CN114537197A - V2V charging optimal matching method and system based on weighted bipartite graph - Google Patents

Abstract

The invention discloses a V2V charging optimal matching method and a system based on weighted bipartite graph, wherein the method comprises the following steps: acquiring information such as electric quantity required by a charging vehicle, electric quantity provided by a discharging vehicle, estimated arrival time of the charging and discharging vehicle and the like; calculating the matching degree between charging and discharging vehicles; constructing a bipartite graph based on the matching degree of the charge-discharge vehicle; a matching mechanism based on a KM (Kuhn-Munkres) algorithm is proposed to obtain the best matching result of the weighted bipartite graph. Compared with the traditional matching method, the algorithm provided by the invention comprehensively considers the influence factors such as the electric quantity required by the charging vehicle, the electric quantity provided by the discharging vehicle, the charging waiting time and the like, can realize the optimal matching of the charging and discharging vehicles, and improves the charging experience of users; in addition, the algorithm has the advantages of small calculation complexity, high robustness, good expansibility, high convergence speed and the like, can quickly feed back the matching result to the user, and can efficiently adapt to large-scale charging and discharging matching demand scenes.

Description

An optimal matching method and system for V2V charging based on weighted bipartite graph

technical field

The invention belongs to the field of vehicle-to-vehicle charging, and in particular relates to an optimal matching method and system for V2V charging based on a weighted bipartite graph.

Background technique

With the increasing problems of energy shortage and environmental pollution, new energy vehicles have received more and more attention due to their advantages of zero emission, low noise, and efficient energy conversion, and have gradually become the mainstream trend of the development of the current automobile industry.

The charging methods of new energy vehicles are divided into grid-to-vehicle (G2V) charging, vehicle-to-vehicle (V2V) charging and battery replacement (Battery Swap, BS). The G2V charging mechanism is difficult to adapt to the vigorous development of the new energy vehicle industry, and cannot effectively meet the charging needs of a large number of new energy vehicles. The BS mechanism has various problems such as uneven quality of replacement batteries, and it is difficult to be popularized on a large scale. The V2V charging mechanism can be disconnected from the grid to carry out charging services, and the charging method is flexible and convenient, without the support of expensive charging facilities, which has attracted widespread attention.

In V2V charging, the matching of charging and discharging vehicles is very important. However, in the existing method, the information such as the arrival time interval of charging and discharging vehicles is not considered, which leads to the failure of charging and discharging vehicles to complete the optimal pairing, and as the charging and discharging of the parking point occurs As the number of vehicles increases, the time required for matching is longer, and the user experience is poor. Therefore, it is of great significance to study an efficient optimal matching method for V2V charging.

SUMMARY OF THE INVENTION

The purpose of the present invention is to propose an optimal matching method and system for V2V charging based on a weighted bipartite graph, so as to solve the problems of poor user experience and too long matching time mentioned in the above background technology, so as to make the best possible connection between vehicles. It is possible to exchange as much energy as possible, to minimize the inter-arrival time between the charged and discharged vehicles, and to minimize the difference between the demanded energy of the charged vehicle and the supplied energy of the discharged vehicle.

The technical solution that realizes the object of the present invention is:

An optimal matching method for V2V charging based on a weighted bipartite graph, comprising the following steps:

S1, obtain the power required by the charging vehicle, the power provided by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle;

S2, determine the matching degree between the charging and discharging vehicles;

S3, construct a weighted bipartite graph with the matching degree of the charging and discharging vehicle as the weight;

S4, determine the best matching result of the weighted bipartite graph through the KM algorithm.

A V2V charging optimal matching system based on a weighted bipartite graph, comprising a charging information collection module, a matching degree calculation module, a weighted bipartite graph building module and a matching module; wherein:

The charging information collection module is used to acquire the electricity demanded by the charging vehicle, the electricity supplied by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle;

The matching degree calculation module is used to determine the matching degree between charging and discharging vehicles;

The weighted bipartite graph building module is used to construct a weighted bipartite graph with the matching degree of the charging and discharging vehicle as the weight;

The matching module is used to determine the best matching result of the weighted bipartite graph through the KM algorithm.

Compared with the prior art, the present invention has the following remarkable effects:

(1) According to the obtained charging and discharging vehicle information, the present invention comprehensively considers the power demanded by the charging vehicle, the power provided by the discharging vehicle, and the waiting time for charging, etc., to calculate the matching degree of the charging and discharging vehicles, and realizes the best performance between the charging and discharging vehicles. It is possible to exchange more energy; minimize the arrival time interval of charging and discharging vehicles, reduce the waiting time of users; minimize the difference between the demanded energy of charging vehicles and the supply energy of discharging vehicles, and ensure the interests of discharging vehicle owners;

(2) The present invention establishes a weighted bipartite graph based on the calculated matching degree of charging and discharging vehicles, and abstracts the matching problem of charging and discharging new energy vehicles into a bipartite graph-based maximum weight matching problem. The proposed method is based on KM (Kuhn The optimal matching method of the weighted bipartite graph of the -Munkres) algorithm has the advantages of low computational complexity, high robustness, good scalability, and fast convergence speed. It can quickly feed back the matching results to users, and can efficiently adapt to large-scale Charge and discharge matching demand scenarios.

Description of drawings

FIG. 1 is a flow chart of the optimal matching method for V2V charging based on a weighted bipartite graph proposed by the present invention.

FIG. 2 is a schematic diagram of a specific flow for calculating the optimal matching proposed by the present invention.

FIG. 3 is a schematic diagram of a specific flow chart for updating a label proposed by the present invention.

FIG. 4 is a schematic diagram of realizing the optimal matching of V2V charging according to the present invention.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

This embodiment provides an optimal matching method for V2V charging based on a weighted bipartite graph. First, the vehicle that needs charging will tell the cloud server the required amount of electricity and the estimated time when the vehicle will arrive at the parking lot through the Internet of Vehicles, and then the cloud server will According to this information, the charging and discharging vehicles are matched, and finally the matching information is sent to the parking lot and the matching charging and discharging vehicles through the Internet of Vehicles.

1, the optimal matching method for V2V charging based on a weighted bipartite graph proposed by the present invention includes the following steps:

S1, obtain information such as the power demanded by the charging vehicle, the power provided by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle;

S2, calculate the matching degree between charging and discharging vehicles;

S3, design a bipartite graph with the matching degree of charging and discharging vehicles as the weight;

S4, calculate the best matching result of the weighted bipartite graph through the KMKM (Kuhn-Munkres) algorithm.

In the step S2 of this embodiment, according to information such as the amount of electricity required by the charging vehicle, the amount of electricity provided by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle, the matching degree of the charging and discharging vehicle is divided into the following two cases.

Case 1: When the energy required by the charging vehicle u is greater than the energy provided by the discharging vehicle v, or the time difference between the charging vehicle u and the discharging vehicle v arriving is greater than the set maximum value, it means that the matching of the charging and discharging vehicle is invalid, and the matching degree Defined as follows:

ω(u, v)=0

where ω(u, v) represents the matching degree between the charging vehicle u and the discharging vehicle v, and 0 means that the charging and discharging vehicles do not match.

Case 2: When the energy required by the charging vehicle u is less than the energy provided by the discharging vehicle v, and the arrival time difference between the charging vehicle u and the discharging vehicle v is less than the set maximum value, it means that the matching of the charging and discharging vehicles is effective, and the matching degree is Defined as follows:

表示待充电车辆u所需的电量，C表示新能源汽车的电池容量，TG表示系统允许的充放电车辆到达时间差的最大值，TG(u，v)表示充电车辆u和放电车辆v到达的时间差，EG_max表示所有充放电车辆能量差的最大值，EG_min表示所有充放电车辆能量差的最小值，EG(u，v)是充电车辆u所需的能量和放电车辆v能提供的能量的差值。α₁、α₂、α₃是每个目标的权重系数，他们每一个都大于0，而且α₁+α₂+α₃＝1。ω(u，v)表示充电车辆u和放电车辆v之间的匹配度，并且ω(u，v)越大，表示充电车辆u和放电车辆v越匹配。in

Represents the power required by the vehicle u to be charged, C represents the battery capacity of the new energy vehicle, TG represents the maximum time difference between the arrival of the charging and discharging vehicle allowed by the system, and TG(u, v) represents the arrival time difference between the charging vehicle u and the discharging vehicle v , EG _max represents the maximum value of the energy difference between all charging and discharging vehicles, EG _min represents the minimum value of the energy difference between all charging and discharging vehicles, EG(u, v) is the difference between the energy required by charging vehicle u and the energy provided by discharging vehicle v difference. α ₁ , α ₂ , and α ₃ are weight coefficients for each target, each of which is greater than 0, and α ₁ +α ₂ +α ₃ =1. ω(u, v) represents the degree of matching between the charged vehicle u and the discharged vehicle v, and the larger ω(u, v) is, the more matched the charged vehicle u and the discharged vehicle v are.

In the step S3 of this embodiment, a bipartite graph G=(U, V, E) and a matching subgraph M=(U, V, E′ _t ) are established according to the matching degree of charging and discharging vehicles, where U represents the set of charging vehicles, V represents the set of discharging vehicles, and E represents the set that can be matched between charging and discharging vehicles, that is, the edge e=(u, v) in the bipartite graph, e∈E, u∈U, v∈V. Each edge has a weight, and the weight is the matching degree between charging and discharging vehicles. E' _t represents the set of matched edges, and E' _t ∈ E, M represents a subgraph of the bipartite graph G that contains only matched edges.

The step S4 in this embodiment includes the following steps:

S4.1, initialize a label y for each vehicle;

S4.2, judge whether the maximum match is found, if not, execute S4.3, otherwise the algorithm ends;

S4.3, judge whether there is an augmentation path, if so, execute S4.4, otherwise execute S4.5;

S4.4, search for an augmented path from the unmatched charging vehicle, update the matching set _E't and the matching subgraph M, and then execute S4.2;

S4.5, update the label, add the found new edge to the matching set E' _t and the matching subgraph M, and then execute S4.2.

In the step S4.1 of this embodiment, the label of the vehicle to be charged is initialized to the maximum matching degree with all discharged vehicles, and the label of the discharged vehicle is initialized to zero, which is expressed as follows:

where y(u) represents the label of the charged vehicle u, y(v) represents the label of the discharged vehicle v, U represents the set of charged vehicles, V represents the set of discharged vehicles, and ω(u, v) represents the charged vehicle calculated in claim 2 The matching degree between u and the discharging vehicle v. Definition When y(u)+y(v)=ω(u,v), e(u,v) is a candidate path.

In the step S4.5 of this embodiment, as shown in FIG. 3 , in the process of searching for the augmented road, the charging vehicle and the discharging vehicle that have not passed, calculate the label y(u) of the charging vehicle plus the discharge The minimum value of the vehicle's label y(v) minus the weight ω(u, v) between them. Then, subtract this minimum value from the label y(u) of the charged vehicle that has reached in the process of finding the augmented road, add this minimum value to the label y(v) of the discharged vehicle that has reached in the process of finding the augmented road, and update the label The way is as follows:

ψ=min{y(u)+y(v)-ω(u,v)|u∈U′, v∈V/V′}

Among them, U' represents the set of charged vehicles that have arrived in the process of finding the augmented path, V' represents the set of discharged vehicles that have arrived in the process of finding the augmented path, ψ represents the minimum value calculated in the set, and y(u) The label y(v) representing the charged vehicle u represents the label of the discharged vehicle v. Finally, the edge of the newly found minimum is added to _E't and M.

According to this implementation method, the optimal matching effect of V2V charging is shown in Figure 4, in which there are 3 charging vehicles and 4 discharging vehicles, and the number next to the connection represents the matching degree. Through the above method, the optimal matching is achieved. The thick line in the figure represents the matching result, u1 matches v4, u2 matches v3, and u3 matches v1.

Compared with the traditional matching method, the algorithm proposed in the present invention comprehensively considers the influencing factors such as the power demand of the charging vehicle, the power supplied by the discharging vehicle and the charging waiting time, etc., which can realize the optimal matching of the charging and discharging vehicles and improve the charging experience of the user; in addition, the algorithm It has the advantages of low computational complexity, high robustness, good scalability, and fast convergence speed. It can quickly feedback matching results to users, and can efficiently adapt to large-scale charging and discharging matching demand scenarios.

Of course, those skilled in the art should realize that the above-mentioned embodiments are only used to illustrate the present invention, but not to limit the present invention, as long as the changes to the above-mentioned embodiments are within the essential spirit of the present invention , modifications will fall within the scope of the claims of the present invention.

Claims (10)

1. a V2V charging optimal matching method based on a weighted bipartite graph, is characterized in that, comprises the following steps: S1, obtain the power required by the charging vehicle, the power provided by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle; S2, determine the matching degree between the charging and discharging vehicles; S3, construct a weighted bipartite graph with the matching degree of the charging and discharging vehicle as the weight; S4, determine the best matching result of the weighted bipartite graph through the KM algorithm. 2. A kind of V2V charging optimal matching method based on a weighted bipartite graph according to claim 1, is characterized in that, in described step S2, the matching degree of charging and discharging vehicle is divided into two kinds of situations to determine: Case 1, when the energy required by the charging vehicle u is greater than the energy provided by the discharging vehicle v, or the estimated time difference between the charging vehicle u and the discharging vehicle v is greater than the set maximum value; In case 2, when the energy required for charging the vehicle u is less than the energy that can be provided by the discharging vehicle v, and the expected time difference between the charging vehicle u and the discharging vehicle v is less than the set maximum value. 3. a kind of V2V charging optimal matching method based on a weighted bipartite graph according to claim 2, is characterized in that, the matching degree of described situation 1 is: ω(u,v)=0 where ω(u, v) represents the matching degree between the charging vehicle u and the discharging vehicle v, and 0 means that the charging and discharging vehicles do not match. 4. a kind of V2V charging optimal matching method based on a weighted bipartite graph according to claim 2, is characterized in that, the matching degree of described situation 2 is:

in

Represents the power required by the vehicle u to be charged, C represents the battery capacity of the new energy vehicle, TG represents the maximum allowable arrival time difference between the charging and discharging vehicles, TG(u, v) represents the expected arrival time difference between the charging vehicle u and the discharging vehicle v , EG _max represents the maximum value of the energy difference of all charging and discharging vehicles, EG _min represents the minimum value of the energy difference of all charging and discharging vehicles, EG(u, v) is the difference between the energy required by charging vehicle u and the energy provided by discharging vehicle v difference; α ₁ , α ₂ , α ₃ are weight coefficients; ω(u,v) represents the matching degree between the charging vehicle u and the discharging vehicle v, the larger ω(u,v) is, the more the charging vehicle u and the discharging vehicle are. The more the vehicle v is matched. 5 . The optimal matching method for V2V charging based on a weighted bipartite graph according to claim 4 , wherein the α ₁ , α ₂ , and α ₃ are all greater than 0, and α ₁ +α ₂ +α ₃ = 1. 6. The optimal matching method for V2V charging based on a weighted bipartite graph according to claim 1, wherein the step S3 constructing a weighted bipartite graph with the matching degree of the charging and discharging vehicle as a weight specifically comprises: establishing a The bipartite graph G=(U, V, E) and the matching subgraph M=(U, V, E′ _t ), where U represents the set of charging vehicles, V represents the set of discharging vehicles, and E represents the matching between charging and discharging vehicles Set, that is, the edge e=(u, v) in the bipartite graph, e∈E, u∈U, v∈V, each edge has a weight, the weight is the matching degree between the charging and discharging vehicles, E′ _t represents The set of matched edges, and E′ _t ∈ E, M represents a subgraph of the bipartite graph G that contains only matched edges. 7. The optimal matching method for V2V charging based on a weighted bipartite graph according to claim 1, wherein the step S4 specifically comprises: S4.1, initialize a label y for each vehicle; S4.2, judge whether the maximum match is found, if not, execute S4.3, otherwise the algorithm ends, and the best match result is obtained; S4.3, judge whether there is an augmentation path, if so, execute S4.4, otherwise execute S4.5; S4.4, search for an augmented path from the unmatched charging vehicle, update the matching set _E't and the matching subgraph M, and then execute S4.2; S4.5, update the label, add the found new edge to the matching set E' _t and the matching subgraph M, and then execute S4.2. 8. The optimal matching method for V2V charging based on a weighted bipartite graph according to claim 7, wherein in the step S4.1, initializing a label y for each vehicle comprises: initializing the label of the vehicle to be charged For the maximum matching degree with all discharged vehicles, the label of the discharged vehicle is initialized to zero, which is expressed as:

where y(u) represents the label of the charging vehicle u, y(v) represents the label of the discharging vehicle v, U represents the set of charging vehicles, and V represents the set of discharging vehicles; Definition When y(u)+y(v)=ω(u,v), e(u,v) is a candidate path. 9. the V2V charging optimal matching method based on the weighted bipartite graph according to claim 7, is characterized in that, the method that label is updated in described step S4.5 is: ψ=min{y(u)+y(v)-ω(u,v)|u∈U′, v∈V/V′}

Among them, U' represents the set of charged vehicles that have arrived in the process of finding the augmented road, V' represents the set of discharged vehicles that have reached the process of finding the augmented road, ψ represents the minimum value calculated in the set, and y(u) represents the label of the charged vehicle u, and y(v) represents the label of the discharged vehicle v. 10. An optimal matching system for V2V charging based on a weighted bipartite graph based on any one of the methods of claims 1 to 9, characterized in that it comprises a charging information collection module, a matching degree calculation module, and a weighted bipartite graph construction module and matching modules; where: The charging information collection module is used to acquire the electricity demanded by the charging vehicle, the electricity supplied by the discharging vehicle, and the expected arrival time of the charging and discharging vehicle; The matching degree calculation module is used to determine the matching degree between charging and discharging vehicles; The weighted bipartite graph building module is used to construct a weighted bipartite graph with the matching degree of the charging and discharging vehicle as the weight; The matching module is used to determine the best matching result of the weighted bipartite graph through the KM algorithm.

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