CN112435061B - Electric automobile growth rate determination method and device based on SI infectious disease model - Google Patents
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Abstract
The invention discloses an electric vehicle growth rate determining method and device based on an SI infectious disease model. The method and the device solve the technical problems that in the prior art, a method for evaluating the satisfaction degree of the user on the electric automobile from a macroscopic view does not exist, and the increase rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realize evaluation of the satisfaction degree of the user on the electric automobile from a macroscopic view through simple parameters, further determine the increase rate of the electric automobile, and provide a new basis for judging the development trend of the electric automobile.
Description
Technical Field
The embodiment of the invention relates to the technical field of electric automobiles, in particular to a method and a device for determining the growth rate of an electric automobile based on an SI infectious disease model.
Background
With the increasing problems of climate change, energy crisis and environmental pollution, especially air pollution caused by automobile emission is a major problem in environmental governance in large cities, and research and investment on electric automobiles are increasing worldwide.
As electric vehicles are gradually accepted by people, electric vehicles are popularized, but at present, there is no clear method for evaluating the satisfaction degree of users on the electric vehicles from a macroscopic perspective, so that governments or individuals can make judgments on the development trend of the electric vehicles according to the satisfaction degree of users on the electric vehicles.
Disclosure of Invention
The invention provides a method and a device for determining the growth rate of an electric vehicle based on an SI infectious disease model, which solve the technical problems that no method exists for evaluating the satisfaction degree of a user on the electric vehicle from a macroscopic view and determining the growth rate of the electric vehicle according to the satisfaction degree of the user on the electric vehicle.
The embodiment of the invention provides an electric automobile growth rate determining method based on an SI infectious disease model, which comprises the following steps:
calculating the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city;
determining a user's overall satisfaction value for charging stations based on inter-city driving arrival rates, a proportion of long distance drivers, the user's satisfaction with the number of destination charging stations, and the user's satisfaction with the number of super charging stations within the city;
establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile;
and determining the growth rate of the electric automobile according to the SI infectious disease model.
Further, the calculating of the user's satisfaction with the number of destination charging stations and the user's satisfaction with the number of super charging stations in the city comprises:
calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle;
and calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric vehicle.
Further, the calculating of the user satisfaction with the number of destination charging stations based on the number of destination charging stations and the electric vehicle permeability comprises:
according to the formulaCalculating user satisfaction with the number of destination charging stations, wherein DNL is user satisfaction with the number of destination charging stations and DTL is calculated now The number of current destination charging stations, the DTL is the total number of destination charging stations when the fuel vehicles are replaced by electric vehicles and the gas stations are replaced by charging stations, and the PT is the electric vehicle permeability.
Further, the calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the electric vehicle permeability comprises:
according to the formulaCalculating the satisfaction degree of the user to the number of super charging stations in the city, wherein the SNL is the satisfaction degree of the user to the number of super charging stations in the city, and the STL is the satisfaction degree of the user to the number of super charging stations in the city c_now For the number of super charging stations in the current city, STL c When the fuel vehicles are replaced by the electric vehicles and the gas stations are replaced by the charging stations, the total number of the super charging stations is calculated, and PT is the permeability of the electric vehicles.
Further, by the formulaCalculating the electric vehicle permeability, wherein N sum Is the total number of electric vehicles; m sum Is the total number of fuel vehicles and electric vehicles.
Further, the determining a user's overall satisfaction value for charging stations based on driving arrival rates between cities, a proportion of long distance drivers, the user's satisfaction with the number of destination charging stations, and the user's satisfaction with the number of super charging stations within a city comprises:
calculating a total satisfaction value of a user for charging stations according to the formula D = w × RL + (1-w) × (a × SNL + DNL), wherein D is the total satisfaction value, w is a proportion of long distance drivers, a is a proportion of short distance drivers who forget to charge, RL is a driving arrival rate between cities, DNL is the satisfaction degree of the user for the number of destination charging stations, and SNL is the satisfaction degree of the user for the number of super charging stations in cities.
Further, the establishing of the SI infectious disease model based on the overall satisfaction value of the user on the electric automobile comprises the following steps:
according to the formulaCalculating to obtain the number of the electric vehicles effectively used every day, wherein lambda is the number of the electric vehicles effectively used every day, and X is a preset threshold; d is the overall satisfaction value, and P is the number of people who use fuel automobiles but come into contact with electric automobile owners every day.
Further, the determining the growth rate of the electric vehicle according to the SI infectious disease model comprises:
for is toCalculating an integral to obtain the number of increases of the electric automobile every year, wherein i is the occupancy of the current electric automobile; lambda is the number of people who effectively use the electric vehicle per day; i.e. i 0 Is an initial value of the electric vehicle;
calculating an annual electric vehicle growth rate based on the annual electric vehicle growth number.
The embodiment of the invention also provides an electric automobile growth rate determining device based on the SI infectious disease model, which comprises:
the first calculation module is used for calculating the satisfaction degree of the user on the number of the destination charging stations and the satisfaction degree of the user on the number of the super charging stations in the city;
a first determination module for determining a total satisfaction value of a user for charging stations based on driving arrival rate between cities, a proportion of long distance drivers, the satisfaction of the user with the number of destination charging stations, and the satisfaction of the user with the number of super charging stations in the city;
the establishment module is used for establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile;
and the second determination module is used for determining the growth rate of the electric automobile according to the SI infectious disease model.
Further, the first calculation module includes:
the first calculation submodule is used for calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle;
and the second calculation submodule is used for calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the electric automobile permeability.
The invention discloses an electric vehicle growth rate determining method and device based on an SI infectious disease model. The method solves the technical problems that in the prior art, the method for evaluating the satisfaction degree of the user on the electric automobile from the macroscopic view does not exist, and the growth rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realizes evaluation of the satisfaction degree of the user on the electric automobile from the macroscopic view through simple parameters, further determines the growth rate of the electric automobile, and provides a new basis for judging the development trend of the electric automobile.
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FIG. 1 is a flowchart of a method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 2 is a flowchart of another method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 3 is a flowchart of a method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 4 is a flowchart of a method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 5 is a flowchart of a method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 6 is a flowchart of a method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 7 is a flowchart of a method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 8 is a graph of an occupancy of an electric vehicle as a function of an infection rate according to an embodiment of the present invention;
FIG. 9 is a flowchart of a method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention;
FIG. 10 is a flow chart of constructing a two-layer complex network model according to an embodiment of the present invention;
fig. 11 is a structural diagram of an electric vehicle growth rate determination apparatus based on an SI infectious disease model according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that the terms "first", "second", and the like in the description and claims of the present invention and the accompanying drawings are used for distinguishing different objects, and are not used for limiting a specific order. The following embodiments of the present invention may be implemented individually, or in combination with each other, and the embodiments of the present invention are not limited in this respect.
In life, people decide whether to use a traditional automobile or an electric automobile according to the satisfaction degree of the electric automobile, which is mainly measured by the number density and the position of charging stations. When a person is very satisfied with the electric automobile, the person can tell the advantages of the electric automobiles of friends and family, so that the surrounding people have certain possibility to be persuaded by the person to use the electric automobile.
Fig. 1 is a flowchart of a method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention.
As shown in fig. 1, the method for determining the growth rate of the electric vehicle based on the SI infectious disease model specifically includes the following steps:
step S201, calculating the satisfaction degree of the user on the number of the destination charging stations and the satisfaction degree of the user on the number of the super charging stations in the city.
Specifically, since users who like different preferences have different demands for the kinds of charging stations, it is necessary to separately calculate the satisfaction of different users with respect to the number of different charging stations, divide the satisfaction calculation into the satisfaction of the user who drives short and remembers charging with respect to the number of destination charging stations and the satisfaction of the user who drives short and forgets charging with respect to the number of super charging stations in a city according to the classification of the user preferences and the types of charging stations.
Step S202, determining the total satisfaction value of the user on the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city.
Specifically, after the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city are calculated, the total satisfaction value of the user on the charging stations is calculated according to the driving arrival rate between the cities and the proportion of long-distance drivers. The driving arrival rate between cities is used for representing the satisfaction degree of the user on the positions of the super charging stations on the expressway and the national road, namely the satisfaction degree of the user on the super charging stations between the cities is represented by the driving arrival rate between the cities.
Step S203, an SI infectious disease model is established based on the overall satisfaction value of the user to the electric automobile.
Specifically, in the SI infectious disease model, only two types, namely, a patient and a susceptible person, are included, and a user using an electric vehicle is regarded as a patient in the present application; users using conventional fuel vehicles are considered healthy persons; while the healthy people are infected with infectious diseases, that is, users using the conventional fuel vehicles may use electric vehicles, so the healthy people may also be infected as patients. And establishing an SI infectious disease model based on the theory and the overall satisfaction value of the user for the electric automobile, namely establishing an evaluation index system based on the SI infectious disease model.
And step S204, determining the growth rate of the electric automobile according to the SI infectious disease model.
Specifically, after the SI infectious disease model is established, the total satisfaction value of the user for the electric automobile is compared with a preset threshold value, the infection rate of the electric automobile, namely the number of people who effectively use the electric automobile in a certain time, is calculated, and the growth rate of the electric automobile is calculated according to the infection rate.
According to the method and the device, the satisfaction degree of the user on the number of the different types of charging stations is calculated, the overall satisfaction value of the user on the charging stations is further calculated, and finally the SI infectious disease model is established and obtained based on the overall satisfaction value, so that the growth rate of the electric automobile can be determined according to the SI infectious disease model. The method solves the technical problems that in the prior art, the method for evaluating the satisfaction degree of the user on the electric automobile from the macroscopic view does not exist, and the growth rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realizes the evaluation of the satisfaction degree of the user on the electric automobile from the macroscopic view through simple parameters, further determines the growth rate of the electric automobile, and provides a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the satisfaction degree of the user on the number of the destination charging stations and the satisfaction degree of the user on the number of the super charging stations in the city are calculated and optimized in the embodiment. Fig. 2 is a flowchart of another method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 2, the method for determining an electric vehicle growth rate based on an SI infectious disease model according to the embodiment includes the following steps:
step S301, calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle.
And S302, calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric vehicle.
Specifically, the electric vehicle permeability refers to a ratio of the number of electric vehicles to the total number of vehicles, and the satisfaction of the user with the number of destination charging stations can be calculated based on the number of destination charging stations and the electric vehicle permeability, and the satisfaction of the user with the number of super charging stations in the city can be calculated based on the number of super charging stations in the city and the electric vehicle permeability.
Step S303, determining the total satisfaction value of the user on the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city.
And step S304, establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile.
And S305, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method solves the technical problems that in the prior art, the method for evaluating the satisfaction degree of the user on the electric automobile from the macroscopic view does not exist, and the growth rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realizes the evaluation of the satisfaction degree of the user on the electric automobile from the macroscopic view through simple parameters, further determines the growth rate of the electric automobile, and provides a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the satisfaction degree of the user on the number of the destination charging stations is calculated based on the number of the destination charging stations and the permeability of the electric vehicle in the embodiment and is optimized. Fig. 3 is a flowchart of another method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 3, the method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to the embodiment includes the following steps:
step S401, according to the formulaCalculating user satisfaction with the number of destination charging stations, wherein DNL is user satisfaction with the number of destination charging stations and DTL is calculated now The number of current destination charging stations, the DTL is the total number of destination charging stations when the fuel vehicles are replaced by electric vehicles and the gas stations are replaced by charging stations, and the PT is the electric vehicle permeability.
Optionally by formulaCalculating the permeability of the electric automobile, wherein N sum Is the total number of electric vehicles; m is a group of sum Is the total number of fuel vehicles and electric vehicles.
And S402, calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric automobile.
And step S403, determining the total satisfaction value of the user to the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user to the number of destination charging stations and the satisfaction degree of the user to the number of super charging stations in the cities.
And step S404, establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile.
And step S405, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method solves the technical problems that in the prior art, the method for evaluating the satisfaction degree of the user on the electric automobile from the macroscopic view does not exist, and the growth rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realizes the evaluation of the satisfaction degree of the user on the electric automobile from the macroscopic view through simple parameters, further determines the growth rate of the electric automobile, and provides a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the satisfaction degree of the user for calculating the number of the super charging stations in the city based on the number of the super charging stations in the city and the electric vehicle permeability in the embodiment is optimized. Fig. 4 is a flowchart of another method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 4, the method for determining an electric vehicle growth rate based on an SI infectious disease model according to the embodiment includes the following steps:
step S501, calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the penetration rate of the electric vehicle.
Step S502, according to the formulaCalculating the satisfaction degree of the user on the number of super charging stations in the city, wherein the SNL is the satisfaction degree of the user on the number of super charging stations in the city, STL c_now For the number of super charging stations in the current city, STL c When the fuel vehicles are replaced by the electric vehicles and the gas stations are replaced by the charging stations, the total number of the super charging stations is calculated, and PT is the permeability of the electric vehicles.
Optionally by means of a formulaCalculating the permeability of the electric automobile, wherein N sum Is the total number of electric vehicles; m is a group of sum Is the total number of fuel vehicles and electric vehicles.
Step S503, determining the total satisfaction value of the user to the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user to the number of destination charging stations and the satisfaction degree of the user to the number of super charging stations in the cities.
Step S504, an SI infectious disease model is established based on the overall satisfaction value of the user to the electric automobile.
And step S505, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method and the device solve the technical problems that in the prior art, a method for evaluating the satisfaction degree of the user on the electric automobile from a macroscopic view does not exist, and the increase rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realize evaluation of the satisfaction degree of the user on the electric automobile from a macroscopic view through simple parameters, further determine the increase rate of the electric automobile, and provide a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the embodiment optimizes the total satisfaction value of the user to the charging stations determined based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user to the number of destination charging stations and the satisfaction degree of the user to the number of super charging stations in the cities. Fig. 5 is a flowchart of another method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 5, the method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to the embodiment includes the following steps:
step S601, calculating the satisfaction of the user on the number of destination charging stations and the satisfaction of the user on the number of super charging stations in the city.
Step S602, calculating a total satisfaction value of the user to the charging stations according to a formula D = w × RL + (1-w) × (a × SNL + DNL), where D is the total satisfaction value, w is a proportion of long distance drivers, a is a proportion of short distance drivers who forget to charge, RL is a driving arrival rate between cities, DNL is the satisfaction degree of the user to the number of destination charging stations, and SNL is the satisfaction degree of the user to the number of super charging stations in a city.
Specifically, RL is inter-city driving arrival rate, which refers to the probability that a drive can be made from city a to city B, and if the distance between city a and city B is too far and there is no super charging station midway, the reachability is 0, otherwise it is reachable; the satisfaction of the super charging station locations of the highway and the national road can be represented by an arrival rate RL. w is the proportion of long-distance drivers, i.e. the proportion of long-distance drivers to all drivers, and can be calculated by the formula w = PT × x. a is the proportion of the short-distance driver who forgets to charge and the proportion of the short-distance driver who forgets to charge in all the short-distance drivers, and can be calculated by the formula a = PT multiplied by y. Wherein PT is permeability; x is the number of long-distance drivers after full electric vehicle formation and full charging station formation; and y is a short-distance driver after full electric vehicle and full charging station.
The term "fully electric vehicle" and "fully charged vehicle" refer to cases where the fuel vehicle is replaced by an electric vehicle and the gas station is replaced by a charging station.
And step S603, establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile.
And step S604, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method and the device solve the technical problems that in the prior art, a method for evaluating the satisfaction degree of the user on the electric automobile from a macroscopic view does not exist, and the increase rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realize evaluation of the satisfaction degree of the user on the electric automobile from a macroscopic view through simple parameters, further determine the increase rate of the electric automobile, and provide a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the embodiment establishes the SI infectious disease model based on the overall satisfaction value of the user for the electric vehicle to optimize. Fig. 6 is a flowchart of another method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 6, the method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to the embodiment includes the following steps:
and step S701, calculating the satisfaction degree of the user on the number of the destination charging stations and the satisfaction degree of the user on the number of the super charging stations in the city.
Step S702, determining the total satisfaction value of the user to the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user to the number of destination charging stations and the satisfaction degree of the user to the number of super charging stations in the cities.
Step S703, according to the formulaCalculating the number of people who effectively use the electric automobile every day, wherein lambda is the number of people who effectively use the electric automobile every day, and X is a preset threshold; d is the overall satisfaction value, and P is the number of people who use the fuel automobile but will contact the electric automobile owner every day.
Specifically, in the infectious disease model, λ is a daily infection rate in the infectious disease model, i.e., the above-mentioned number of persons who effectively use electric vehicles per day, and X is a preset threshold; d is the overall satisfaction value. When D = X, the user maintains a neutral attitude to the electric automobile; when D > X, the user tends to purchase an electric vehicle; when D < X, the user tends to use the fuel automobile.
And step S704, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method and the device solve the technical problems that in the prior art, a method for evaluating the satisfaction degree of the user on the electric automobile from a macroscopic view does not exist, and the increase rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realize evaluation of the satisfaction degree of the user on the electric automobile from a macroscopic view through simple parameters, further determine the increase rate of the electric automobile, and provide a new basis for judging the development trend of the electric automobile.
Based on the technical scheme, the embodiment optimizes the growth rate of the electric vehicle determined according to the SI infectious disease model in the embodiment. Fig. 7 is a flowchart of another method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 7, the method for determining an increase rate of an electric vehicle based on an SI infectious disease model according to the embodiment includes the following steps:
step S801, calculating the satisfaction of the user with the number of destination charging stations and the satisfaction of the user with the number of super charging stations in the city.
Step S802, determining the total satisfaction value of the user on the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city.
Step S803, according to the formulaCalculating to obtain the number of the electric vehicles effectively used every day, wherein lambda is the number of the electric vehicles effectively used every day, and X is a preset threshold; d is the overall satisfaction value, and P is the number of people who use the fuel automobile but will contact the electric automobile owner every day.
Step S804, forCalculating an integral to obtain the number of increases of the electric automobile every year, wherein i is the occupancy of the current electric automobile; λ is the number of people who effectively use electric cars daily; i.e. i 0 Is an initial value of the electric vehicle.
Specifically, fig. 8 is a graph of occupancy of an electric vehicle as a function of infection rate, according to an embodiment of the present invention. As shown in fig. 8, the abscissa t represents time, and the ordinate represents the rate of change of the occupancy i with the infection rate λ, and curves of the rate of change when λ =0.3, 0.33, and 0.27 are exemplarily shown.
In step S805, the annual electric vehicle growth rate is calculated based on the annual electric vehicle growth count.
Specifically, after the number of electric vehicles per year is calculated according to step S804, the rate of electric vehicles per year can be calculated, and will not be described herein.
The method and the device solve the technical problems that in the prior art, a method for evaluating the satisfaction degree of the user on the electric automobile from a macroscopic view does not exist, and the increase rate of the electric automobile is determined according to the satisfaction degree of the user on the electric automobile, realize evaluation of the satisfaction degree of the user on the electric automobile from a macroscopic view through simple parameters, further determine the increase rate of the electric automobile, and provide a new basis for judging the development trend of the electric automobile.
The following describes a specific embodiment of a method for determining the growth rate of an electric vehicle based on the SI infectious disease model.
Fig. 9 is a flowchart of another method for determining an electric vehicle growth rate based on an SI infectious disease model according to an embodiment of the present invention. As shown in fig. 9, the method for determining the growth rate of an electric vehicle based on the SI infectious disease model specifically includes the following steps:
step S1001, by formulaCalculating the permeability of the electric automobile, wherein N sum Is the total number of electric vehicles; m is a group of sum Is the total number of fuel vehicles and electric vehicles.
Step S1002, according to the formulaCalculating user satisfaction with the destination charging stations, wherein DNL is user satisfaction with the number of destination charging stations and DTL now The number of current destination charging stations, the DTL is the total number of destination charging stations when the fuel vehicles are replaced by electric vehicles and the gas stations are replaced by charging stations, and the PT is the electric vehicle permeability.
Step S1003, according to the formulaCalculating the satisfaction degree of the user on the number of super charging stations in the city, wherein the SNL is the satisfaction degree of the user on the number of super charging stations in the city, STL c_now For the number of super charging stations in the current city, STL c When the fuel vehicles are completely replaced by the electric vehicles and the gas stations are completely replaced by the charging stations, the total number of the super charging stations is equal to the total number of the super charging stations, and PT is the permeability of the electric vehicles.
Step S1004, calculating a total satisfaction value of the user to the charging stations according to a formula D = w × RL + (1-w) × (a × SNL + DNL), where D is the total satisfaction value, w is a proportion of long distance drivers, a is a proportion of short distance drivers who forget to charge, RL is a driving arrival rate between cities, DNL is the satisfaction degree of the user to the number of destination charging stations, and SNL is the satisfaction degree of the user to the number of super charging stations in cities.
Step S1005, according to the formulaCalculating the number of people who effectively use the electric automobile every day, wherein lambda is the number of people who effectively use the electric automobile every day, and X is a preset threshold; d is the overall satisfaction value, and P is the number of people who use the fuel automobile but will contact the electric automobile owner every day.
Step S1006, forCalculating an integral to obtain the number of increases of the electric automobile every year, wherein i is the occupancy of the current electric automobile; λ is the number of people who effectively use electric cars daily; i all right angle 0 Is an initial value of the electric vehicle.
And step S1007, determining the growth rate of the electric automobile according to the SI infectious disease model.
The method for determining the growth rate of the electric automobile based on the SI infectious disease model has the advantages that parameters are simple, a curve of the trend of the infectious disease model development trend of the electric automobile is easy to fit, a clear concept is provided for the society from a macroscopic perspective, the method is easy to accept by the society, and a guiding effect is provided for government measures and the cognition of using the electric automobile by individuals.
Before establishing an evaluation index system based on an SI infectious disease model, the requirements of a user and the type of a charging station need to be analyzed, and indexes of the evaluation index system are determined according to an analysis result.
First, according to the current design of electric vehicles, charging station types can be divided into two types: a super charging station and a destination charging station. The super charging station is usually built on a main road, so that the vehicle can obtain enough electric quantity in a short time, and normal running can be quickly recovered; the destination charging station refers to a charging station which is mostly built in a company, a supermarket, a park and the like, that is, a person does not return to a vehicle immediately after leaving the vehicle, and therefore, in consideration of cost and practical benefits, site selection design for dividing the charging station into two types of charging stations, namely, a destination charging station and a super charging station, is most reasonable.
Secondly, according to the preference of the user, the users using the automobile can be divided into two types: users who prefer long distance driving and users who prefer short distance driving. Often, users who drive long distances span multiple cities, and certainly require super charging stations on the road, and therefore, the number and location of super charging stations is more important for users who prefer long distance driving. Most users who drive for a short distance live in the places of daily living, the users who drive for a short distance still need to be divided into two types of remembering to charge and forgetting to charge, the users who remember to charge do not need super charging stations, only need enough destination charging stations to satisfy their daily charging, the users who forget to charge may need super charging stations in the city, conveniently in time charge for electric automobile, therefore, to the users who forget to charge, the number of super charging stations in the city is more important than the destination charging stations.
Finally, in order to design the positions of the destination charging stations and the super charging stations from a macroscopic perspective, the charging station network is abstracted into a double-layer complex network, and the double-layer complex network can be used for determining the number, the positions and the distribution of the charging stations.
Fig. 10 is a flowchart for constructing a two-layer complex network model according to an embodiment of the present invention.
As shown in fig. 10, the two-layer complex network model includes an outer layer network model and an inner layer network model, wherein the outer layer network model is mainly used for studying the requirement of the user in long-distance driving on the super charging stations, so that the mileage anxiety distance can be introduced to determine the distribution of the super charging stations arranged between cities. The internal network model is mainly used for researching the requirements of long-distance driving users, short-distance driving users who remember to charge and short-distance driving users who forget to charge on the charging station. The super charging stations are required by the long-distance driving users and the short-distance driving users who forget to charge, the destination charging stations are required by the short-distance driving users who remember that the charging short-distance driving users need, therefore, cities are used as network nodes, roads between the cities are used as edges, the betweenness of the weighted network nodes is calculated, and the distribution of the super charging stations arranged in the cities, namely the first number of the super charging stations, is considered according to the importance of the cities; calculating the distribution of super charging stations in the city and the second number of the super charging stations by introducing user mileage anxiety of short-distance driving which forgets to charge; charging head loads companies were introduced to quantify the distribution of destination charging stations.
According to the above analysis, the evaluation of the indexes of the index system should include: the number of destination charging stations; number of super charging stations within a city; the number of super charging stations on the road (i.e., the number of super charging stations between cities).
Specifically, the construction of the double-layer complex network model comprises the following steps:
step S1, according to the formulaCalculating the number of super charging stations between cities, wherein L is the distance between the cities, E R Distance of mileage anxiety, N i Total number of charging cars for the ith city, N sum Total number of cars charged nationwide, K ij Is the number of inter-city super charging stations between the ith city and the jth city, K sum μ is a scaling factor for the number of super charging stations across the country.
And S2, determining the number of the super charging stations distributed among the cities based on the inter-city vehicle density.
And S3, after the number of the super charging stations set between the cities is determined, setting the super charging stations set between the cities on the shortest path between the two cities.
Step S4, according to the formula STL FC = DTL × a × rd determine first number of super charging stations within city, wherein STL FC Of said first number, a being users who drive for a short distance and forget to chargeScale, rd is the mileage anxiety factor;
step S5, according to the formulaDetermining the number of super charging stations required within each city, wherein STL i Is the number of super charging stations required in the ith city; STL is the total number of super charging stations required nationwide; CD (compact disc) i Is the vehicle density of the ith city.
Step S6, according to the formulaDetermining a second number of super charging stations within the city, wherein STL LT And for the second quantity, w is the proportion of users in long-distance driving to all users, M is the daily driving distance of the users in long-distance driving, and rho is a preset operator.
S7, constructing a weighting network by taking the cities as nodes and taking the distance between two adjacent cities as edges;
step S8, according to the formulaComputing the betweenness of network nodes, wherein n jl (i) Is node v j And node v l Number of shortest paths in between, and through another node v i ,n jl Is node v j And node v l The number of shortest paths between;
step S9, based on the network node betweenness obtained by calculation and a formula WB i =B i ×η 1 ×η 2 Calculating to obtain weighted network node betweenness, wherein WB i Is a weighted network node betweenness, eta 1 Is the ratio of a certain city population to the national population; eta 2 The ratio of the sum of the boundary lengths between the urban area of a certain city and all suburbs (town and district) around the urban area and the rural area to the total length of all calculated boundaries;
step S10, according to the formulaCalculating the number of said super charging stations within a city, wherein STL ci The number of super charging stations in a city; STL LT For the second number, β is the ratio of super charging stations to the total number of super charging stations on the roads in the city.
Step S11, dividing the total number of the rechargeable automobiles into a preset number of user groups based on the driving mileage of the rechargeable automobiles used by users within a preset time length;
step S12, charging total load formula L (S) i ,t,τ)=f(S i ,τ)×Φ(S i )×N sum ×μ((P,t,τ)|s i ) I =1, 2.., 6, the number of destination charging stations required by the user group for a preset time of a preset work day is calculated, wherein S i Refers to the ith user group, L (S) i T, τ) is S i The number of destination charging stations required during time t of the day, f (S) i τ) is S in the group of working days and times i Probability distribution of user groups, N sum To charge the total number of cars nationwide, μ ((P, t, P) | S i ) User group S in which a single user is charged during time t of day i Expected value of, phi period S i ) Is a user group S i Total number N of nationwide chargeable cars sum In which the number of the users is increased, wherein,g(D i ) Is a group S of users i Probability density function of the daily driving distance, tt, of an individual user τ Is a set of user groups charged during τ work dates;
step S13, by formulaCalculating the number of destination charging stations required by all users within a preset time of a preset working day, wherein TL (t, middle) is the number of destination charging stations required within t preset time of tau preset working day;
step S14, calculating the maximum number of required destination charging stations in t preset time of the τ preset working day through a formula DTL = max { ∑ TL (t, τ) }, wherein DTL is the maximum number of destination charging stations required nationwide, and taking DTL as the number of destination charging stations.
Step S15, according to the formulaCalculating the number of destination charging stations required for each city, wherein DTL i Number of destination charging stations, CD, required for the ith city i Is the vehicle density of the ith city.
After a double-layer complex network model is built and an evaluation index is determined according to the built double-layer complex network model, an evaluation index system of the electric automobile is built based on the SI infectious disease model, and the growth rate of the electric automobile is determined based on the evaluation index system of the electric automobile.
The embodiment of the invention further provides an electric vehicle growth rate determining device based on the SI infectious disease model, which is used for executing the electric vehicle growth rate determining method based on the SI infectious disease model provided by the above embodiment of the invention.
Fig. 11 is a structural diagram of an electric vehicle growth rate determination apparatus based on an SI infectious disease model according to an embodiment of the present invention, and as shown in fig. 11, the electric vehicle growth rate determination apparatus based on the SI infectious disease model mainly includes: a first calculation module 11, a first determination module 12, a creation module 13, a second determination module 14, wherein:
the first calculation module 11 is used for calculating the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city;
a first determination module 12 for determining a total satisfaction value of the user with the charging stations based on the driving arrival rate between cities, the proportion of long-distance drivers, the satisfaction degree of the user with the number of destination charging stations and the satisfaction degree of the user with the number of super charging stations in the city;
the establishing module 13 is used for establishing an SI infectious disease model based on the overall satisfaction value of the user on the electric automobile;
and the second determination module 14 is used for determining the growth rate of the electric automobile according to the SI infectious disease model.
Optionally, the first calculation module 11 includes:
the first calculation submodule is used for calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle;
and the second calculation submodule is used for calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric automobile.
Optionally, the first computation submodule is specifically configured to:
according to the formulaCalculating user satisfaction with the destination charging stations, wherein DNL is user satisfaction with the number of destination charging stations and DTL now The number of current destination charging stations, the DTL is the total number of destination charging stations when the fuel vehicles are replaced by electric vehicles and the gas stations are replaced by charging stations, and the PT is the permeability of the electric vehicles.
Optionally, the second computing submodule is specifically configured to:
according to the formulaCalculating the satisfaction degree of the user to the number of super charging stations in the city, wherein the SNL is the satisfaction degree of the user to the number of super charging stations in the city, and the STL is the satisfaction degree of the user to the number of super charging stations in the city c_now For the number of super charging stations in the current city, STL c When the fuel vehicles are completely replaced by the electric vehicles and the gas stations are completely replaced by the charging stations, the total number of the super charging stations is equal to the total number of the super charging stations, and PT is the permeability of the electric vehicles.
Optionally, the apparatus further comprises: a second calculation module forBy the formulaCalculating the electric vehicle permeability, wherein N sum Is the total number of electric vehicles; m sum Is the total number of fuel vehicles and electric vehicles.
Optionally, the first determining module 12 is specifically configured to:
calculating a total satisfaction value of a user for charging stations according to the formula D = w × RL + (1-w) × (a × SNL + DNL), wherein D is the total satisfaction value, w is a proportion of long distance drivers, a is a proportion of short distance drivers who forget to charge, RL is a driving arrival rate between cities, DNL is the satisfaction degree of the user for the number of destination charging stations, and SNL is the satisfaction degree of the user for the number of super charging stations in cities.
Optionally, the establishing module 13 is specifically configured to:
according to the formulaCalculating the number of people who effectively use the electric automobile every day, wherein lambda is the number of people who effectively use the electric automobile every day, and X is a preset threshold; d is the overall satisfaction value, and P is the number of people who use fuel automobiles but come into contact with electric automobile owners every day.
Optionally, the second determining module 14 is specifically configured to: to pairCalculating an integral to obtain the number of increases of the electric automobile every year, wherein i is the occupancy of the current electric automobile; λ is the number of people who effectively use electric cars daily; i all right angle 0 Is an initial value of the electric vehicle; calculating an annual electric vehicle growth rate based on the annual electric vehicle growth number.
The device provided by the embodiment of the present invention has the same implementation principle and the same technical effects as those of the foregoing method embodiments, and for the sake of brief description, reference may be made to corresponding contents in the foregoing method embodiments for the parts of the device embodiments that are not mentioned.
The method for determining the growth rate of the electric vehicle based on the SI infectious disease model provided by the embodiment of the invention has the same technical characteristics as the device for determining the growth rate of the electric vehicle based on the SI infectious disease model provided by the embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.
In the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
Finally, it should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention and the technical principles applied thereto. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in some detail by the above embodiments, the invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the invention, and the scope of the invention is determined by the scope of the appended claims.
Claims (8)
1. An electric vehicle growth rate determination method based on an SI infectious disease model is characterized by comprising the following steps:
calculating the satisfaction degree of the user on the number of destination charging stations and the satisfaction degree of the user on the number of super charging stations in the city;
determining a user's overall satisfaction value for charging stations based on inter-city driving arrival rates, a proportion of long distance drivers, the user's satisfaction with the number of destination charging stations, and the user's satisfaction with the number of super charging stations in the city;
establishing an SI infectious disease model based on the overall satisfaction value of the user for the charging station;
determining the growth rate of the electric automobile according to the SI infectious disease model;
the establishing of the SI infectious disease model based on the overall satisfaction value of the user for the charging station comprises the following steps:
according to the formulaThe number of people who effectively use the electric vehicle every day is calculated, wherein,λfor the number of people who effectively use electric vehicles daily,Xis a preset threshold;Dis the overall satisfaction value of the charging station,Pthe number of people who use fuel automobiles but come into contact with electric automobiles each day;
the determining the growth rate of the electric vehicle according to the SI infectious disease model comprises:
for is toAnd (4) integrating to obtain the annual increase number of the electric automobile, wherein,iis the occupancy of the current electric vehicle;λthe number of people who effectively use electric vehicles per day;i 0 is an initial value of the electric vehicle;tis time;
calculating a growth rate of the electric vehicle per year based on the growth number of the electric vehicle per year.
2. The method of claim 1, wherein calculating the user's satisfaction with the number of destination charging stations and the user's satisfaction with the number of super charging stations in the city comprises:
calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle;
and calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric vehicle.
3. The method of claim 2, wherein calculating user satisfaction with the number of destination charging stations based on the number of destination charging stations and electric vehicle penetration comprises:
according to the formulaCalculating a user satisfaction with the number of destination charging stations, wherein,DNLis the user's satisfaction with the number of destination charging stations,DTL now is the number of charging stations at the current destination,DTLwhen the fuel vehicle is replaced by the electric vehicle, the filling station is replaced by the charging station, the total number of destination charging stations,PTis the electric vehicle permeability.
4. The method of claim 2, wherein calculating user satisfaction with the number of in-city super charging stations based on the number of in-city super charging stations and the electric vehicle permeability comprises:
according to the formulaCalculating the satisfaction of the user with the number of super charging stations in the city, wherein,SNLis the user's satisfaction with the number of super charging stations in the city,STL c_now for the number of super charging stations in the current city,STL c the total number of super charging stations is equal to the total number of the electric vehicles which are used for replacing the fuel vehicles and the charging stations which are used for replacing the gas stations,PTis the electric vehicle permeability.
6. The method of claim 2, wherein determining a user's overall satisfaction value for charging stations based on driving arrival rates between cities, a proportion of long distance drivers, the user's satisfaction with the number of destination charging stations, and the user's satisfaction with the number of super charging stations within a city comprises:
according to the formulaAnd calculating the overall satisfaction value of the user on the charging station, wherein,Dis the value of the overall satisfaction that is,wis the proportion of long-distance drivers,ais the proportion of short-distance drivers who forget to charge,RLin order to achieve inter-city driving arrival rates,DNLis the user's satisfaction with the number of destination charging stations,SNLis the user's satisfaction with the number of super charging stations in the city.
7. An electric vehicle growth rate determination apparatus based on an SI infectious disease model, the apparatus comprising:
the first calculation module is used for calculating the satisfaction degree of the user on the number of the destination charging stations and the satisfaction degree of the user on the number of the super charging stations in the city;
a first determination module for determining a total satisfaction value of a user with charging stations based on driving arrival rates between cities, a proportion of long distance drivers, the satisfaction of the user with the number of destination charging stations, and the satisfaction of the user with the number of super charging stations within a city;
the establishment module is used for establishing an SI infectious disease model based on the overall satisfaction value of the user for the charging station; in particular for use according to formulaeThe number of people who effectively use the electric vehicle every day is calculated, wherein,λfor the number of people who effectively use electric vehicles daily,Xis a preset threshold value;Dis the overall satisfaction value of the charging station,Pfor using fuel-oil vehicles but with daily and electric operationThe number of persons the car is in contact with;
the second determination module is used for determining the growth rate of the electric automobile according to the SI infectious disease model; particularly for the pairAnd calculating an integral to obtain the increment of the electric automobile every year, wherein,iis the occupancy of the current electric vehicle;λthe number of people who effectively use electric vehicles daily;i 0 is an initial value of the electric vehicle; calculating a growth rate of the electric vehicle per year based on the number of growth of the electric vehicle per year;tis time.
8. The apparatus of claim 7, wherein the first computing module comprises:
the first calculation submodule is used for calculating the satisfaction degree of the user on the number of the destination charging stations based on the number of the destination charging stations and the permeability of the electric vehicle;
and the second calculation submodule is used for calculating the satisfaction degree of the user on the number of the super charging stations in the city based on the number of the super charging stations in the city and the permeability of the electric vehicle.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107020963A (en) * | 2015-12-10 | 2017-08-08 | 施耐德电器工业公司 | Method for managing power in the charging station of electric vehicle |
CN108388975A (en) * | 2018-01-15 | 2018-08-10 | 南京邮电大学 | A kind of Information Security Risk transmission control method and device based on Epidemic Model |
CN108390421A (en) * | 2018-01-19 | 2018-08-10 | 上海电力学院 | Meter and the double scale charging bootstrap techniques of the electric vehicle of user satisfaction and system |
CN108596363A (en) * | 2018-03-26 | 2018-09-28 | 四川大学 | A kind of city electric car quantity deduction emulation mode |
CN111523714A (en) * | 2020-04-15 | 2020-08-11 | 广东电网有限责任公司 | Site selection layout method and device for electric power charging station |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5104448B2 (en) * | 2008-03-21 | 2012-12-19 | 富士通株式会社 | Business improvement support device and business improvement support program |
US10116765B2 (en) * | 2015-07-14 | 2018-10-30 | Tuvi Orbach | Needs-matching navigator system |
-
2020
- 2020-11-26 CN CN202011348881.8A patent/CN112435061B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107020963A (en) * | 2015-12-10 | 2017-08-08 | 施耐德电器工业公司 | Method for managing power in the charging station of electric vehicle |
CN108388975A (en) * | 2018-01-15 | 2018-08-10 | 南京邮电大学 | A kind of Information Security Risk transmission control method and device based on Epidemic Model |
CN108390421A (en) * | 2018-01-19 | 2018-08-10 | 上海电力学院 | Meter and the double scale charging bootstrap techniques of the electric vehicle of user satisfaction and system |
CN108596363A (en) * | 2018-03-26 | 2018-09-28 | 四川大学 | A kind of city electric car quantity deduction emulation mode |
CN111523714A (en) * | 2020-04-15 | 2020-08-11 | 广东电网有限责任公司 | Site selection layout method and device for electric power charging station |
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