Method and apparatus for scheduling vehicle charging and shuttle vehicle charging system
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING JINGDONG YUANSHENG TECH CO LTD
- Filing Date
- 2024-11-27
- Publication Date
- 2026-05-29
Smart Images
Figure CN122114408A_ABST
Abstract
Description
Technical Field
[0001] Embodiments of this disclosure relate to the field of logistics technology, specifically to methods and apparatus for scheduling vehicle charging and shuttle charging systems. Background Technology
[0002] In a high-density storage system based on multiple shuttles, the entry and exit of bins are jointly handled by a cargo elevator and shuttles. Each shuttle moves horizontally within a certain layer of the rack, responsible for transporting bins back and forth between the layer buffer position and the storage position; the cargo elevator moves vertically, responsible for transporting bins between the layer buffer position and the conveyor line.
[0003] Each shelf level is equipped with a charging point, allowing shuttles to charge on their designated shelf without needing to switch shelves. A typical shuttle charging scheme involves setting a minimum battery level threshold; the shuttle charges when its battery level falls below this threshold and disconnects when fully charged. However, because multiple shuttles share a single charger, simultaneous charging often occurs, causing multiple shuttles to share the charger's current. The more shuttles there are, the lower the charging efficiency becomes. This not only impacts system efficiency but also increases charger costs.
[0004] To reduce the probability of multiple vehicles charging simultaneously, the industry has proposed using an off-peak charging scheme. This involves setting an idle power threshold, which is generally higher than the minimum power threshold. When the power of an idle shuttle is between the two thresholds and no other vehicle is using the charger, the idle shuttle with the lowest power is scheduled to charge, and the charging is disconnected once the shuttle is fully charged.
[0005] The current off-peak charging scheme simply prioritizes shuttles based on their battery level, without considering their workload. This results in shuttles with a high number of recent tasks being scheduled for charging, preventing them from completing tasks in a timely manner and impacting operational efficiency. Meanwhile, shuttles with fewer tasks and high battery levels that are in idle periods continue to consume power while in standby mode. Summary of the Invention
[0006] Embodiments of this disclosure present a method and apparatus for scheduling vehicle charging.
[0007] In a first aspect, embodiments of this disclosure provide a method for scheduling vehicle charging, comprising: in response to detecting that the number of idle vehicles is greater than a predetermined number, acquiring the current battery level and average task interval time of each idle vehicle; calculating the non-charging cost of each idle vehicle based on the current battery level of each idle vehicle; calculating the charging cost of each idle vehicle based on the current battery level and average task interval time of each idle vehicle; calculating the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle; and sending a charging instruction to a predetermined number of idle vehicles with the highest total cost.
[0008] In some embodiments, calculating the non-charging cost of each idle vehicle based on its current battery level includes: calculating a first operating cost for each idle vehicle based on the difference between the charging time from the lowest battery level to the highest battery level and the power-off time from the current battery level to the lowest battery level; calculating a second operating cost for each idle vehicle based on the difference between the charging time from the lowest battery level to the highest battery level and the power-off time from the degraded battery level to the lowest battery level, wherein the degraded battery level is the battery level after the current battery level is degraded; and multiplying the first operating cost and the second operating cost of each idle vehicle by the battery level retention probability and the battery level decay probability, respectively, and then summing them to obtain the non-charging cost of each idle vehicle.
[0009] In some embodiments, calculating the non-charging cost of each idle vehicle based on its current battery level includes: calculating a first operating cost of each idle vehicle based on the ratio of its maximum charging amount to its current charging amount, wherein the maximum charging amount is the difference between the highest and lowest battery level, and the current charging amount is the difference between the current and lowest battery level; calculating a second operating cost of each idle vehicle based on the ratio of its maximum charging amount to its current charging amount after a power outage; and multiplying the first and second operating costs of each idle vehicle by the probability of battery level retention and the probability of battery level decay, respectively, and then summing the results to obtain the non-charging cost of each idle vehicle.
[0010] In some embodiments, calculating the charging cost of each idle vehicle based on its current battery level and average task interval includes: calculating the probability of each idle vehicle being fully charged to its maximum battery level based on the average task interval of each idle vehicle; and calculating the charging cost of each idle vehicle based on the product of the charging time from its current battery level to its maximum battery level and the full charge probability.
[0011] In some embodiments, calculating the charging cost of each idle vehicle based on its current battery level and average task interval includes: calculating the probability of each idle vehicle being fully charged to its maximum battery level based on the average task interval of each idle vehicle; calculating the base charging cost of each idle vehicle based on the ratio of its pending charging amount to its maximum charging amount, wherein the pending charging amount is the difference between the maximum battery level and the current battery level, and the maximum charging amount is the difference between the maximum battery level and the minimum battery level; and calculating the charging cost of each idle vehicle based on the product of its base charging cost and the probability of full charge.
[0012] In some embodiments, calculating the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle includes: calculating the Whittle index of each idle vehicle as the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle.
[0013] In some embodiments, the charging cost is the sum of the charging costs for various amounts of power from the current power level to a safe charging range, wherein the safe charging range includes a safe power level threshold to a maximum power level.
[0014] In some embodiments, the method further includes: calculating the probability that each idle vehicle has no task before its battery level reaches a safe battery level threshold based on the average task interval time of each idle vehicle; and filtering out idle vehicles with a probability of having no task less than a predetermined threshold.
[0015] Secondly, embodiments of this disclosure provide an apparatus for scheduling vehicle charging, comprising: an acquisition unit configured to acquire the current battery level and average task interval time of each idle vehicle in response to detecting that the number of idle vehicles is greater than a predetermined number; a first calculation unit configured to calculate the non-charging cost of each idle vehicle based on the current battery level of each idle vehicle; a second calculation unit configured to calculate the charging cost of each idle vehicle based on the current battery level and average task interval time of each idle vehicle; a third calculation unit configured to calculate the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle; and a scheduling unit configured to send charging instructions to a predetermined number of idle vehicles with the highest total cost.
[0016] In some embodiments, the first calculation unit is further configured to: calculate a first operating cost for each idle vehicle based on the difference between the charging time from the lowest to the highest battery level and the power-down time from the current battery level to the lowest battery level; calculate a second operating cost for each idle vehicle based on the difference between the charging time from the lowest to the highest battery level and the power-down time from the decayed battery level to the lowest battery level, wherein the decayed battery level is the battery level after the current battery level is lost; and multiply the first operating cost and the second operating cost for each idle vehicle by the battery level retention probability and the battery level decay probability, respectively, and then sum them to obtain the non-charging cost for each idle vehicle.
[0017] In some embodiments, the first calculation unit is further configured to: calculate a first operating cost for each idle vehicle based on the ratio of the maximum charging amount to the charged amount of each idle vehicle, wherein the maximum charging amount is the difference between the highest and lowest charge levels, and the charged amount is the difference between the current charge level and the lowest charge level; calculate a second operating cost for each idle vehicle based on the ratio of the maximum charging amount to the charged amount after power loss; and multiply the first operating cost and the second operating cost of each idle vehicle by the probability of maintaining charge level and the probability of charge decay, respectively, and then sum them to obtain the non-charging cost of each idle vehicle.
[0018] In some embodiments, the second calculation unit is further configured to: calculate the probability of each idle vehicle being fully charged to its maximum capacity based on the average task interval time of each idle vehicle; and calculate the charging cost of each idle vehicle based on the product of the charging time from its current capacity to its maximum capacity and the full charge probability.
[0019] In some embodiments, the second calculation unit is further configured to: calculate the probability of each idle vehicle being fully charged to its maximum capacity based on the average task interval time of each idle vehicle; calculate the basic charging cost of each idle vehicle based on the ratio of the amount of energy to be charged to the maximum charging capacity of each idle vehicle, wherein the amount of energy to be charged is the difference between the maximum capacity and the current capacity, and the maximum charging capacity is the difference between the maximum capacity and the minimum capacity; and calculate the charging cost of each idle vehicle based on the product of the basic charging cost of each idle vehicle and the probability of full charge.
[0020] In some embodiments, the third calculation unit is further configured to calculate the Whittle index of each idle vehicle as the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle.
[0021] In some embodiments, the charging cost is the sum of the charging costs for various amounts of power from the current power level to a safe charging range, wherein the safe charging range includes a safe power level threshold to a maximum power level.
[0022] In some embodiments, the apparatus further includes a filtering unit configured to: calculate the probability that each idle vehicle has no task before its battery level reaches a safe battery level threshold based on the average task interval time of each idle vehicle; and filter out idle vehicles with a probability of having no task less than a predetermined threshold.
[0023] Thirdly, embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more computer programs stored thereon, wherein when the one or more computer programs are executed by the one or more processors, the one or more processors perform the method as described in any one of the first or second aspects.
[0024] Fourthly, embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method as described in any one of the first or second aspects.
[0025] Fifthly, embodiments of this disclosure provide a computer program product including a computer program that, when executed by a processor, implements the method as described in any one of the first or second aspects.
[0026] In a sixth aspect, embodiments of this disclosure provide a shuttle charging system, comprising: a server configured to perform the method described in any one of the first or second aspects; and a shuttle configured to receive a charging instruction sent by the server and charge it.
[0027] The methods and apparatus for scheduling vehicle charging provided in the embodiments of this disclosure determine the priority of vehicle charging by comprehensively considering the number of tasks and the amount of electricity, thereby reducing vehicle charging time and improving system efficiency without interfering with business operations.
[0028] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description
[0029] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:
[0030] Figure 1 This is an exemplary system architecture diagram to which one embodiment of this disclosure can be applied;
[0031] Figure 2 This is a flowchart of one embodiment of the method for scheduling vehicle charging according to the present disclosure;
[0032] Figure 3 This is a schematic diagram of an application scenario of the method for scheduling vehicle charging according to this disclosure;
[0033] Figure 4 This is a flowchart of yet another embodiment of the method for scheduling vehicle charging according to the present disclosure;
[0034] Figure 5 This is a schematic diagram of a device for scheduling vehicle charging according to an embodiment of the present disclosure;
[0035] Figure 6 This is a schematic diagram of the structure of a computer system suitable for implementing embodiments of the present disclosure. Detailed Implementation
[0036] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.
[0037] It should be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.
[0038] Figure 1 An exemplary system architecture is shown, illustrating an embodiment of the method or apparatus for scheduling vehicle charging that can be applied according to this disclosure.
[0039] like Figure 1 As shown, the system architecture may include a hoist, vehicles, charging stations, and a server. The hoist, vehicles, and charging stations interact with the server via wireless communication links. The vehicles are located on different levels of the shelving and are responsible for the inbound and outbound operations of goods on those levels.
[0040] The server can send a lifting task (indicating the shelf level) to the elevator, causing the elevator to lift the received goods to the corresponding shelf level, from where a vehicle responsible for that shelf level will transport them to the appropriate storage location. For example, Figure 1 The image shows a lifting task received by the elevator, which involves delivering goods to the second-level shelving. The elevator can adjust its height according to the number of shelves in the target shelving unit to accommodate different shelf levels. The elevator can also receive outbound tasks, transporting goods from the corresponding shelf level to the first level for transport by other vehicles.
[0041] The server also sends handling tasks to the vehicles, such as instructing them to retrieve goods from the elevator and transport them to a designated storage location on the same shelf. It can also instruct vehicles to retrieve goods from a designated storage location on the same shelf and transport them to the elevator. The server can calculate the average task interval time for each vehicle by tracking the intervals between different tasks.
[0042] The server can obtain the current battery level of vehicles. It can then notify vehicles with low battery levels to charge at charging stations. This minimizes the average charging time for vehicles without interfering with business operations, thereby improving system efficiency.
[0043] It's important to note that a server can be either hardware or software. When a server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When a server is software, it can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services), or as a single software program or software module. No specific limitations are made here. A server can also be a server for a distributed system, or a server integrated with blockchain technology. A server can also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology.
[0044] It should be noted that the method for scheduling vehicle charging provided in the embodiments of this disclosure is generally executed by a server, and correspondingly, the device for scheduling vehicle charging is generally located in the server.
[0045] It should be understood that Figure 1 The number of hoists, vehicles, charging stations, and servers shown is merely illustrative. Any number of hoists, vehicles, charging stations, and servers can be included depending on implementation needs.
[0046] Continue to refer to Figure 2 The diagram illustrates a flow 200 of an embodiment of a method for scheduling vehicle charging according to the present disclosure. The method for scheduling vehicle charging includes the following steps:
[0047] Step 201: In response to detecting that the number of idle vehicles is greater than a predetermined number, obtain the current battery level and average task interval of each idle vehicle.
[0048] In this embodiment, the execution entity of the method for scheduling vehicle charging (e.g.) Figure 1 The server shown can obtain the status of the charging piles via wired or wireless connections. To improve charging efficiency, the number of vehicles charging simultaneously can be limited, for example, only one vehicle can be charged at a time. If an idle charging pile is detected, a charging command can be sent to the idle vehicles (i.e., vehicles not performing transportation tasks). However, if there are too many idle vehicles, these idle vehicles need to be sorted and a predetermined number of vehicles notified to charge in descending order of priority.
[0049] To minimize the average charging time, this application needs to consider the current battery level of idle vehicles and the average task interval. Here, "task" refers to the task of transporting goods, including outbound and inbound tasks.
[0050] Vehicle battery level changes as follows Figure 3 As shown, each circle represents a battery status, and the numbers 100, y, x, etc. in the circles represent integer battery percentages. Figure 3 100 in the middle indicates that the battery level is 100%, x min This indicates the minimum battery level threshold; the vehicle must be charged when its battery level falls below this threshold. 0 (x, x-1) represents the probability that the charge will become x-1 in the next moment, p 1 (x, y) represents the probability that the vehicle will be charged to a level of y in a single charge. In this method, the vehicle does not need to be fully charged; charging can be stopped at any time when there is a task. Therefore, for any y > x, p 1 (x,y)>0.
[0051] The following describes how to calculate the probabilities of battery depletion and replenishment. If the vehicle is not charging, the probability that the battery level will decrease to x-1 at the next moment is as follows: The probability that the battery level remains at x. In other words, the higher the battery level, the lower the probability of battery degradation. The above probabilities are only used to estimate the rate of battery depletion; the higher the battery level, the slower the depletion, and they are unrelated to the actual physical laws governing battery drain. In reality, different battery models degrade at different rates. The precise probability of battery degradation and growth can be determined by statistically analyzing the degradation rates of different vehicles. For ease of calculation, a uniform value can also be used.
[0052] If the vehicle chooses to charge, let T(x,y) be the time required for the vehicle to charge from x to y, and let t be the idle time of the vehicle. Then, what is the probability p that the vehicle can charge to y? 1 (x,y)=P(T(x,y+1)≥t>T(x,y)). Based on the vehicle's historical mission data, we can calculate the average mission interval time as 1 / λ, then p 1 (x,y)=P(T(x,y+1)≥t>T(x,y))=exp(-λT(x,y))-exp(-λT(x,y+1)).
[0053] Assuming the vehicle's task flow follows a Poisson flow, and the average task interval time 1 / λ is calculated based on the vehicle's historical task data, then the probability of task interval time t ≤ T(x,y) is P(t≤T(x,y))=1-exp(-λT(x,y)). Next, the probability of the vehicle charging to a charge level y is calculated as p. 1 (x,y)=P(T(x,y+1)≥t>T(x,y))=P(t≤T(x,y+1))-P(t≤T(x,y))=exp(-λT(x,y))-exp(-λT(x,y+1)). According to the properties of Poisson flow, the remaining idle time of a vehicle is independent of the already idle time; therefore, the already idle time of the vehicle does not need to be considered when calculating the probability.
[0054] Step 202: Calculate the non-charging cost of each idle vehicle based on its current battery level.
[0055] In this embodiment, the higher the current battery level, the lower the cost of not charging; conversely, the lower the current battery level, the higher the cost of not charging. Some non-charging cost functions can be preset so that the cost of not charging is negatively correlated with the current battery level. For example, the non-charging cost function can be set to constant - equivalent battery level, or the non-charging cost function can be set to constant / equivalent battery level.
[0056] Optionally, the cost of not charging can be calculated by subtracting the standby time from the time it takes for the vehicle to fully charge from its minimum charge level, and the cost of charging can be calculated by using the time it takes to fully charge. The principle is that since our goal is to minimize the vehicle's average charging time, we directly use the vehicle's charging time as the cost. When the charge level is x, if the vehicle charges, the charging cost is equal to the time T(x, 100) it takes to charge from the current charge level to 100%; if the vehicle does not charge, it needs to wait for the charge level to decrease to the minimum charge level x. min Recharge, at this time the charging time is T(x) min The working time increases by the time T(x, x) from standby x to minimum battery level. min The cost of continuing to operate is the former minus the latter, because if the vehicle's battery level is high, the standby time will be longer than the charging time, and the cost of continuing to operate will be very low, so the vehicle should continue to operate instead of charging.
[0057] The above are just examples of non-charging cost functions. In practical applications, the above examples are not the only ones. Various types of functions can be designed so that the non-charging cost is negatively correlated with the current battery level.
[0058] Here, the fully charged capacity is not necessarily 100%, but can be any set maximum capacity, denoted as x. max This is due to the limitations of battery characteristics; capacitor batteries generally cannot be charged to 100%.
[0059] Step 203: Calculate the charging cost of each idle vehicle based on its current battery level and average task interval.
[0060] In this embodiment, the lower the current battery level, the higher the cost of not charging and the cost of charging.
[0061] Some charging cost functions can be preset so that the charging cost is negatively correlated with the current battery level. The following are some examples of charging cost functions, but not limited to them. Where x represents the current battery level, and C(x) represents the charging cost.
[0062] 1. When the average task interval is large enough, the average task interval can be ignored when calculating charging costs. Charging costs can be expressed as the time it takes to fully charge the battery from its current level.
[0063] 2. If the average task interval is short, charging may be interrupted by a transport task during the charging process, which can be divided into two situations:
[0064] 1) Calculate the probability of fully charging based on the average task interval time, and then calculate the charging cost based on the probability of fully charging and the duration of full charging.
[0065] 2) Calculate the cost of all possible scenarios, i.e., the vehicle's battery level can be charged from x+1 to x. max The cost of all charging scenarios is summed up.
[0066] The above are just examples of charging cost functions. In practical applications, the above examples are not the only ones. Various types of functions can be designed to make the charging cost negatively correlated with the current power level.
[0067] Step 204: Calculate the total cost of each idle vehicle based on the non-charging cost and charging cost of each idle vehicle.
[0068] In this embodiment, the total cost of each idle vehicle can be calculated by subtracting the product of the non-charging cost and the non-charging weight from the product of the charging cost and the charging weight.
[0069] Step 205: Send charging instructions to the predetermined number of idle vehicles with the highest total cost.
[0070] In this embodiment, the idle vehicle with the highest total cost is given priority for charging, thereby reducing the average charging time.
[0071] The method provided in the above embodiments of this disclosure schedules the highest priority idle shuttle to charge, thereby reducing the probability of multiple shuttles charging at the same time without interfering with business operations, thus shortening the long-term average charging time and improving system efficiency.
[0072] In some optional implementations of this embodiment, the step of calculating the non-charging cost of each idle vehicle based on its current battery level includes: calculating a first operating cost for each idle vehicle based on the difference between the charging time from the lowest battery level to the highest battery level and the power-off time from the current battery level to the lowest battery level; calculating a second operating cost for each idle vehicle based on the difference between the charging time from the lowest battery level to the highest battery level and the power-off time from the degraded battery level to the lowest battery level, wherein the degraded battery level is the battery level after the current battery level is degraded; and multiplying the first operating cost and the second operating cost of each idle vehicle by the battery level retention probability and the battery level decay probability, respectively, and then summing them to obtain the non-charging cost of each idle vehicle.
[0073] The available time of the vehicle can be used as a cost metric to calculate the first operating cost when the battery is maintained and the second operating cost when the battery is depleted. The total cost can then be calculated by combining the probability of maintaining the battery and the probability of depletion.
[0074] In some optional implementations of this embodiment, the step of calculating the non-charging cost of each idle vehicle based on its current battery level includes: calculating a first operating cost of each idle vehicle based on the ratio of its maximum charging amount to its already charged amount, wherein the maximum charging amount is the difference between the highest and lowest battery level, and the already charged amount is the difference between the current battery level and the lowest battery level; calculating a second operating cost of each idle vehicle based on the ratio of its maximum charging amount to its already charged amount after a power outage; and multiplying the first and second operating costs of each idle vehicle by the probability of battery level retention and the probability of battery level decay, respectively, and then summing the results to obtain the non-charging cost of each idle vehicle.
[0075] To simplify the calculation, the ratio of available power can be used instead of the charging time difference method mentioned earlier, which makes the calculation more convenient and faster.
[0076] In some optional implementations of this embodiment, the step of calculating the charging cost of each idle vehicle based on the current battery level and average task interval time of each idle vehicle includes: calculating the probability of each idle vehicle being fully charged to its maximum battery level based on the average task interval time of each idle vehicle; and calculating the charging cost of each idle vehicle based on the product of the charging time from the current battery level to the maximum battery level and the full charge probability.
[0077] The charging cost is the product of the probability of a full charge and the time required to fully charge, meaning the time from the current battery level to a full charge. The lower the battery level, the higher both the operating cost and the charging cost.
[0078] In some optional implementations of this embodiment, the step of calculating the charging cost of each idle vehicle based on its current battery level and average task interval includes: calculating the probability of each idle vehicle being fully charged to its maximum battery level based on the average task interval of each idle vehicle; calculating the basic charging cost of each idle vehicle based on the ratio of its pending charging amount to its maximum charging amount, wherein the pending charging amount is the difference between the highest battery level and the current battery level, and the maximum charging amount is the difference between the highest battery level and the lowest battery level; and calculating the charging cost of each idle vehicle based on the product of its basic charging cost and the probability of full charge.
[0079] Replacing the charging time difference method mentioned earlier with the ratio of electricity consumption allows for a more convenient and faster calculation of charging costs.
[0080] In some optional implementations of this embodiment, the step of calculating the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle includes: calculating the Whittle index of each idle vehicle as the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle.
[0081] Whittle Index: A method proposed by Whittle in 1988 for solving the multi-armed slot machine problem with state changes. It creates an index for each machine in the system, and the strategy of selecting machines based on this index has been proven to be approximately optimal.
[0082] Based on the above energy representation and probability calculation, the Whittle index is calculated with the goal of minimizing the average charging time of the shuttle.
[0083] Each vehicle is sorted from high to low according to the Whittle index. If no vehicle is currently charging, the idle vehicle with the highest priority is scheduled to charge.
[0084] The Whittle index calculates the cost of all possible scenarios, i.e., the vehicle's battery level could be charged to between x+1 and 100. The Whittle index sums up the costs of all charging scenarios.
[0085] If a vehicle is always fully charged and premature charging is not allowed, the Whittle index can be simplified to: the cost of not charging the vehicle when its charge level is x - the cost of charging the vehicle when its charge level is x.
[0086] The Whittle index is used to prioritize vehicles, selecting the highest-priority idle vehicle for charging. This is because the problem of charging multiple idle vehicles can be modeled as a state-changing multi-armed slot machine problem, and the Whittle index is an efficient method for solving this problem by dynamically calculating the priority of each vehicle based on its long-term expected payoff.
[0087] In some optional implementations of this embodiment, the charging cost is the sum of the charging costs of various quantities of electricity from the current quantity to the safe charging quantity range, wherein the safe charging quantity range includes the safe quantity threshold to the maximum quantity.
[0088] For charging safety reasons, if a vehicle stops charging when its battery level is low, electric arcing may occur. Therefore, a safe battery level threshold below the maximum battery level can be set, and charging can only be stopped once the vehicle reaches this threshold. This, combined with the maximum battery level threshold mentioned in the first point, improves the Whittle index. Setting a safe battery level threshold means that operating and charging costs are considered in relation to at least reaching this threshold, rather than arbitrarily exceeding the current battery level.
[0089] Further reference Figure 4 This illustrates a flow 400 of another embodiment of a method for scheduling vehicle charging. Flow 400 of this method for scheduling vehicle charging includes the following steps:
[0090] Step 401: In response to detecting that the number of idle vehicles is greater than a predetermined number, obtain the current battery level and average task interval of each idle vehicle.
[0091] Step 401 is basically the same as step 201, so it will not be described again.
[0092] Step 402: Calculate the probability that each idle vehicle will not have a task before its battery level reaches a safe battery level threshold based on the average task interval time of each idle vehicle, and filter out idle vehicles whose probability of not having a task is less than a predetermined threshold.
[0093] In this embodiment, if a safe charging threshold is set, to prevent busy vehicles from being assigned to charging stations, these vehicles can be filtered out first. Specifically, the probability that a vehicle has reached a safe charging level and has no assigned task is calculated as P(t>T(x,x)). safe ))=exp(-λT(x,x safe Set the probability threshold to Filter out The vehicle, so that it won't be adjusted.
[0094] Vehicles with relatively short task intervals.
[0095] Step 403: Calculate the non-charging cost of each idle vehicle based on its current battery level.
[0096] Step 404: Calculate the charging cost of each idle vehicle based on its current battery level and average task interval.
[0097] Step 405: Calculate the total cost of each idle vehicle based on the non-charging cost and charging cost of each idle vehicle.
[0098] Step 406: Send charging instructions to the predetermined number of idle vehicles with the highest total cost.
[0099] Steps 403-406 are basically the same as steps 202-205, so they will not be described again.
[0100] Further reference Figure 5 As an implementation of the methods shown in the above figures, this disclosure provides an embodiment of a device for scheduling vehicle charging, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.
[0101] like Figure 5As shown, the vehicle charging scheduling device 500 of this embodiment includes: an acquisition unit 501, a first calculation unit 502, a second calculation unit 503, a third calculation unit 504, and a scheduling unit 505. The acquisition unit 501 is configured to acquire the current battery level and average task interval time of each idle vehicle in response to detecting that the number of idle vehicles exceeds a predetermined number. The first calculation unit 502 is configured to calculate the non-charging cost of each idle vehicle based on its current battery level. The second calculation unit 503 is configured to calculate the charging cost of each idle vehicle based on its current battery level and average task interval time. The third calculation unit 504 is configured to calculate the total cost of each idle vehicle based on its non-charging cost and charging cost. The scheduling unit 505 is configured to send charging instructions to the predetermined number of idle vehicles with the highest total cost.
[0102] In this embodiment, the specific processing of the acquisition unit 501, the first calculation unit 502, the second calculation unit 503, the third calculation unit 504, and the scheduling unit 505 of the vehicle charging scheduling device 500 can be referred to Figure 2 The corresponding steps are 201, 202, 203, 204 and 205 in the embodiment.
[0103] In some optional implementations of this embodiment, the first calculation unit 502 is further configured to: calculate a first operating cost for each idle vehicle based on the difference between the charging time from the lowest to the highest battery level and the power-off time from the current battery level to the lowest battery level; calculate a second operating cost for each idle vehicle based on the difference between the charging time from the lowest to the highest battery level and the power-off time from the decayed battery level to the lowest battery level, wherein the decayed battery level is the battery level after the current battery level is lost; and multiply the first operating cost and the second operating cost of each idle vehicle by the battery level retention probability and the battery level decay probability, respectively, and then sum them to obtain the non-charging cost of each idle vehicle.
[0104] In some optional implementations of this embodiment, the first calculation unit 502 is further configured to: calculate a first operating cost for each idle vehicle based on the ratio of the maximum charging amount to the charged amount of each idle vehicle, wherein the maximum charging amount is the difference between the highest and lowest charge levels, and the charged amount is the difference between the current charge level and the lowest charge level; calculate a second operating cost for each idle vehicle based on the ratio of the maximum charging amount to the charged amount after power loss; and multiply the first operating cost and the second operating cost of each idle vehicle by the probability of maintaining charge level and the probability of charge decay, respectively, and then sum them to obtain the non-charging cost of each idle vehicle.
[0105] In some optional implementations of this embodiment, the second calculation unit 503 is further configured to: calculate the probability of each idle vehicle being fully charged to its maximum capacity based on the average task interval time of each idle vehicle; and calculate the charging cost of each idle vehicle based on the product of the charging time from its current capacity to its maximum capacity and the full charge probability.
[0106] In some optional implementations of this embodiment, the second calculation unit 503 is further configured to: calculate the probability of each idle vehicle being fully charged to its maximum capacity based on the average task interval time of each idle vehicle; calculate the basic charging cost of each idle vehicle based on the ratio of the amount of energy to be charged to the maximum charging capacity of each idle vehicle, wherein the amount of energy to be charged is the difference between the maximum capacity and the current capacity, and the maximum charging capacity is the difference between the maximum capacity and the minimum capacity; and calculate the charging cost of each idle vehicle based on the product of the basic charging cost of each idle vehicle and the probability of full charge.
[0107] In some optional implementations of this embodiment, the third calculation unit 503 is further configured to: calculate the Whittle index of each idle vehicle as the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle.
[0108] In some optional implementations of this embodiment, the charging cost is the sum of the charging costs of various quantities of electricity from the current quantity to the safe charging quantity range, wherein the safe charging quantity range includes the safe quantity threshold to the maximum quantity.
[0109] In some optional implementations of this embodiment, the device further includes a filtering unit (not shown in the figures), configured to: calculate the probability that each idle vehicle has no task before its battery level reaches a safe battery level threshold based on the average task interval time of each idle vehicle; and filter out idle vehicles with a probability of having no task less than a predetermined threshold.
[0110] It should be noted that the collection, gathering, updating, analysis, processing, use, transmission, and storage of user personal information involved in this disclosed technical solution all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.
[0111] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.
[0112] An electronic device includes: one or more processors; and a storage device having one or more computer programs stored thereon, which, when executed by the one or more processors, cause the one or more processors to implement the method described in process 200 or 400.
[0113] A computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in process 200 or 400.
[0114] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.
[0115] like Figure 6 As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded from storage unit 608 into random access memory (RAM) 603. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.
[0116] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0117] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as road planning methods. For example, in some embodiments, the road planning method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the road planning method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the road planning method by any other suitable means (e.g., by means of firmware).
[0118] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0119] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0120] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0121] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0122] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.
[0123] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be servers in distributed systems or servers incorporating blockchain technology. Servers can also be cloud servers, or intelligent cloud computing servers or intelligent cloud hosts with artificial intelligence technology.
[0124] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.
[0125] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.
Claims
1. A method for scheduling vehicle charging, comprising: In response to the detection that the number of idle vehicles is greater than a predetermined number, the current battery level and average task interval of each idle vehicle are obtained; Calculate the non-charging cost of each idle vehicle based on its current battery level. The charging cost of each idle vehicle is calculated based on its current battery level and average task interval. Calculate the total cost of each idle vehicle based on the non-charging cost and charging cost of each idle vehicle; Send charging instructions to the predetermined number of idle vehicles with the highest total cost.
2. The method according to claim 1, wherein, The calculation of the non-charging cost of each idle vehicle based on its current battery level includes: The first operating cost of each idle vehicle is calculated based on the difference between the charging time from the lowest battery level to the highest battery level and the power loss time from the current battery level to the lowest battery level. The second operating cost of each idle vehicle is calculated based on the difference between the charging time from the lowest to the highest battery level and the power-off time from the depleted battery level to the lowest battery level for each idle vehicle, wherein the depleted battery level is the battery level after the current battery level is depleted. The first and second operating costs of each idle vehicle are multiplied by the probability of maintaining battery power and the probability of battery power decay, respectively, and then summed to obtain the non-charging cost of each idle vehicle.
3. The method according to claim 1, wherein, The calculation of the non-charging cost of each idle vehicle based on its current battery level includes: The first operating cost of each idle vehicle is calculated based on the ratio of its maximum charging capacity to its current charging capacity, wherein the maximum charging capacity is the difference between the highest and lowest charging capacity, and the current charging capacity is the difference between the current charging capacity and the lowest charging capacity. The second operating cost of each idle vehicle is calculated based on the ratio of the maximum charging capacity of each idle vehicle to the charging capacity after a power outage. The first and second operating costs of each idle vehicle are multiplied by the probability of maintaining battery power and the probability of battery power decay, respectively, and then summed to obtain the non-charging cost of each idle vehicle.
4. The method according to claim 1 or 2, wherein, The calculation of the charging cost for each idle vehicle based on its current battery level and average task interval includes: The probability of each idle vehicle being fully charged to its maximum capacity is calculated based on the average task interval time of each idle vehicle. The charging cost of each idle vehicle is calculated based on the product of the charging time from its current charge level to its maximum charge level and the probability of it being fully charged.
5. The method according to claim 1 or 3, wherein, The calculation of the charging cost for each idle vehicle based on its current battery level and average task interval includes: The probability of each idle vehicle being fully charged to its maximum capacity is calculated based on the average task interval time of each idle vehicle. The basic charging cost of each idle vehicle is calculated based on the ratio of the amount of electricity waiting to be charged to the maximum charging capacity of each idle vehicle. The amount of electricity waiting to be charged is the difference between the maximum charging capacity and the current charging capacity, and the maximum charging capacity is the difference between the maximum charging capacity and the minimum charging capacity. The charging cost of each idle vehicle is calculated based on the product of the base charging cost of each idle vehicle and the full charge probability.
6. The method according to claim 1, wherein, The calculation of the total cost of each idle vehicle based on the non-charging cost and charging cost of each idle vehicle includes: The Whittle index of each idle vehicle is calculated based on the non-charging cost and charging cost of each idle vehicle, and is used as the total cost of each idle vehicle.
7. The method according to claim 1 or 6, wherein, The charging cost is the sum of the charging costs for various amounts of electricity from the current amount of electricity to the safe charging range, wherein the safe charging range includes the safe charging threshold to the maximum amount of electricity.
8. The method according to claim 1, wherein, The method further includes: The probability that each idle vehicle will not have a task before its battery level reaches the safe battery threshold is calculated based on the average task interval time of each idle vehicle. Idle vehicles with a probability of having no task less than a predetermined threshold are filtered out.
9. A device for scheduling vehicle charging, comprising: The acquisition unit is configured to acquire the current battery level and average task interval of each idle vehicle in response to detecting that the number of idle vehicles is greater than a predetermined number. The first calculation unit is configured to calculate the non-charging cost of each idle vehicle based on the current battery level of each idle vehicle. The second calculation unit is configured to calculate the charging cost of each idle vehicle based on the current battery level and average task interval of each idle vehicle. The third calculation unit is configured to calculate the total cost of each idle vehicle based on the non-charging cost and the charging cost of each idle vehicle. The scheduling unit is configured to send charging instructions to a predetermined number of idle vehicles that have the highest total cost.
10. An electronic device, comprising: One or more processors; Storage device, on which one or more computer programs are stored, When the one or more computer programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-8.
11. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-8.
12. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-8.
13. A shuttle charging system, comprising: The server is configured to perform the method according to any one of claims 1-8; The shuttle is configured to receive charging instructions sent by the server and charge accordingly.