An offline-online combined mobile charging vehicle scheduling method

Abstract

The application discloses a kind of off-line online combination mobile charging car scheduling method, comprising: according to the attribute of wireless chargeable sensor network, energy consumption rate and normalized charging cost of chargeable node, under the constraints of charging cost and distance, chargeable node is divided into multiple node groups, and node information table is generated;According to node information table, the TSP path of connecting all chargeable nodes in each node group is planned;Based on offline scheduling algorithm, according to the TSP path of each node group, the first mobile charging car corresponding to the node group is controlled to charge the chargeable nodes in the node group;Based on online scheduling algorithm, according to the charging request issued by the chargeable nodes in each node group, the second mobile charging car corresponding to the node group is controlled to charge the chargeable nodes issuing charging request.The application meets the needs of nodes in urgent need of charging through the scheduling operation of off-line and online, and also takes into account the energy of other nodes in the network.

Description

TECHNICAL FIELD

[0001] The present application relates to a kind of off-line online combination mobile charging car scheduling method, belong to mobile charging car scheduling technical field. BACKGROUND

[0002] Wireless rechargeable sensor networks (WRSNs) are composed of a large number of micro-sensor nodes, which can be deployed in a specific area to form a multi-hop self-organizing network to monitor the target. In wireless rechargeable sensor networks, one or more mobile charging vehicles are used to supplement the energy of all rechargeable nodes to avoid premature death of rechargeable nodes and affect network operation. In order to achieve better charging effect, the mobile charging vehicles in the wireless rechargeable sensor network need to be scheduled.

[0003] Current mobile charging vehicle scheduling algorithms in the field of wireless rechargeable sensor networks mainly include offline scheduling algorithms and online scheduling algorithms. In offline scheduling algorithms, mobile charging vehicles often traverse all nodes in the network periodically along predetermined paths and charge them. However, wireless rechargeable sensor networks are dynamically operated, and the energy consumption of each node will change according to different actual situations, which will cause the predetermined path and scheduling in offline scheduling algorithms to be no longer optimal, thereby reducing energy supply efficiency and node survival rate. In online scheduling algorithms, when the remaining power of a node is lower than its set threshold, it will send a charging request, and the mobile charging vehicle will be triggered to supplement the energy of the corresponding node when it meets certain conditions. Although online scheduling algorithms can adapt to changes in node energy consumption rate to some extent, their application scale is limited, and in the case of a single mobile charging vehicle in the network, it is often impossible to ensure that all requesting nodes can be served. SUMMARY

[0004] To solve the problems in the prior art, the present application proposes a mobile charging vehicle scheduling method combining offline and online scheduling, which groups rechargeable nodes in the wireless rechargeable sensor network, optimizes the movement path of the mobile charging vehicle, and through the combination of offline and online scheduling, meets the needs of nodes in urgent need of charging, and also takes into account the energy of other nodes in the network, reduces charging cost, improves charging effect, and improves the reliability and stability of the wireless rechargeable sensor network.

[0005] To solve the above technical problems, the present application adopts the following technical means:

[0006] The present application provides a mobile charging vehicle scheduling method combining offline and online scheduling, comprising the following steps:

[0007] According to attribute information of each chargeable node in the wireless chargeable sensor network, energy consumption rate and normalized charging cost of each chargeable node are calculated;

[0008] According to the attribute, energy consumption rate and normalized charging cost of the chargeable node, the chargeable nodes in the wireless chargeable sensor network are divided into a plurality of node groups under the charging cost constraint and distance constraint, and a node information table is generated;

[0009] According to the node information table, a TSP path of all chargeable nodes in each node group is planned;

[0010] Based on an offline scheduling algorithm, a first mobile charging vehicle corresponding to each node group is controlled according to the TSP path of the node group, and the chargeable nodes in the node group are charged;

[0011] Based on an online scheduling algorithm, a second mobile charging vehicle corresponding to each node group is controlled according to a charging request sent by a chargeable node in the node group, and the chargeable node sending the charging request is charged.

[0012] Further, the attribute information of each chargeable node in the wireless chargeable sensor network includes node ID, node coordinates and node residual power.

[0013] Further, the calculation of the energy consumption rate and the normalized charging cost of each node according to the attribute information of each chargeable node in the wireless chargeable sensor network comprises:

[0014] The energy consumption rate of each chargeable node is calculated according to the node residual power of each chargeable node, and the calculation formula is as follows:

[0015] p i i i ’ / t

[0016] P i ’=E s -E i,t

[0017] Wherein, p i is the energy consumption rate of the i th chargeable node, P i ' is the power consumed by the i th chargeable node from 0 to t, i ∈ [1, N], N is the total number of chargeable nodes in the wireless chargeable sensor network, E s is the initial power of the chargeable node, E i,t is the node residual power of the i th chargeable node at t;

[0018] The distance of each chargeable node to the base station is calculated according to the node coordinates of each chargeable node;

[0019] The normalized charging cost of each chargeable node is calculated according to the distance of each chargeable node to the base station and the energy consumption rate of the chargeable node, and the calculation formula is as follows:

[0020] c i = α × p i + β × d(s i , BS)

[0021] Wherein, c i is the normalized charging cost of the i th chargeable node, α and β are normalized charging coefficients, α, β ∈ [0, 1], and α + β = 1, d(s i , BS) is the Euclidean distance of the i th chargeable node s i to the base station BS.

[0022] Further, the chargeable nodes are grouped, comprising:

[0023] (1) all chargeable nodes in the wireless chargeable sensor network are sorted according to the value of the normalized charging cost from large to small, and a first queue Q is obtained;

[0024] (2) the first chargeable node in the first queue Q is taken as a member of the first node group Cluster1, and is added to the first node group Cluster1, and K = 1 is recorded, and the first chargeable node is deleted from the first queue Q;

[0025] (3) starting from k = 1 until k = K, the first chargeable node s j in the current first queue Q is sequentially judged whether the k th node group Cluster k satisfies the charging cost constraint and the distance constraint after s k is added to the k th node group Cluster k ; if the k th node group Cluster j satisfies the charging cost constraint and the distance constraint, the chargeable node s k is added to the k th node group Cluster k , the charging cost C k and the center Center k of the k th node group Cluster j are updated, and the chargeable node s j is deleted from the current first queue Q; if all node groups do not satisfy the charging cost constraint and the distance constraint, the current chargeable node s k+1 is taken as a member of the K+1 th node group Cluster k+1 , and is added to the K+1 th node group Cluster j , and K = K+1 is recorded, and the chargeable node s is deleted from the current first queue Q;; wherein, j∈[1, N], N is the total number of chargeable nodes in the wireless chargeable sensor network;

[0026] (4) repeating step (3) until the first queue Q is empty, obtaining K node groups.

[0027] Further, the charging cost constraint is:

[0028] C k <C’

[0029] wherein, C k is the charging cost of the node s j after joining the node group Cluster k , C k is the sum of the normalized charging costs of all chargeable nodes in the node group Cluster k , and C’ is a preset cost threshold. k

[0030] The distance constraint is:

[0031] d(s j , Center k )≤d(s j , BS)

[0032] wherein, d(s j , Center k ) is the distance from any chargeable node in the node group Cluster j to the center Center k after the node s k joins the node group Cluster k , and d(s j , BS) is the distance from the node s j to the base station.

[0033] Further, the node information table includes N row vectors, each row vector corresponding to a chargeable node, and each row vector including: node ID, node coordinates, node energy consumption rate, node remaining power, normalized charging cost, and node group number.

[0034] Further, based on the online scheduling algorithm, the charging request of each chargeable node is controlled to control the second mobile charging vehicle corresponding to the node group to charge the chargeable node that sends the charging request, including:

[0035] The obtained charging request of the chargeable node is sequentially added to the charging request queue Q’ of the node group;

[0036] ​According to the order of the charging requests in the charging request queue Q', the second mobile charging vehicle corresponding to the node group is controlled to go to each charging request corresponding chargeable node in turn, and the chargeable node is charged to E', E' being a preset charging value;

[0037] Whenever the second mobile charging vehicle finishes charging a chargeable node, the charging request of the chargeable node is deleted from the charging request queue Q' according to the node ID of the chargeable node.

[0038] Further, before the first mobile charging vehicle or the second mobile charging vehicle charges any chargeable node, it is checked through information interaction whether the chargeable node is being charged; if the chargeable node is being charged, the first mobile charging vehicle or the second mobile charging vehicle is controlled to move to the next chargeable node; if the chargeable node is not being charged, it is judged whether the remaining power of the chargeable node is greater than a preset safety threshold; if greater than the preset safety threshold, the first mobile charging vehicle or the second mobile charging vehicle is controlled to move to the next chargeable node; if not greater than the preset safety threshold, the first mobile charging vehicle or the second mobile charging vehicle is controlled to charge the chargeable node.

[0039] Further, before the first mobile charging vehicle or the second mobile charging vehicle charges any chargeable node, the remaining power of the chargeable node and the remaining power of the mobile charging vehicle are combined to judge whether the first mobile charging vehicle or the second mobile charging vehicle has enough power to return to the base station after completing the charging task, and the judgment formula three is as follows:

[0040] E current ≥p m ×(d(s i )+d(s i ,BS))+(E’–e i r )

[0041] Wherein, E current represents the current remaining power of the mobile charging vehicle, p m represents the energy consumption of the mobile charging vehicle per unit distance, and d(s i ) represents the Euclidean distance of the mobile charging vehicle from the current position to the chargeable node s i .

[0042] If the judgment formula three is established, the first mobile charging vehicle or the second mobile charging vehicle is controlled to charge the chargeable node, otherwise, the current charging task is abandoned, and the first mobile charging vehicle or the second mobile charging vehicle is controlled to return to the base station to replace the battery.

[0043] Further, when the first mobile charging vehicle completes the charging task of the last chargeable node in the node group along the TSP path, if the remaining power of the first mobile charging vehicle is greater than ηEM If the first mobile charging vehicle does not return to the base station, it continues to charge the rechargeable nodes in its node group with remaining power below E0 to E' along the TSP path, until Formula 3 is not true or there are no rechargeable nodes with remaining power below E0 in the node group where the first mobile charging vehicle is located, where E... M The mobile charging vehicle is at full charge, η is a preset percentage value, E' is a preset charging value, and E0 is a preset safety threshold.

[0044] When the second mobile charging vehicle has completed all charging requests from the rechargeable nodes within its node group, if the remaining power of the second mobile charging vehicle is greater than ηE... M If the second mobile charging vehicle does not return to the base station, it will traverse all rechargeable nodes in its node group in descending order of normalized charging cost, charging nodes that have not been charged in this round and whose remaining power is below E0 to E', until the third judgment is not true or there are no rechargeable nodes in the node group where the second mobile charging vehicle is located that have not been charged in this round and whose remaining power is below E0; where "this round" refers to the time period from the last time the first and second mobile charging vehicles left the base station to the current time.

[0045] The following advantages can be obtained by adopting the above technical means:

[0046] This invention proposes a mobile charging vehicle scheduling method that combines offline and online methods. It groups rechargeable nodes in a wireless rechargeable sensor network and then schedules mobile charging vehicles for each node group to charge the rechargeable nodes within that group. Specifically, the invention uses a combined offline and online scheduling method to control the mobile charging vehicles. A first mobile charging vehicle performs standardized charging operations along the TSP path, while a second mobile charging vehicle provides real-time charging to rechargeable nodes that have issued charging requests. This method satisfies the needs of nodes in urgent need of charging while also considering the energy needs of other nodes, improving charging efficiency, ensuring sufficient power for rechargeable nodes, and preventing nodes from failing due to insufficient power.

[0047] When grouping, this invention fully considers the shortcomings of mobile charging vehicles, such as limited energy storage, slow charging speed, and low charging efficiency. It imposes dual constraints on the grouping process, ensuring that the size of each node group is adapted to the capacity of the mobile charging vehicle through charging cost constraints and distance constraints, thus achieving a reasonable node group division.

[0048] The method of this invention can fully meet the needs of all rechargeable nodes, and the charging scheduling is more flexible and reliable. Compared with the prior art, this invention can reduce charging costs, improve charging efficiency, and reduce the number of dead nodes. Attached Figure Description

[0049] Figure 1 This is a schematic diagram illustrating the steps of a mobile charging vehicle scheduling method combining offline and online operation according to the present invention.

[0050] Figure 2 This is a schematic diagram showing the locations of the rechargeable node, node group, and base station in an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of the charging paths for the first and second mobile charging vehicles in an embodiment of the present invention;

[0052] Figure 4 For the first mobile charging vehicle x k Preparing to charge the next rechargeable node while the node is being charged by a second mobile charging vehicle. k First mobile charging vehicle x k Path adjustment diagram;

[0053] Figure 5 For the second mobile charging vehicle z k When preparing to charge the next rechargeable node, it was discovered that the node was being used by the first mobile charging vehicle. k Second mobile charging vehicle z k The path adjustment diagram is shown below. Detailed Implementation

[0054] The technical solution of the present invention will be further described below with reference to the accompanying drawings:

[0055] This embodiment introduces a mobile charging vehicle scheduling method that combines offline and online methods, such as... Figure 1 As shown, the specific steps include the following:

[0056] Step A: Initialize the wireless rechargeable sensor network.

[0057] Suppose that N isomorphic rechargeable nodes s are randomly distributed in a wireless rechargeable sensor network. i For each node i∈[1,N], the node knows its own location information; all rechargeable nodes start with a full charge E. s When the remaining power of any rechargeable node is lower than the preset threshold E th At that time, the rechargeable node will send a charging request to the base station; the base station is located at the center of the wireless rechargeable sensor network, and the base station can control the mobile charging vehicle to charge the rechargeable node. In this embodiment of the invention, let E... th =30%E s .

[0058] Step B, obtaining attribute information of each chargeable node in the wireless chargeable sensor network through information interaction between the chargeable node and the base station, and calculating energy consumption rate and normalized charging cost of each chargeable node according to the attribute information of each chargeable node.

[0059] In the embodiment of the application, the base station in the wireless chargeable sensor network can actively obtain attribute information of all chargeable nodes. The wireless chargeable sensor network starts running from time 0, and after the network runs to a preset time t0, the base station broadcasts an "attribute request packet" to the whole network. After the chargeable nodes in the wireless chargeable sensor network receive the "attribute request packet", the chargeable nodes send an "attribute return packet" to the base station, and send their own attribute information to the base station. The preset time t0 is a value set by a person, and the specific value can be selected according to the power consumption performance of the chargeable node itself, for example, t0 = 10 min.

[0060] In addition, considering that the actual power consumption of each chargeable node is different in actual use, in order to further improve the scheduling performance of the mobile charging vehicle, the base station in the wireless chargeable sensor network can also passively obtain attribute information of all chargeable nodes at the request of the chargeable nodes. Specifically, any chargeable node in the wireless chargeable sensor network can actively send a "request charging packet" containing its own attribute information to the base station when the remaining power is less than E th , and record the current time t. After the base station receives the "request charging packet", it immediately broadcasts an "attribute request packet" to the whole network. All chargeable nodes that have not sent the "request charging packet" receive the "attribute request packet" and send an "attribute return packet" to the base station, and send their own attribute information to the base station.

[0061] The attributes of the chargeable node mainly include node ID, node coordinates and node remaining power, wherein the node ID has uniqueness. In the embodiment of the application, the content of the "request charging packet" includes a "packet type" field of 3 bytes, a "packet node ID" field of 2 bytes, a "packet node coordinates" field of 2 bytes, a "packet node energy consumption rate" field of 1 byte (initially empty) and a "packet node remaining power" field of 1 byte; the content of the "attribute request packet" includes a "packet type" field of 3 bytes, a "packet node ID" field of 2 bytes; the content of the "attribute return packet" includes a "packet type" field of 3 bytes, a "packet node ID" field of 2 bytes, a "packet node coordinates" field of 2 bytes, a "packet node energy consumption rate" field of 1 byte (initially empty) and a "packet node remaining power" field of 1 byte.

[0062] In this embodiment of the invention, the "Package Type" field in the "Request Charging Pack" is specifically the string "REQ"; the "Package Type" field in the "Attribute Request Pack" is specifically the string "PRE"; and the "Package Type" field in the "Attribute Return Pack" is specifically the string "PAC".

[0063] After receiving the "request charging packet" and / or "attribute return packet", the base station can extract the attribute information of each rechargeable node at the current time based on the packet content, and then calculate the energy consumption rate and normalized charging cost of each rechargeable node based on the attributes of each rechargeable node. The specific calculation steps are as follows:

[0064] Step B01: Calculate the energy consumption rate of each rechargeable node based on its remaining power. The calculation formula is as follows:

[0065] p i =P i ' / t(1)

[0066] P i '=E s -E i,t (2)

[0067] Where, p i Let P be the energy consumption rate of the i-th rechargeable node. i ' represents the amount of electricity consumed by the i-th rechargeable node from time 0 to time t, N is the total number of rechargeable nodes in the wireless rechargeable sensor network, and E i,t Let t be the remaining power of the i-th rechargeable node at time t.

[0068] Step B02: Calculate the Euclidean distance from each rechargeable node to the base station based on the node coordinates of each rechargeable node.

[0069] Step B03: Calculate the normalized charging cost for each rechargeable node based on the Euclidean distance from the base station and the energy consumption rate of that rechargeable node. The calculation formula is as follows:

[0070] c i ﹦α×p i +β×d(s i ,BS)(3)

[0071] Among them, c i Let d(s) be the normalized charging cost of the i-th rechargeable node, where α and β are normalized charging coefficients, α and β ∈ [0,1], and α + β = 1. i ,BS) represents the i-th rechargeable node s i Euclidean distance to base station (BS).

[0072] Step C, according to the attribute, energy consumption rate and normalized charging cost of the chargeable node, divide the chargeable nodes in the wireless chargeable sensor network into multiple node groups under the charging cost constraint and distance constraint, and generate a node information table.

[0073] Step C01, sort all the chargeable nodes in the wireless chargeable sensor network according to the value of the normalized charging cost c i from large to small, to obtain a first queue Q. Take the first chargeable node in the first queue Q as a member of a first node group Cluster1, and add the first chargeable node to the first node group Cluster1. At this time, K = 1.

[0074] Step C02, take out the first chargeable node s j in the current first queue Q, and perform the following operations: from k = 1 to k = K, try to add the first chargeable node s j in the current first queue Q to each node group in turn, and judge whether the node group satisfies the charging cost constraint and distance constraint after the chargeable node s j is added to the node group; if the first node group Cluster k that satisfies the constraint appears, add the chargeable node s j to the node group Cluster k , and update the charging cost C k value and the center Center k value of the node group Cluster k , and delete the chargeable node s j from the first queue Q; if none of the K node groups satisfies the constraint, and there is no node group that the chargeable node s j can join, take the chargeable node s j as a member of a K+1 node group Cluster k+1 , delete the chargeable node s j from the first queue Q, and update the value of K to K+1.

[0075] Step C03, repeat step C02, and store the chargeable nodes in the first queue Q into each node group in turn through a loop operation, and update the node groups and the first queue Q in the loop process until the first queue Q is empty, to obtain the final K node groups, each of which contains one or more chargeable nodes.

[0076] Step C04, a "node information table" is established, as shown in Table 1, which is composed of N row vectors, each of which corresponds to a chargeable node in the wireless chargeable sensor network, and the specific content of the vector includes: a "node ID" field of 2 bytes, a "node coordinate" field of 2 bytes, a "node energy consumption rate" field of 1 byte, a "node residual capacity" field of 1 byte, a "normalized charging cost" field of 1 byte, and a "node group group number" field of 1 byte. The content in the "node energy consumption rate" field is calculated by formula (1) and (2) and filled in, the content in the "node residual capacity" field is updated in real time, the content in the "normalized charging cost" field is calculated by formula (3) and filled in, the content in the "group number" field is determined by steps C01-C03, and the content in the remaining fields is written by the base station after extracting the corresponding field values from the "request charging packet" and "attribute return packet" received by it.

[0077] Table 1

[0078]

[0079]

[0080] In step C02, the charging cost constraint is that the chargeable node s j joins the node group Cluster k , the sum of the normalized charging costs of all chargeable nodes in the node group Cluster k is the charging cost C k of the node group, and the charging cost C k is not greater than the preset cost threshold C', that is, C k <C'; wherein the cost threshold C' is used to limit the number of chargeable nodes in a node group, so as to avoid that the number of chargeable nodes in a node group is too large and the mobile charging vehicle cannot fully serve the chargeable nodes, the value of the cost threshold C' is related to the number and capacity of the mobile charging vehicle, and can be selected by experiment or experience, and in the embodiment of the present application, C'=165.

[0081] In step C02, the distance constraint is that the chargeable node s j joins the node group Cluster k , the adjacent chargeable nodes are connected in a straight line, all the chargeable nodes in the node group Cluster k can form a polygon, and the centroid of the polygon can be calculated according to the node coordinates of all the chargeable nodes in the node group Cluster k , which is recorded as the centroid Center k of the node group Cluster k , the distance between the chargeable node s kFrom any rechargeable node to the centroid Center k Distance d(s) j Center k The distance d(s) from the rechargeable node to the base station is not greater than the distance d(s) j ,BS), that is, d(s j Center k )≤d(s j Distance constraints are used to limit the distance between rechargeable nodes in a node group. Under distance constraints, the rechargeable nodes in each node group are closer together. The mobile charging vehicle needs to travel a shorter distance to charge these rechargeable nodes, which can reduce the power consumed during travel, avoid resource waste, and improve charging efficiency. Figure 2 It shows d(s) j Center k )>d(s j In the case of BS), from Figure 2 It can be seen that the rechargeable node s j It is too far away from other rechargeable nodes in the node group to be placed in the same group.

[0082] After grouping, a corresponding mobile charging vehicle is configured for each node group. Theoretically, each mobile charging vehicle will only serve the rechargeable nodes within its node group. In this embodiment of the invention, each node group is configured with at least two mobile charging vehicles, referred to as the first mobile charging vehicle and the second mobile charging vehicle. The first mobile charging vehicle is responsible for charging the rechargeable nodes within its node group according to an offline scheduling algorithm, and the second mobile charging vehicle is responsible for charging the rechargeable nodes within its node group according to an online scheduling algorithm.

[0083] Step D: Based on the node information table, plan a TSP path connecting all rechargeable nodes within each node group. Select the rechargeable node in the current node group that is closest to the base station as the starting point of the TSP path for that node group, and establish a TSP path connecting the nodes within the group using existing path planning algorithms. This invention can employ any existing path planning algorithm, such as the nearest neighbor algorithm, to directly connect adjacent nodes after determining the starting point, forming a complete path connecting all rechargeable nodes.

[0084] Step E: Based on the TSP path of each node group, the first mobile charging vehicle corresponding to that node group is offline scheduled to charge the rechargeable nodes within that node group. In this invention, there are two conditions for initiating offline scheduling: one is to start the first mobile charging vehicle for offline charging according to a preset offline charging cycle (e.g., performing an offline charging task once per hour); the other is to start the first mobile charging vehicle for offline charging based on a charging request issued by any rechargeable node within the node group to which the first mobile charging vehicle is located. After the first mobile charging vehicle is started, it departs from the base station and, according to the offline scheduling algorithm, performs partial charging of the rechargeable nodes within the node group it is responsible for according to the TSP path.

[0085] After the first mobile charging vehicle arrives at a rechargeable node, it first checks the remaining power of that node. If the remaining power is not lower than a preset charging value E', it does not charge that node. If the remaining power is lower than E', it controls the first mobile charging vehicle to charge the node to E', and then controls the first mobile charging vehicle to move along the TSP path to the next rechargeable node. In this embodiment of the invention, E' can be set to 90% of E'. s The reason for not directly charging the rechargeable node to full capacity is... s This is to enable a mobile charging vehicle to charge more charging nodes.

[0086] To improve charging efficiency, this embodiment of the invention configures two first mobile charging vehicles x for each node group. k y k When an offline charging task needs to be performed, the first mobile charging vehicle x k y k Simultaneously, starting from the base station, it proceeds to the starting point of the TSP path within its node group, and from that starting point, traverses all rechargeable nodes within the node group in both clockwise and counterclockwise directions along the TSP path, such as... Figure 3 As shown.

[0087] Step F: Based on the charging requests of the rechargeable nodes in each node group, schedule the second mobile charging vehicle corresponding to each node group online to charge the rechargeable nodes in each node group.

[0088] When the remaining power of the rechargeable node is lower than E th At that time, the rechargeable node sends a "request for charging" to the base station. The base station can determine which node group the requesting node belongs to based on the node information table, and send the charging request of the rechargeable node to the charging request queue Q' of that node group. After the first charging request appears in the charging request queue Q' of the node group, the second mobile charging vehicle starts, and the second mobile charging vehicle z kFrom the base station, according to the principle of "first come first served" in the online scheduling algorithm, according to the order of the charging requests in the charging request queue Q', the first mobile charging vehicle goes to different chargeable nodes for partial charging in turn, as shown in FIG. 2. Figure 3

[0089] Whenever the second mobile charging vehicle finishes serving a chargeable node, it removes the charging request of the node from the charging request queue Q' according to the node ID. After the second mobile charging vehicle departs from the base station, the base station can continue to receive charging requests of chargeable nodes in the node group and send new charging requests to the charging request queue Q'.

[0090] In steps E and F, in order to avoid wireless charging conflicts, each mobile charging vehicle checks whether each chargeable node is being charged before charging the node, and performs different operations according to the checking results, as follows:

[0091] (1) Each chargeable node in the node group Cluster k sends a "to-be-charged" message packet to the remaining mobile charging vehicles in the group at the moment before being charged by a mobile charging vehicle. The packet contains a 3-byte "packet type" field, a 2-byte "node ID" field, a 1-byte "node remaining power e i r " field, and a 1-byte "charging start time t i begin " field. The specific string in the "packet type" field is "CHA".

[0092] (2) Before charging any chargeable node in the node group Cluster k , any mobile charging vehicle in the group first checks whether it has received the "to-be-charged" message packet from the chargeable node in the current round. If it has received the packet, it performs step (3); otherwise, it controls the mobile charging vehicle to charge the power of the chargeable node to E'. In the embodiment of the application, one round of charging refers to the time period from the time when the first mobile charging vehicle and the second mobile charging vehicle last left the base station to the time when they return to the base station.

[0093] (3) The mobile charging vehicle determines whether the chargeable node is being charged according to the "to-be-charged" message packet, and the determination formula one is as follows:

[0094] t i current > t i begin + (E'- e i r / P​c (4)

[0095] where t i current represents the current time, P c represents the charging power of the mobile charging vehicle, (E'-e i r ) / P c represents the time required to charge the ith chargeable node s i to E'.

[0096] If formula (4) is not established, it indicates that the chargeable node s i is being charged by other mobile charging vehicles, and the current mobile charging vehicle no longer serves the chargeable node, and the current mobile charging vehicle is controlled to go to the next chargeable node.

[0097] If formula (4) is established, it indicates that the chargeable node s i is not being charged at present, and in order to avoid reducing the energy utilization rate of the mobile charging vehicle, the residual capacity of the chargeable node s i needs to be judged, and the second judgment formula is as follows:

[0098] E'-p i ×(t i current -(t i begin +(E'-e i r ) / (P c ))>E0 (5)

[0099] where p i represents the energy consumption rate of the node s i , and E0 is a fixed value and is a safety threshold of the residual capacity of the chargeable node.

[0100] If formula (5) is established, it indicates that the residual capacity of the chargeable node s i is sufficient and does not need to be charged again, and the mobile charging vehicle no longer serves the chargeable node, and the mobile charging vehicle is controlled to go to the next chargeable node; if formula (5) is not established, it indicates that the residual capacity of the chargeable node s i is not sufficient, and the mobile charging vehicle is controlled to charge the chargeable node s i to E'.

[0101] In the embodiment of the application, E0 can be set to 70% E s. Through formula (5), the chargeable node which has been charged and whose residual energy is between (E0, E') will not be charged again, so as to leave the energy of the mobile charging vehicle for the chargeable node which needs charging more, and improve the energy utilization rate of the mobile charging vehicle.

[0102] Figure 4 and Figure 5 Two possible wireless charging conflicts and the charging path of the adjusted mobile charging vehicle are given. In Figure 4 , the second mobile charging vehicle z k is charging the chargeable node s4, while the first mobile charging vehicle x k is also ready to go to the chargeable node s4 for charging (see the original charging path of x k ). At this time, the first mobile charging vehicle x k judges that the chargeable node s4 is being charged through formula (4), so the first mobile charging vehicle x k adjusts the charging path and skips the chargeable node s4, and directly goes to the chargeable node s3 for charging (see the adjusted charging path of x k ). In Figure 5 , the first mobile charging vehicle x k is charging the chargeable node s6, while the second mobile charging vehicle z k is also ready to go to the chargeable node s6 for charging (see the original charging path of z k ). At this time, the second mobile charging vehicle z k judges that the chargeable node s6 is being charged through formula (4), so the second mobile charging vehicle z k adjusts the charging path and skips the chargeable node s6, and directly goes to the chargeable node s8 for charging (see the adjusted charging path of z k ).

[0103] In steps E and F, in order to avoid that the mobile charging vehicle runs out of power halfway and cannot return to the base station, the mobile charging vehicle will also judge whether the mobile charging vehicle has enough power to return to the base station after completing the charging task according to the residual power of the chargeable node and the residual power of the mobile charging vehicle before charging each chargeable node, and perform different operations according to the judgment result. The judgment formula three is as follows:

[0104] E current ≥ p m × (d(s i )+d(s i ,BS))+(E ’– e i r ) (6)

[0105] Wherein, E current represents the current residual power of the mobile charging vehicle, p mThe energy consumption of the mobile charging vehicle for moving a unit distance can be obtained from the mobile charging vehicle manufacturer m , d(s i ) represents the Euclidean distance of the mobile charging vehicle from the current position to the chargeable node s i .

[0106] If formula (6) is not established, it means that the charging of the chargeable node s i by the mobile charging vehicle will cause the mobile charging vehicle to be unable to return to the base station, at which time the mobile charging vehicle is controlled to give up charging the chargeable node s i and is directly controlled to return to the base station to replace the battery. If formula (6) is established, the mobile charging vehicle is controlled to continue to charge the chargeable node s i .

[0107] In the embodiments of the present application, in order to further improve the energy utilization rate of the mobile charging vehicle, when a mobile charging vehicle completes the charging task for the last target object in the current round, if there is still sufficient energy, the charging operation is continued, otherwise the mobile charging vehicle returns to the base station to replace the battery, and when a new charging request is generated in the node group in which the mobile charging vehicle is located, the charging operation of steps E and F is re-executed.

[0108] For the first mobile charging vehicle, if the remaining energy after completing a round of charging task is higher than ηE M , the first mobile charging vehicle does not return to the base station, and the first mobile charging vehicle is controlled to continue to traverse the nodes with remaining energy lower than E0in the clockwise or counterclockwise direction of the TSP path of the node group, and charge the nodes to E', until formula (6) is not established or there is no node with remaining energy lower than E0in the node group, the first mobile charging vehicle returns to the base station and replaces the battery, and when a new charging request is generated in the node group in which the mobile charging vehicle is located or when the next offline charging period arrives, the offline scheduling algorithm is executed again to perform partial charging for the nodes along the predetermined route. Wherein, E M is the full energy value of the mobile charging vehicle, and η is a preset percentage value, in the embodiments of the present application, η is preferably 30%.

[0109] For the second mobile charging vehicle, if the remaining energy after completing a round of charging task is higher than ηE M , the second mobile charging vehicle continues to charge the nodes in the current node group which have not been served by any mobile charging vehicle in the current round and have remaining energy lower than E0in the order of the values of the chargeable nodes c i from large to small, to E', until formula (6) is not established or there is no node in the node group that meets the above conditions, the second mobile charging vehicle returns to the base station and replaces the battery, and waits for a new charging request to be generated in the node group, and the online charging algorithm is executed again to perform partial charging for the chargeable nodes according to the charging request.

[0110] The method of the present application can master the attribute information of all chargeable nodes in the wireless chargeable sensor network by carrying out information interaction between the chargeable nodes and the base station, and then divide all the nodes in the network into K groups under double constraints, wherein the chargeable nodes in each node group are close to each other, and the total charging capacity required also conforms to the capacity of the existing mobile charging vehicle. When the mobile charging vehicle charges these chargeable nodes, the time of movement can be reduced, the charging efficiency can be improved as much as possible, and the rationalized grouping design is realized. The method of the present application adopts the mobile charging vehicle scheduling technology combining offline and online, in the offline scheduling aspect, the TSP path of all chargeable nodes in the connected node group is established, and the first mobile charging vehicle in each group is controlled according to the TSP path to carry out offline charging task. The offline charging can be started according to the preset period, or can be started after receiving the charging request, so that the target of offline charging is more targeted. In the online scheduling aspect, the second mobile charging vehicle charges the nodes in time according to the charging request of the chargeable nodes, improves the real-time and accuracy of charging, and can effectively reduce the number of dead nodes.

[0111] In the method of the present application, each mobile charging vehicle will check whether the service object is being charged before charging each service object, which can effectively avoid possible wireless charging conflicts and reduce charging costs. In addition, the mobile charging vehicle will also judge whether the remaining power is sufficient to return to the base station before each charging, to ensure the automation and sustainability of the entire charging process, without the need for manual recovery of the mobile charging vehicle with no power.

[0112] After the mobile charging vehicle completes the charging task of the last target object in the current round, if there is still sufficient energy, it can continue to perform the corresponding charging operation, so that the present application can maximize the utilization of the circuit of the mobile charging vehicle, reduce waste, and further reduce the charging cost.

[0113] The method of the present application combines offline and online scheduling operations, which not only meets the needs of nodes in urgent need of charging, but also takes into account the energy of other nodes in the network, improves the reliability and stability of the wireless chargeable sensor network, and prolongs the life cycle of the wireless chargeable sensor network.

[0114] The above only describes the preferred embodiments of the present application, and it should be noted that those skilled in the art can make some improvements and modifications without departing from the technical principles of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims

1. An offline-online combined mobile charging vehicle scheduling method, characterized in that, The method comprises the following steps: According to the attribute information of each chargeable node in the wireless chargeable sensor network, the energy consumption rate and the normalized charging cost of each chargeable node are calculated; According to the attributes, energy consumption rate and normalized charging cost of the chargeable node, the chargeable nodes in the wireless chargeable sensor network are divided into multiple node groups under the charging cost constraint and distance constraint, and a node information table is generated; According to the node information table, the TSP path of all chargeable nodes in each node group is planned; Based on the offline scheduling algorithm, the first mobile charging vehicle corresponding to each node group is controlled according to the TSP path of the node group, and the chargeable nodes in the node group are charged; Based on the online scheduling algorithm, the second mobile charging vehicle corresponding to each node group is controlled according to the charging request issued by the chargeable nodes in the node group, and the chargeable nodes issuing the charging request are charged; The grouping of the chargeable nodes comprises: (1) all chargeable nodes in the wireless chargeable sensor network are sorted according to the value of the normalized charging cost from large to small to obtain a first queue Q; (2) the first chargeable node in the first queue Q is taken as a member of a first node group Cluster1 and added to the first node group Cluster1, and K=1 is recorded, and the first chargeable node is deleted from the first queue Q; (3) Starting from k=1 and continuing until k=K, sequentially determine the first rechargeable node s in the current first queue Q. j Join the k-th node group Cluster k Then, the k-th node group Cluster k Does it satisfy the charging cost constraint and distance constraint? If the k-th node group (Cluster) k To satisfy the charging cost constraint and distance constraint, the rechargeable node s j Join the k-th node group Cluster k Update the k-th node group (Cluster) k Charging cost C k and center of mass k At the same time, remove the rechargeable node s from the current first queue Q. j If all node groups do not satisfy the charging cost constraint and distance constraint, then the current rechargeable node s will be... j As the K+1th node group, Cluster k+1 Members join the (K+1)th node group, Cluster. k+1 In this context, let K = K+1, and simultaneously, remove rechargeable node s from the current first queue Q. j Where j∈[1, N], and N is the total number of rechargeable nodes in the wireless rechargeable sensor network; (4) step (3) is repeated until the first queue Q is empty, and K node groups are obtained; The charging cost constraint is: C k < C’ ; wherein C k represents the chargeable node s j joins the node group Cluster k the node group Cluster k the charging cost of the node s k is the sum of the normalized charging costs of all chargeable nodes in the node group Cluster k C' is a preset cost threshold value; Rechargeable nodes j Join the node group Cluster k Then, connect adjacent rechargeable nodes in a straight line to form a node cluster. k All rechargeable nodes in the cluster form a polygon, according to the node group Cluster k The centroid of the polygon is calculated from the coordinates of all rechargeable nodes in the polygon, and denoted as the node group Cluster. k Center of mass k The distance constraint is: d(s j , Center k ) ≤d(s j ,BS) ; where d(s j , Center k ) denotes the distance from a chargeable node s j to the centroid Center k after the node s k joins the cluster Cluster k , and d(s j , BS) denotes the distance from the chargeable node s j to the base station.

2. The off-line and on-line combined mobile charging vehicle scheduling method according to claim 1, characterized in that, The attribute information of each chargeable node in the wireless chargeable sensor network comprises node ID, node coordinates and node residual capacity. 3.The offline-online combined mobile charging vehicle scheduling method according to claim 2, characterized in that, According to the attribute information of each chargeable node in the wireless chargeable sensor network, the energy consumption rate and the normalized charging cost of each node are calculated, comprising: The energy consumption rate of each chargeable node is calculated according to the node residual capacity of each chargeable node, and the calculation formula is as follows: p i ﹦P i ’ / t; P i ’=E s -E i,t ; wherein p i is the energy consumption rate of the i-th chargeable node, P i is the amount of electricity consumed by the i-th chargeable node from 0 to the t moment, i ∈ [1, N], N is the total number of chargeable nodes in the wireless chargeable sensor network, E s is the initial amount of electricity of the chargeable node, E i,t is the node residual amount of electricity of the i-th chargeable node at the t moment; The distance of each chargeable node to the base station is calculated according to the node coordinates of each chargeable node; The normalized charging cost of each chargeable node is calculated according to the distance of each chargeable node to the base station and the energy consumption rate of the chargeable node, and the calculation formula is as follows: c i + a x p i + b x d(s i , BS) ; Among them, c i Let be the normalized charging cost of the i-th rechargeable node, where α and β are normalized charging coefficients, α and β ∈ [0,1], and α + β = 1. d ( s i , BS ) is the first i One rechargeable node s i to base station BS Euclidean distance.

4. The off-line and on-line combined mobile charging van scheduling method according to claim 1, characterized in that, The node information table comprises N row vectors, each row vector corresponding to a chargeable node, and each row vector comprising node ID, node coordinates, node energy consumption rate, node residual capacity, normalized charging cost and node group number.

5. The off-line and on-line combined mobile charging van scheduling method according to claim 1, characterized in that, Based on the online scheduling algorithm, the second mobile charging vehicle corresponding to each node group is controlled according to the charging request issued by the chargeable nodes in the node group, and the chargeable nodes issuing the charging request are charged, comprising: The obtained charging request of the chargeable node is sequentially added to the charging request queue Q' of the node group; According to the order of the charging requests in the charging request queue Q', the second mobile charging vehicle corresponding to the node group is controlled to sequentially go to each chargeable node corresponding to the charging request and charge the chargeable node to E', which is a preset charging value; Whenever the second mobile charging vehicle serves a chargeable node, the charging request of the chargeable node is deleted from the charging request queue Q' according to the node ID of the chargeable node.

6. The off-line and on-line combined mobile charging vehicle scheduling method according to claim 1, characterized in that, Before the first mobile charging vehicle or the second mobile charging vehicle charges any one of the chargeable nodes, it is checked through information interaction whether the chargeable node is being charged; if the chargeable node is being charged, the first mobile charging vehicle or the second mobile charging vehicle is controlled to move to the next chargeable node; If the chargeable node is not being charged, it is judged whether the residual power of the chargeable node is greater than a preset safety threshold; If the residual power of the chargeable node is greater than the preset safety threshold, the first mobile charging vehicle or the second mobile charging vehicle is controlled to move to the next chargeable node; If the residual power of the chargeable node is not greater than the preset safety threshold, the first mobile charging vehicle or the second mobile charging vehicle is controlled to charge the chargeable node.

7. The off-line and on-line combined mobile charging van scheduling method according to claim 1, characterized in that, Before the first mobile charging vehicle or the second mobile charging vehicle charges any one of the chargeable nodes, the residual power of the chargeable node and the residual power of the mobile charging vehicle are combined to judge whether the first mobile charging vehicle or the second mobile charging vehicle has enough power to return to the base station after completing the charging task, and the judgment formula three is as follows: E current ≥p m × (d(s i )+d(s i ,BS))+(E’ – e i r ) ; wherein E current represents the current remaining battery level of the mobile charging vehicle, p m represents the energy consumption of the mobile charging vehicle moving a unit distance, d(s i ) represents the Euclidean distance from the current location of the mobile charging vehicle to the chargeable node s i . If the judgment formula three is established, the first mobile charging vehicle or the second mobile charging vehicle is controlled to charge the chargeable node, otherwise, the current charging task is abandoned, and the first mobile charging vehicle or the second mobile charging vehicle is controlled to return to the base station to replace the battery. 8.The offline-online combined mobile charging vehicle scheduling method according to claim 7, characterized in that, When the first mobile charging vehicle completes the charging task of the last chargeable node in the node group along the TSP path, if the remaining power of the first mobile charging vehicle is greater than ηE M , the first mobile charging vehicle does not return to the base station, and controls the first mobile charging vehicle to continue charging the chargeable nodes with power less than E0in the node group to E' along the TSP path until the judgment formula three is not true or there is no chargeable node with power less than E0in the node group of the first mobile charging vehicle, wherein E M is the full power value of the mobile charging vehicle, η is a preset percentage value, E' is a preset charging value, and E0is a preset safety threshold. When the second mobile charging vehicle finishes all charging requests from chargeable nodes in the node group where it is located, if the remaining power of the second mobile charging vehicle is greater than ηE M , the second mobile charging vehicle does not return to the base station, and controls the second mobile charging vehicle to traverse all chargeable nodes in the node group where it is located in descending order of normalized charging cost, and charges the chargeable nodes that have not been charged in the current round and whose remaining power is lower than E0to E' until the third judging formula is not true or there is no chargeable node in the node group where the second mobile charging vehicle is located that has not been charged in the current round and whose remaining power is lower than E0; wherein the current round refers to the time period from the last time the first mobile charging vehicle and the second mobile charging vehicle leave the base station to the current time.

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