Platooning of electric vehicles to improve fleet availability

Abstract

Electric vehicles arriving at a charging station transmit their state of charge, capacity, and departure time to a computer system. Vehicles are sorted into tiers based on departure time, and within each tier, they are sorted by charging time based on state of charge and capacity. The vehicles are then assigned to queues based on the tiers and rankings within the tiers, giving priority to vehicles with faster departure times and shorter charging times. In the case of multiple queues, vehicles with shorter charging times can be assigned to the first queue, while the remaining vehicles are assigned to one or more other queues. Charging stations may have different capacities, and vehicles with higher priority based on faster departure times and shorter charging times can be assigned to faster chargers.

Description

background Technical Field

[0002] The present invention relates to wireless charging of electric vehicles, particularly autonomous vehicles. Background Art

[0004] Electric vehicles offer significant advantages in terms of emissions and energy efficiency. Advances in battery technology have improved their range and overall practicality. A drawback of electric vehicles is their long charging times, which can be many times longer than those of combustion-powered vehicles. A convenient option for recharging electric vehicles is wireless charging, where an induction coil at a charging station induces a current in a corresponding coil on the vehicle, which is then used to charge the vehicle's battery.

[0005] The systems and methods disclosed herein provide improved methods for implementing charging of electric vehicles, particularly autonomous electric vehicles. Summary of the Invention

[0006] A computer system may implement a method comprising: receiving charging data from a plurality of vehicles; receiving departure time data from the plurality of vehicles; determining a permutation of the plurality of vehicles based on both the charging data and the departure time data; and assigning the vehicles to one or more queues to access one or more charging stations based on the permutation. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order that the advantages of the present invention will be readily understood, a more particular description of the invention, briefly described above, will be rendered by reference to specific embodiments that are illustrated in the accompanying drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings, in which:

[0008] Figure 1A is a schematic block diagram of components implementing an autonomous vehicle for use in accordance with an embodiment of the present invention;

[0009] Figure 1B is a schematic block diagram illustrating a wireless charging station;

[0010] Figure 2 is a schematic block diagram of an exemplary computing device suitable for implementing methods according to embodiments of the present invention;

[0011] Figure 3 is a process flow diagram of a method for arranging vehicles into a queue at a charging station according to an embodiment of the present invention;

[0012] Figure 4 is a process flow diagram illustrating hierarchical placement of vehicles in a platoon according to an embodiment of the present invention; and

[0013] Figure 5 is a process flow diagram of a method for managing multiple queues of vehicles assigned to multiple charging stations according to an embodiment of the present invention; and

[0014] Figure 6 is a diagram illustrating a process of managing multiple queues of multiple charging stations according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] refer to Figure 1A The vehicle used in accordance with the methods disclosed herein can be a low-capacity vehicle, such as a sedan or other small vehicle, or a high-capacity vehicle, such as a truck, bus, van, large sport utility vehicle (SUV), or the like.

[0016] The vehicle may include any vehicle known in the art. The vehicle may have all the structure and features of any vehicle known in the art, including wheels, a drive train coupled to the wheels, an engine coupled to the drive train, a steering system, a braking system, and other systems known in the art to be included in a vehicle.

[0017] As discussed in more detail herein, the vehicle's controller 102 can perform autonomous navigation and collision avoidance. The controller 102 can receive one or more outputs from one or more external sensors 104. For example, one or more cameras 106a can be mounted to the vehicle and output received image streams to the controller 102.

[0018] The external sensors 104 may include sensors such as an ultrasonic sensor 106 b , a RADAR (Radio Detection and Ranging) sensor 106 c , a LIDAR (Light Detection and Ranging) sensor 106 d , a SONAR (Sound Navigation and Ranging) sensor 106 e , and the like.

[0019] The controller 102 may execute an autonomous operation module 108 that receives output from the external sensors 104. The autonomous operation module 108 may include an obstacle recognition module 110a, a collision prediction module 110b, and a decision module 110c. The obstacle recognition module 110a analyzes the output from the external sensors and identifies potential obstacles, including people, animals, vehicles, buildings, curbs, and other objects and structures. Specifically, the obstacle recognition module 110a may identify vehicle images in the sensor output.

[0020] Collision prediction module 110b predicts which obstacle images may collide with the vehicle based on its current trajectory or currently projected path. Collision prediction module 110b can assess the likelihood of collision with objects identified by obstacle recognition module 110a. Decision module 110c can make decisions such as stopping, accelerating, and turning to avoid obstacles. The manner in which collision prediction module 110b predicts potential collisions and the manner in which decision module 110c takes actions to avoid potential collisions can be based on any method or system known in the field of autonomous vehicles.

[0021] The decision module 110c can control the trajectory of the vehicle by actuating one or more actuators 112 that control the direction and speed of the vehicle. For example, the actuators 112 can include a steering actuator 114a, an acceleration actuator 114b, and a brake actuator 114c. The configuration of the actuators 114a to 114c can be based on any implementation of such actuators known in the field of autonomous vehicles.

[0022] In the embodiments disclosed herein, the autonomous operation module 108 may perform autonomous navigation to a designated location, autonomous parking, and other autonomous driving activities known in the art.

[0023] The controller 102 may maintain and transmit various charging parameters 116 describing the battery of the electric vehicle. For example, the state of charge (SOC) 118a may indicate the amount of energy remaining in the vehicle battery, such as as a percentage of the total charge, a kilowatt-hour (kWH) value, an ampere-hour (Ah) value, a kilojoule (kJ) value, or some other measure of remaining energy.

[0024] The charging parameters 116 may also include the capacity 118b of the battery, which may also be expressed in kWH, Ah, kJ, or some other measure of energy or charge.

[0025] The charging parameters 116 may also include a charging rate 118c. The charging rate 118c may indicate the speed at which the battery can be charged, such as in the form of a C-rate (coulomb rate), kilowatts (kW), amperes, joules, or some other rate at which the battery can receive energy or current as is known in the art of battery design.

[0026] refer to Figure 1B , the vehicle 120 may include the above Figure 1A In addition, the vehicle 120 may include an induction coil 122 coupled to a rectifier 124 that converts the alternating current in the coil 122 into direct current that is supplied to a battery 126 for charging. The components 122, 124, 126 may be implemented according to any method known in the art for performing wireless charging.

[0027] The charging station may include one or more inductive coils 128 driven by a power source 130 (such as a utility grid, photovoltaic panels, or some other power source). As is known in the art, the alternating current passing through the inductive coils 128 generates a magnetic field that induces a current in the coil 122 located above the coil 128.

[0028] A charge controller coupled to one or both of the coil 128 and the battery 126 may be used to implement Figure 1B The structure shown in FIG. 1 is used to control the charging rate to ensure safety and extend battery life. When charging is complete, the charging controller can provide an indication to the controller 102.

[0029] Wireless charging stations are particularly useful for autonomous vehicles because no human operator is required to plug in the vehicle for charging.

[0030] Figure 2 is a block diagram illustrating an exemplary computing device 200. Computing device 200 may be used to perform various processes, such as the processes discussed herein for managing vehicle assignment to queue at a charging facility. Controller 102 may have some or all of the attributes of computing device 200.

[0031] The computing device 200 includes one or more processors 202, one or more memory devices 204, one or more interfaces 206, one or more mass storage devices 208, one or more input / output (I / O) devices 210, and a display device 230, all of which are coupled to a bus 212. The one or more processors 202 include one or more processors or controllers that execute instructions stored in the one or more memory devices 204 and / or the one or more mass storage devices 208. The one or more processors 202 may also include various types of computer-readable media, such as cache memory.

[0032] The one or more memory devices 204 include various computer-readable media, such as volatile memory (e.g., random access memory (RAM) 214) and / or non-volatile memory (e.g., read-only memory (ROM) 216). The one or more memory devices 204 may also include a rewritable ROM, such as flash memory.

[0033] The one or more mass storage devices 208 include various computer-readable media, such as magnetic tapes, magnetic disks, optical disks, solid-state memory (e.g., flash memory), and the like. Figure 2As shown, the specific mass storage device is a hard drive 224. The one or more mass storage devices 208 may also include various drives to enable reading from and / or writing to various computer-readable media. The one or more mass storage devices 208 may include removable media 226 and / or non-removable media.

[0034] The one or more I / O devices 210 include various devices that allow data and / or other information to be input to or retrieved from the computing device 200. Exemplary I / O device(s) 210 include a cursor control device, a keyboard, a keypad, a microphone, a monitor or other display device, a speaker, a printer, a network interface card, a modem, a lens, a CCD or other image capture device, and the like.

[0035] Display device 230 includes any type of device capable of displaying information to one or more users of computing device 200. Examples of display device 230 include a monitor, a display terminal, a video projection device, and the like.

[0036] The one or more interfaces 206 include various interfaces that allow the computing device 200 to interact with other systems, devices, or computing environments. One or more exemplary interfaces 206 include any number of different network interfaces 220, such as interfaces to a local area network (LAN), a wide area network (WAN), a wireless network, and the Internet. One or more other interfaces include a user interface 218 and a peripheral device interface 222. The one or more interfaces 206 may also include one or more peripheral interfaces, such as interfaces for a printer, a pointing device (mouse, trackpad, etc.), a keyboard, and the like.

[0037] The bus 212 allows the one or more processors 202, the one or more memory devices 204, the one or more interfaces 206, the one or more mass storage devices 208, the one or more I / O devices 210, and the display device 230 to communicate with each other and with other devices or components coupled to the bus 212. The bus 212 represents one or more of several types of bus structures, such as a system bus, a PCI bus, an IEEE 1394 bus, a USB bus, and the like.

[0038] For illustrative purposes, programs and other executable program components are shown herein as discrete blocks, but it should be understood that such programs and components may reside at various times in different storage components of the computing device 200 and be executed by one or more processors 202. Alternatively, the systems and processes described herein may be implemented in hardware or a combination of hardware, software, and / or firmware. For example, one or more application specific integrated circuits (ASICs) may be programmed to perform one or more of the systems and processes described herein.

[0039] refer to Figure 3 The illustrated method 300 can be performed by computer system 200 on data received from multiple vehicles arriving at a charging station, the charging station including one or more queues, each queue having a corresponding charging coil 128. Method 300 assumes that multiple vehicles can arrive at a charging station at or approximately the same time. Therefore, method 300 can be performed on multiple vehicles. When executing method 300, a vehicle can be located in a waiting queue or entrance to a charging station, or en route to a charging station and assigned a position in the queue to utilize one or more charging stations according to method 300.

[0040] When the vehicle arrives at the charging station or is within communication range of the charging station, the vehicle may transmit charging data to the computer system 200, such as using a wireless communication protocol such as DSRC (digital short range communication), WI-FI, Bluetooth, cellular data communication, or some other wireless communication method. The charging data may include some or all of the charging parameters 116. The vehicle may be part of a fleet that traverses a predetermined route and / or arrives at designated pickup and drop-off locations. Thus, each vehicle may have an expected departure time at which the vehicle must depart to arrive at the predetermined location. Thus, the vehicle may transmit this departure time along with the charging data using a wireless vehicle-to-vehicle (V2V) or vehicle-to-everything (V2X) communication protocol. A V2X protocol may also be used to execute instructions from the computer system 200 to the vehicle.

[0041] The computer system 200 receives 302 the charging data and departure time of the vehicles. The computer system 200 can then sort 304 the vehicles according to departure time, for example, arranging the vehicles according to departure time from fastest to latest or from latest to fastest.

[0042] The computer system 200 may then assign 306 the vehicles to the tiers. Each tier may have a fixed size or may be based on a fixed threshold. For example, the N vehicles with the N fastest departure times may be assigned to the first tier and not considered further, the M (M equal to or not equal to N) vehicles of the remaining vehicles with the fastest departure times may be assigned to the second tier and not considered further, and so on for any number of tiers until no vehicles remain to be assigned to a tier.

[0043] In an alternative approach, a first rank is filled with vehicles whose departure times are below a first threshold, a second rank is filled with vehicles whose departure times are between the first threshold and a second threshold that is higher than the first threshold, and so on until no vehicles remain to be assigned to a rank. The thresholds may be predetermined static values or functions based on the departure times of the vehicles.

[0044] In a simple embodiment, only two levels are used. In other embodiments, three or more levels may be used.

[0045] Within each tier, vehicles assigned to that tier can be sorted 308 based on charging time. The charging time for the vehicle can be calculated based on the charging data. Specifically, for a given SOC, capacity, and charging rate of the battery and the power output of the charging station, the time to charge the battery can be estimated using any method known in the art for rechargeable batteries. For example, the charging time T can be calculated as T = [(100% - SOC) * battery capacity] / (wireless charger output rate), where the battery capacity is in ampere hours and the wireless charger output rate is expressed in amperes.

[0046] The charging time may be the time to fully charge, or the time to charge to a level sufficient to complete the desired route plus an excess charge for contingencies.

[0047] The vehicle may then be assigned 310 a queue position based on the rank assignment 306 and the ranking 308. For example, Figure 4 As shown in FIG, vehicles 400a, 400b assigned to the first level 402a are placed in the queue first. Vehicle 400a with the shortest charging time is placed in the queue first, followed by vehicle 400b with a longer charging time.

[0048] The vehicles 400c, 400d in the second level 402b are placed behind the vehicles in the first level 402a. Likewise, the first vehicle 400c for the second level 402b has a shorter charging time than the vehicle 400d.

[0049] The example shown includes only two classes, and each class has only two vehicles. However, any number of vehicles per class and any number of classes can be implemented using the above method.

[0050] Once the permutation is assigned 310, the computer system can instruct the vehicles to queue up in a queue according to the permutation. This can be accomplished by sending instructions to the vehicles to queue up one at a time according to the permutation. Alternatively, the permutation can be transmitted to all vehicles, which will then use V2V (vehicle-to-vehicle) communication to autonomously arrange themselves in a queue according to the permutation.

[0051] Method 300 may be performed repeatedly as vehicles arrive at a charging station, such as every N minutes or once a minimum number of vehicles notify computer system 200 of an intent to charge at a charging station, whichever occurs first.

[0052] Note that if only one vehicle needs to be added to the queue or the number of vehicles is less than or equal to the number of currently unused charging stations, the vehicles can simply be assigned to charging stations randomly or on a first-come, first-served basis, and the prioritization according to method 300 can be omitted. Alternatively, the number of charging stations can be indicated to the vehicle as being greater than or equal to the number of vehicles that have indicated their intent to use a charging station. The vehicle can then autonomously select an unoccupied charging station.

[0053] However, in situations where the charging stations have different capacities (e.g., some charging stations are capable of charging faster than others), the assignment may be based on the charging data and departure time even if the number of charging stations is less than or equal to the number of vehicles that have indicated an intent to recharge but have not yet been assigned to a charging station.

[0054] In this case, vehicles with earlier departure times will be assigned to faster chargers than vehicles with later departure times. Within a certain level, vehicles with faster charging times will be assigned to faster chargers than vehicles with slower charging times.

[0055] Figure 5 A method 500 is shown for assigning vehicles to a plurality of queues of corresponding charging stations. The method 500 may be performed by the computer system 200 on a plurality of vehicles that have indicated an intent to charge at a charging station but have not yet been assigned to a queue.

[0056] Method 500 may include receiving 302 charging data and departure times of vehicles, sorting 304 vehicles according to departure times, assigning 306 vehicles to tiers, and sorting 308 vehicles within tiers according to charging times. Steps 302 through 308 may be performed in the same manner as for method 300.

[0057] The method 500 may also include selecting 502 a queue for each vehicle and assigning 504 each vehicle to a position within each queue. The assigning 502, 504 may be performed using various methods.

[0058] In one approach, one or more queues are reserved for vehicles with fast charging times (e.g., "fast lanes"). Thus, vehicles with charging times below a threshold can be assigned to the queues, such as in a tiered arrangement, e.g., vehicles in a first tier that meet the charging time threshold are placed in the queue first, followed by vehicles in a second tier that meet the charging time threshold, and so on for any number of tiers.

[0059] As mentioned above, in situations where there are multiple charging stations, they may have multiple charging rates. Therefore, in some embodiments, a reserved queue may be used for the charger with the fastest charging rate. Therefore, in situations where there are multiple charging stations with multiple charging rates, a vehicle may have multiple charging times depending on the charger used. In some embodiments, the vehicle's charging time is calculated based on the charging rate of the fastest charger. In this way, vehicles that can utilize faster charging rates are given higher priority and are more likely to be assigned to faster chargers.

[0060] In another approach, vehicles are assigned to queues in a round-robin fashion, e.g., vehicles from a first tier are added to the queue in a round-robin fashion, and then vehicles from a second tier are added in the same manner, and so on for any number of tiers.

[0061] In another approach, each queue corresponds to a tier. Thus, first-tier vehicles are assigned to the first queue, second-tier vehicles to the second queue, and so on for any number of tiers. As mentioned above, in scenarios where there are multiple charging stations, they can have multiple charging rates. Thus, the first tier can be assigned to the fastest charger, the second tier to the second-fastest charger, and so on for any number of chargers.

[0062] The vehicles may be instructed to proceed to the assigned queues according to the assigned positions. As described above, this may include transmitting instructions sequentially for each queue or one at a time by transmitting the queue assignments and permutations to the vehicles and allowing the vehicles to communicate with each other to automatically arrange themselves into the assigned queues according to the assigned permutations.

[0063] Then, method 500 may include charging the vehicle at the charging station according to the queue of each charging station 506. The vehicle will then queue through the queue and depart after charging. In some cases, the vehicle may end charging before being fully charged, such as when the state of charge is sufficient to complete the scheduled trip and the vehicle needs to leave in order to arrive at the destination of the scheduled trip at a scheduled time.

[0064] Throughout the charging process 506, method 500 may include evaluating 508 whether a lower-priority vehicle in a first queue is in the same position or closer to the front of the queue than a higher-priority vehicle in an adjacent queue. In this case, priority may be based solely on charging time or departure time, or a combination of these factors. Charging time is a particularly suitable basis for prioritization.

[0065] This is Figure 6, where vehicles are arranged in queues 600a to 600c, each corresponding to a charging coil 602a to 602c. In this example, vehicle A is the first vehicle in queue 600a, and charging station 602a is currently unoccupied. In this example, vehicle B has a higher priority.

[0066] If the conditions of step 508 are met, the higher priority vehicle is instructed to move ahead of the lower priority vehicle 510. Figure 6 In the example shown, vehicle B would move in front of vehicle A in queue 600a and would use charging station 602a first.

[0067] To reduce the number of queue changes, queue changes can be limited to only those performed in the case shown in diagram 600: a position in the first queue that is above the charging coil is not currently occupied, and a vehicle in an adjacent queue (no intermediate queue) has a higher priority than the vehicle in the first queue that is closest to the charging coil but not yet above the charging coil.

[0068] In other embodiments, any time a space in front of a first vehicle becomes vacant due to a queue advancing in front of the first vehicle, a second, higher priority vehicle in an adjacent queue may be indicated and allowed to enter the space.

[0069] If the evaluation of step 508 is negative, no changes are made to the queue arrangement. Step 508 may be performed again periodically, such as upon completion of charging of one or more vehicles at the charging station, upon expiration of a time period, or within some threshold time before the expected completion of charging of a currently charging vehicle.

[0070] If it is discovered 512 that more vehicles have indicated a desire to use the charging station and have not yet been assigned to a queue, these vehicles may be assigned to a queue starting from step 302 .

[0071] Various modifications can be implemented to the above method. For example, an entity associated with a vehicle can pay a fee to obtain higher priority, such as being placed in a higher priority class (a lower class number in the above embodiment) or being placed closer to the front of a queue within a class. In another example, an entity associated with a vehicle can pay a fee to obtain an assignment to a faster charging station.

[0072] In some embodiments, the method can be performed or facilitated by a drone flying over a charging station and observing the positions of vehicles in and around the charging station. This information can then be used to assign vehicles to queues according to the methods described herein and to indicate paths to take to each queue to avoid collisions with other vehicles.

[0073] In some cases, vehicles may include solar panels to charge the vehicle's batteries. Thus, while waiting in the queue, the charging time for such vehicles may change (or decrease). Consequently, the priority of such vehicles may increase, resulting in reordering according to steps 508 and 510. In such cases, these vehicles may periodically retransmit their charging data (specifically, state of charge) to computer system 200 so that their priorities can be adjusted accordingly and used during iterations of step 508.

[0074] As is apparent from the above disclosure, vehicles with faster departure times and faster charging times are given higher priority. In this way, the availability of autonomous vehicles in the fleet is improved, and timely arrival of vehicles at their destinations is facilitated. The above prioritization method reduces the likelihood that vehicles with low state of charge and high capacity will cause delays to vehicles with urgent departure times and shorter charging times.

[0075] The above method is particularly useful for autonomous vehicles, but can also be implemented using manned vehicles or a mix of manned and autonomous vehicles. For example, an operator can be instructed to move to a position in a queue indicated according to the above method.

[0076] The above-described method is particularly suitable for vehicles operated by the same entity, as fairness considerations can be ignored for any individual vehicle to improve the availability of the entire fleet. However, the throughput increase may also be beneficial for vehicles owned and controlled by different entities. For example, unless the vehicle scheduling would result in a variance above a threshold (e.g., increased wait time or increased queue position) compared to a first-come, first-served schedule, a schedule according to the method described herein may be used, where the variance threshold is a predetermined value.

[0077] In the above disclosure, reference is made to the accompanying drawings, which form a part of the present disclosure and in which specific implementations of the present disclosure can be practiced are shown by way of illustration. It should be understood that other implementations can be utilized and structural changes can be made without departing from the scope of the present disclosure. References in the specification to "one embodiment", "embodiment", "example embodiment" and the like indicate that the embodiment described may include specific features, structures or characteristics, but every embodiment may not necessarily include the specific features, structures or characteristics. In addition, such phrases do not necessarily refer to the same embodiment. In addition, when specific features, structures or characteristics are described in conjunction with an embodiment, whether or not explicitly described, it is considered that it is within the knowledge of those skilled in the art to implement such features, structures or characteristics in conjunction with other embodiments.

[0078] Implementations of the systems, devices, and methods disclosed herein may include or utilize a dedicated or general-purpose computer including computer hardware (such as, for example, one or more processors and system memory discussed herein). Implementations within the scope of the present disclosure may also include physical and other computer-readable media for carrying or storing computer-executable instructions and / or data structures. Such computer-readable media may be any available medium that can be accessed by a general-purpose or special-purpose computer system. A computer-readable medium that stores computer-executable instructions is a computer storage medium (device). A computer-readable medium that carries computer-executable instructions is a transmission medium. Therefore, by way of example and not limitation, implementations of the present disclosure may include at least two distinct computer-readable media: a computer storage medium (device) and a transmission medium.

[0079] Computer storage media (devices) include RAM, ROM, EEPROM, CD-ROM, solid-state drives ("SSD") (e.g., RAM-based), flash memory, phase-change memory ("PCM"), other types of memory, other optical disk storage devices, magnetic disk storage devices or other magnetic storage devices, or any other medium that can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer.

[0080] The implementation of the device, system and method disclosed herein can communicate through a computer network." network " is defined as one or more data links that can transmit electronic data between a computer system and / or module and / or other electronic devices. When information is delivered to a computer by a network or another communication connection (hard wiring, wireless or hard wiring or wireless combination), the computer appropriately considers the connection as a transmission medium. Transmission medium may include a network and / or data link, which may be used to carry desired program code means in the form of computer executable instructions or data structures and may be accessed by a general or special-purpose computer. The above combination should also be included in the scope of computer-readable media.

[0081] Computer-executable instructions include instructions and data that, when executed in a processor, cause a general-purpose computer, a special-purpose computer, or a special-purpose processing device to perform a certain function or group of functions. Computer-executable instructions can be, for example, binary files, intermediate format instructions (such as assembly language), or even source code. Although the subject matter has been described in language specific to structural features and / or methodological actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the features or actions described above. Rather, the described features and actions are disclosed as example forms of implementing the claims.

[0082] Those skilled in the art will appreciate that the present disclosure can be practiced in a network computing environment using many types of computer system configurations, including built-in vehicle computers, personal computers, desktop computers, laptop computers, message processors, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile phones, PDAs, tablet computers, pagers, routers, switches, various storage devices, and the like. The present disclosure can also be practiced in a distributed system environment, where local and remote computer systems linked (by hardwired data links, wireless data links, or a combination of hardwired and wireless data links) over a network all perform tasks. In a distributed system environment, program modules can be located in both local and remote memory storage devices.

[0083] In addition, where appropriate, the functions described herein may be implemented in one or more of the following: hardware, software, firmware, digital components, or analog components. For example, one or more application specific integrated circuits (ASICs) may be programmed to perform one or more of the systems and processes described herein. Certain terms are used throughout the description and claims to refer to specific system components. Those skilled in the art will appreciate that components may be referred to by different names. This document is not intended to distinguish between components that have different names but the same function.

[0084] It should be noted that the sensor embodiments discussed above may include computer hardware, software, firmware, or any combination thereof to perform at least a portion of their functionality. For example, a sensor may include computer code configured to execute in one or more processors and may include hardware logic / circuitry controlled by the computer code. These exemplary devices are provided herein for illustrative purposes and are not intended to be limiting. The embodiments of the present disclosure may be implemented in other types of devices as known to one or more persons skilled in the relevant art.

[0085] At least some embodiments of the present disclosure relate to computer program products that include such logic (e.g., in the form of software) stored on any computer-usable medium. Such software, when executed on one or more data processing devices, causes the devices to operate as described herein.

[0086] Although various embodiments of the present disclosure have been described above, it should be understood that the embodiments are presented by way of example only and not by way of limitation. It will be clear to those skilled in the relevant art that various changes in form and detail can be made without departing from the spirit and scope of the present disclosure. Therefore, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should only be defined in accordance with the appended claims and their equivalents. The foregoing description has been presented for illustration and description purposes. It is not intended to be exhaustive or to limit the present disclosure to the precise form disclosed. In light of the above teachings, many modifications and variations are possible. In addition, it should be noted that any or all of the aforementioned optional implementations can be used in any desired combination to form additional hybrid implementations of the present disclosure.

Claims

1. A method for queuing vehicles for charging, comprising: receiving charging data from a plurality of vehicles; receiving departure time data from the plurality of vehicles; determining an arrangement of the plurality of vehicles based on both the charging data and the departure time data; as well as assigning the plurality of vehicles to a plurality of queues according to the arrangement to respectively access a plurality of charging stations; The method further includes calculating an estimated charging time for each vehicle of the plurality of vehicles based on the charging data; The method further comprises: assigning the plurality of vehicles to a first class and a second class, wherein the first class includes vehicles having a departure time below a first threshold and the second class includes vehicles having a departure time above the first threshold; Allocating the vehicles of the first level to a first queue and allocating the vehicles of the second level to a second queue; The method further comprises: (a) detecting that a first vehicle of the plurality of vehicles at a first position in a first queue in the plurality of queues has a shorter estimated charging time or a faster departure time than a second vehicle at a second position in a second queue in the plurality of queues, the second position being closer to the front of the second queue than the first position is to the front of the second queue; and In response to (a), the first vehicle is instructed to move in front of the second vehicle.

2. The method of claim 1, wherein the charging data for each of the plurality of vehicles includes a state of charge and a battery capacity; and Wherein determining the arrangement of the plurality of vehicles based on both the charging data and the departure time data comprises: calculating an estimated charging time for each of the plurality of vehicles based on the state of charge and battery capacity; as well as The arrangement of the plurality of vehicles is determined based on the estimated charging time and departure time data of the plurality of vehicles.

3. The method of claim 2, wherein the charging data for each of the plurality of vehicles further comprises a charging speed for each vehicle; and Calculating the estimated charging time for each vehicle includes calculating the estimated charging time based on the state of charge, battery capacity, and charging speed of each vehicle.

4. The method of claim 2, wherein determining the arrangement of the plurality of vehicles comprises: sorting the plurality of vehicles according to the departure time data; assigning the plurality of vehicles to classes according to the departure time data; For each tier, determining an order within the tier for assigning the vehicles according to their estimated charging times; and The plurality of vehicles are assigned to the plurality of queues such that the vehicles are arranged in rank and according to the intra-rank order within the rank.

5. The method of claim 2, wherein the charging stations used for the first queue have a faster charging speed than the charging stations used for the second queue. The method of claim 1 , wherein the plurality of vehicles are autonomous vehicles. 7 . The method of claim 1 , wherein receiving the charging data and the departure time data from the plurality of vehicles comprises receiving the charging data and the departure time data via a vehicle-to-vehicle communication protocol.

8. A system for queuing vehicles for charging, the system comprising one or more processing devices and one or more memory devices, the one or more memory devices operatively coupled to the one or more processing devices, the one or more memory devices storing executable code effective to cause the one or more processing devices to: receiving charging data from a plurality of vehicles; receiving departure time data from the plurality of vehicles; determining an arrangement of the plurality of vehicles based on both the charging data and the departure time data; as well as instructing the plurality of vehicles to join a plurality of queues according to the arrangement to respectively access a plurality of charging stations; wherein the executable code is further effective to cause the one or more processing devices to calculate an estimated charging time for each vehicle of the plurality of vehicles based on the charging data; wherein the executable code is further effective to cause the one or more processing devices to: assigning the plurality of vehicles to a first class and a second class, wherein the first class includes vehicles having a departure time below a first threshold and the second class includes vehicles having a departure time above the first threshold; Allocating the vehicles of the first level to a first queue and allocating the vehicles of the second level to a second queue; wherein the executable code is further effective to cause the one or more processing devices to: (a) detecting that a first vehicle of the plurality of vehicles at a first position in a first queue in the plurality of queues has a shorter estimated charging time or a faster departure time than a second vehicle at a second position in a second queue in the plurality of queues, the second position being closer to the front of the second queue than the first position is to the front of the second queue; as well as In response to (a), the first vehicle is instructed to move in front of the second vehicle.

9. The system of claim 8, wherein the charging data for each of the plurality of vehicles includes a state of charge and a battery capacity; and The executable code is further effective to cause the one or more processing devices to determine the arrangement of the plurality of vehicles based on both the charging data and the departure time data by: calculating an estimated charging time for each of the plurality of vehicles based on the state of charge and battery capacity; and The arrangement of the plurality of vehicles is determined based on the estimated charging time and departure time data of the plurality of vehicles.

10. The system of claim 9, wherein the charging data for each of the plurality of vehicles further comprises a charging speed for each vehicle; and Wherein the executable code is further effective to cause the one or more processing devices to calculate the estimated charging time for each vehicle including calculating the estimated charging time based on the state of charge, battery capacity, and charging speed of each vehicle.

11. The system of claim 9, wherein the executable code is further effective to cause the one or more processing devices to determine the arrangement of the plurality of vehicles by: sorting the plurality of vehicles according to the departure time data; assigning the plurality of vehicles to classes according to the departure time data; For each tier, determining an order within the tier for assigning the vehicles according to their estimated charging times; as well as The plurality of vehicles are assigned to the plurality of queues such that the vehicles are arranged in rank and according to the intra-rank order within the rank.

12. The system of claim 9, wherein the chargers for the first queue have a faster charging speed than the chargers for the second queue.

13. The system of claim 8, wherein the plurality of vehicles are autonomous vehicles.

14. The system of claim 8, wherein the executable code is further effective to cause the one or more processing devices to receive the charging data and the departure time data from the plurality of vehicles via a vehicle-to-vehicle communication protocol.

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