13 - H18 - H17 - V18 to the available station *2. Embodiments of the disclosure thus consider determining the shortest paths between failed and available charging stations by creating a tree or graph for each failed station that describes all possible paths between that station and the available stations. Branches of this tree can then be traversed in spatial order, e.g., from left to right, to determine the shortest branch or path.

[0022] It should be noted that the examples above employ a first-order depth search approach. This means that the branches of each tree are traversed in spatial order from one side to the other. However, any alternative order can be used; that is, the branches can be traversed in any sequence, as long as the shortest branch can be determined.

[0023] In some embodiments of the disclosure, certain shortest paths can further be analyzed for collision risk. Such an analysis can be performed in any way. As an example, certain shortest paths can be checked for common path segments that indicate an intersection between the two paths and thus a potential collision if vehicles travel along the two paths simultaneously. Alternatively, path lengths and vehicle speeds can be considered to determine whether vehicles on paths with intersecting segments can reach these segments at approximately the same time, thereby indicating the probability of a collision. Embodiments of the disclosure consider any method or approach for determining the probability of a collision for certain shortest paths.In some embodiments, a time delay can be implemented in the case where there is no pair of paths that do not intersect, in order to generate a collision-free path.

[0024] Fig. Figure 5 is a flowchart illustrating an exemplary process for optimally diverting vehicles from vehicle charging failures according to some embodiments of the disclosure. In particular, it summarizes Fig. 5 aspects of the above in connection with Fig. 1 to Fig. The process described in section 4 is summarized and further explained. Here, a vehicle charging system such as System 100 can have a number of vehicle chargers and vehicle paths between them to allow vehicles to travel from one charger to another. One or more sections of the system, such as the controller 330, can then detect failed vehicle chargers (step 500). The controller 330 can then determine the shortest vehicle paths between these failed chargers and each available vehicle charger (step 510). In particular, the controller 330 can track which chargers are currently occupied, e.g., currently charging a vehicle, and which are not. Available chargers can be those that have no vehicle in their box or have a sufficiently charged vehicle in their box. In the latter case, in some embodiments of the disclosure, the controller 330 can instruct these vehicles to release the box, e.g.,to move out of the charging depot. In some embodiments, the controller can use data analytics and machine learning algorithms to predict when a charging station might fail due to overuse. For example, based on past failure data, the controller can identify that a charging station may be nearing an overuse threshold and determine that the charging station may fail within a short timeframe. Following this determination, the controller can perform the following steps to move a current vehicle from the identified charging stations to an available charging station and send instructions to the identified charging station to be repaired or serviced.

[0025] As above, the controller can determine 330 shortest paths between the detected failed chargers and any available chargers by building a layout of charger locations and paths between them, chargers such as the one in Fig. 2 shown. Shorter paths between the specific failed and available chargers can then be determined as above by creating a tree of possible paths between these specific chargers and traversing each branch of the tree to determine its length, with the shortest branches representing the shortest paths. In some embodiments, the shortest paths are predetermined and stored in a memory, and the controller 330 retrieves the shortest paths from the memory. The controller 330 can then direct vehicles directly from detected failed chargers to the available chargers along the determined shortest vehicle paths (step 520). In some embodiments of the disclosure, the vehicles in question may be autonomous vehicles, and the controller 330 can instruct the vehicles on the route to navigate to follow the determined shortest paths.Alternatively, the vehicles in question may be vehicles that are not capable of autonomous navigation, and the controller 330 may instruct drivers of the vehicles via a user interface of a display device (e.g., driver's mobile device or vehicle driver display), audio instructions, or other navigational means regarding routes they should take when their vehicles are driven from failed chargers to available chargers.

[0026] Fig. Figure 6 is a flowchart illustrating an exemplary process for collision avoidance in the event of vehicle charger failures according to some embodiments of the disclosure. As above, once the controller 330 determines shortest paths between failed and available chargers, in some embodiments it can also determine whether any pairs of these specific paths intersect in order to prevent or reduce the collision risk. Here, the controller 330 can first determine a number of vehicle paths between failed and available chargers (step 600), as above. The controller 330 can then check whether each of these paths presents potential collision risks. As above, specific shortest paths can be checked for common path segments that indicate an intersection between the two paths and thus a potential collision if vehicles traverse the two paths simultaneously.Alternatively, path lengths and vehicle speeds can be considered to determine whether vehicles on paths with intersecting segments can reach these segments at approximately the same time, thus indicating the probability of a collision. Embodiments of the disclosure consider each method or approach for determining the probability of a collision for certain shortest paths. Accordingly, paths that are considered to be intersecting or otherwise posing a collision risk are removed as shortest path candidates (step 610). Once intersecting paths have been removed, the shortest remaining paths are selected. That is, the controller 330 selects the shortest paths from these specific vehicle paths that do not intersect or otherwise pose a collision risk (step 620).The controller 330 can facilitate a vehicle's navigation to an available charger via the shortest, unobstructed path by sending instructions and an internal map to the driver's mobile device (step 630). In some embodiments, the vehicle may be autonomous; in this case, the controller 330 can cause the autonomous vehicle to move to the available charger by providing instructions to the vehicle to display the shortest route on an embedded navigation system and user interface. In some embodiments, the controller 330 can select an optimal path for the vehicle to take to an available charger, which may include the shortest path, the shortest unobstructed path, the fastest path, or the quickest unobstructed path. In this way, vehicles are guided more efficiently to available chargers while avoiding the risk of collision.

[0027] In some embodiments of the disclosure, systems and methods are described herein for an electric vehicle fleet management system which further manages the charging of an electric vehicle fleet according to the number of available chargers (taking into account failed chargers), the number of vehicles that need to be charged, and their charging times. Fig. Figure 7 is a flowchart illustrating an exemplary process for managing the charging of multiple vehicles according to some embodiments of the present disclosure. As in Fig. 5. A vehicle charging system, such as System 100, can have a number of vehicle chargers and vehicle paths between them to allow vehicles to move from one charger to another. The controller 330 can then generate a list of vehicles ordered according to their charging status (step 700). More specifically, the controller 330 can order the vehicles 120 of a System 100, such as a charging depot, according to the priority with which they should be charged, and then move vehicles to available chargers according to their priority. In particular, the controller 330 can receive information that includes the amount of charge each vehicle in a depot needs, such as the amount of charge required for the next day's tasks.The controller 330 can then determine the current charging level of each vehicle and, in turn, the remaining charging time for each vehicle based on the difference between the required charge, the current charge, and the charging rate of the system 100's chargers. In this way, the controller 330 determines the remaining charging time for each vehicle 120 and can generate a list of these vehicles 120 ordered by their remaining charging time; for example, vehicles 120 with the longest remaining charging times are listed first.

[0028] System 100 can thus charge vehicles 120, for example, to ensure fleet readiness by a specific predetermined deadline, such as the start of the next workday. Controller 330 can then identify available vehicle chargers (step 710). Those vehicles 120 that are sufficiently charged can be moved out of System 100, making their charging station available. Controller 330 can also detect failed vehicle chargers in a known manner (step 720) and route these vehicles from identified failed chargers to available chargers in order of priority (step 730), so that vehicles 120 with the highest priority are routed to new chargers first. The vehicles 120 are routed to available chargers along the shortest paths as described above, further minimizing downtime due to charger failures and reducing charging times caused by such failures.

[0029] Fig. Figure 8 is a block diagram of an illustrative device for performing optimal vehicle path rerouting as a result of vehicle charger failures according to some embodiments of the disclosure. Fig.Figure 8 is a generalized embodiment of an illustrative controller 330 designed for use according to embodiments of the disclosure. Here, a device 800 can serve as a controller 330 of the system 100. The device 800 can receive data via I / O paths 802 and 804. The I / O path 802 can receive data from the charging stations 130 and transformers 110 and transmit instructions, while the I / O path 804 can exchange data and commands with remote devices such as remote servers and / or storage. The device 800 has a control switching logic 806, which includes a processing switching logic 808 and a storage 810. In some embodiments of the disclosure, the I / O path 802 of the controller 330 enables communication with vehicles 120, either through charging stations 130 or directly with the vehicles 120 themselves, such as via a wireless communication link.Accordingly, in some embodiments of the disclosure of the controller 330, the I / O path 802 enables the control system 330 to be instructed, including instructions to navigate from failed to available chargers to enter / exit the system 100, and the like.

[0030] The control switching logic 806 can be based on any suitable processing switching logic, such as the processing switching logic 808. As mentioned herein, a processing switching circuit arrangement is understood to be a circuit arrangement based on one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc., and may include a multi-core processor (e.g., dual-core, quad-core, hexa-core, or any number of cores). In some embodiments, the processing switching logic may be distributed across multiple separate processors or processing units, for example, across multiple processors of the same type of processing unit (e.g., two Intel Core i7 processors) or across multiple different processors (e.g., one Intel Core i5 processor and one Intel Core i7 processor).In some embodiments, the control switching logic 806 executes instructions for carrying out the vehicle fleet charging optimization processes described herein.

[0031] Memory can be an electronic storage device provided as storage 810, which is part of the control switching logic 806. As stated herein, the term "electronic storage device" or "storage device" means any device for storing electronic data, computer software, or firmware, such as random access memory, read-only memory, hard disks, optical drives, digital video disc recorders (DVD recorders), compact disc recorders (CD recorders), Blu-ray disc recorders (BD recorders), Blu-ray 3D disc recorders, digital video recorders (DVRs, sometimes called personal video recorders or PVRs), solid-state devices, quantum storage devices, game consoles, game media, or other suitable fixed or removable storage devices, and / or any combination thereof.Storage 810 can be used to store various instructions for executing any of the procedures and processes described herein. Non-volatile memory can also be used (e.g., to start a startup routine and other instructions). Cloud-based storage can be used in addition to or instead of Storage 810.

[0032] Memory 810 is a memory that stores a number of programs for execution by the processing logic 808. Specifically, memory 810 can store a charger control module 812 for controlling the operation of each vehicle charger and detecting failed chargers, a vehicle control module 814 for instructing vehicles or drivers to follow certain shortest paths, and a path / time control module 816 for determining shortest paths and detecting paths that present potential collision risks. Each of the modules 812, 814, and 816 contains instructions for performing the functions described above when executed by the processing logic 808.

[0033] The foregoing description employed specific nomenclature for explanatory purposes, in order to provide a thorough understanding of the disclosure. However, it is obvious to the person skilled in the art that the specific details are not necessary to implement the methods and systems of the disclosure. Thus, the foregoing descriptions of specific embodiments of the present invention are provided for illustrative and descriptive purposes. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed. With regard to the above teachings, many modifications and variations are possible. For example, paths can be determined for any electric vehicle, autonomous or otherwise. Paths that pose a collision risk can be removed or included as needed.The embodiments were chosen and described to best illustrate the principles of the invention and its practical applications, thereby enabling other skilled persons to make the best use of the methods and systems disclosed and of various embodiments with different modifications suitable for the particular intended use. In addition, different features of the various embodiments, disclosed or otherwise, can be mixed and adapted or otherwise combined to create further embodiments considered by the disclosure.

Claims

[1] Method for managing vehicle charging for a vehicle charging system comprising a plurality of vehicle chargers and a plurality of vehicle paths extending between them to enable vehicles to travel from one of the vehicle chargers to another, the method comprising: Detecting a failed vehicle charger; using processing switching logic, determining an optimal vehicle path between the failed vehicle charger and an available vehicle charger; and Providing an instruction for a vehicle to move from the failed vehicle charger to the available vehicle charger along the determined optimal vehicle path. [2] Method according to claim 1, wherein: The detection also includes the detection of defective vehicle chargers; and The determination further comprises, for each failed vehicle charger, determining a shortest of the vehicle paths between the failed vehicle charger and an available vehicle charger, wherein each determined shortest of the vehicle paths is a path between one of the failed vehicle chargers and a different one of the available vehicle chargers. [3] Method according to claim 2, wherein none of the determined shortest vehicle paths intersect. [4] Method according to claim 1, wherein the determining further comprises: Determining a multitude of vehicle paths between the failed vehicle charger and the available vehicle charger; Determining the shortest of the many possible vehicle paths; and Selecting the shortest of the vehicle paths as the determined shortest of the multitude of vehicle paths. [5] Method according to claim 4, wherein determining a plurality of vehicle paths further comprises determining which vehicle paths of the plurality of vehicle paths do not intersect at least one other of the plurality of vehicle paths, and wherein determining a shortest of the plurality of vehicle paths further comprises determining the shortest of the plurality of vehicle paths from the vehicle paths of the plurality of vehicle paths that do not intersect any other of the plurality of vehicle paths. [6] Method according to claim 1, wherein the vehicles are autonomous vehicles. [7] Method according to claim 6, wherein the guiding further comprises transmitting an instruction to one of the autonomous vehicles to navigate from the failed vehicle charger to the available vehicle charger along the determined shortest of the vehicle paths. [8] Method for managing vehicle charging for a vehicle charging system having a plurality of vehicle chargers and a plurality of vehicle paths extending between them so that vehicles can travel from one of the vehicle chargers to another, the method comprising: Generating a list of vehicles sorted according to their charging status; Identifying available vehicle chargers; Detecting failed vehicle chargers; and Using processing switching logic, routing, in the order of the generated list, some of the vehicles to the failed vehicle chargers, in order to move from the failed vehicle chargers to the available vehicle chargers. [9] Method according to claim 8, wherein the vehicles in the list are further ordered according to a target load quantity. [10] Method according to claim 8, further comprising guiding charged vehicles away from their respective vehicle chargers in order to create the available vehicle chargers. [11] Method according to claim 8, further comprising determining the shortest of the vehicle paths between the failed vehicle chargers and the available vehicle chargers, wherein the guiding further comprises guiding some of the vehicles at the failed vehicle chargers to move from the failed vehicle chargers to the available vehicle chargers along the determined shortest of the vehicle paths. [12] Method according to claim 11, wherein determining the shortest of the vehicle paths further comprises determining the shortest of the vehicle paths that do not intersect, and wherein guiding further comprises guiding some of the vehicles at the failed vehicle chargers to move from the failed vehicle chargers to the available vehicle chargers along the determined shortest of the vehicle paths that do not intersect. [13] Method according to claim 8, wherein the vehicles are autonomous vehicles. [14] Method according to claim 13, wherein the guiding further comprises transmitting instructions to the autonomous vehicles in the order of the generated list to navigate from the failed vehicle chargers to the available vehicle chargers. [15] System for managing vehicle charging with a plurality of vehicle chargers and a plurality of vehicle paths extending between them to enable vehicles to travel from one of the vehicle chargers to another, the system comprising: a storage device; and Control switching logic configured to: Detecting failed vehicle chargers; Determine the shortest of the vehicle paths between the failed vehicle chargers and available vehicle chargers; and Guiding vehicles to drive from the failed vehicle chargers to the available vehicle chargers along the determined shortest vehicle paths. [16] System according to claim 15, wherein the control switching logic is configured to determine the shortest of the vehicle paths by determining, for each failed vehicle charger, a shortest of the vehicle paths between the failed vehicle charger and an available vehicle charger, wherein each determined shortest of the vehicle paths determines a path between one of the failed vehicle chargers and a different one of the available vehicle chargers. [17] System according to claim 16, wherein none of the determined shortest vehicle paths intersect. [18] System according to claim 15: wherein the control switching logic is further configured to generate a list of vehicles ordered according to their charge status; and the control switching logic is configured to direct the vehicles by directing some of the vehicles to the failed vehicle chargers in the order of the generated list, in order to move from the failed vehicle chargers to the available vehicle chargers. [19] System according to claim 18, wherein the control switching logic is configured to: Determining the shortest of the vehicle paths by determining the shortest of the vehicle paths that do not intersect; and Guiding the vehicles by further directing some of the vehicles to the failed vehicle chargers in order to move from the failed vehicle chargers to the available vehicle chargers along the determined shortest of the vehicle paths which do not intersect. [20] System according to claim 15, wherein the vehicles in the list are further ordered according to a target load quantity.

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