KR102235943B1 - Ev charging station system - Google Patents

Abstract

The present invention relates to an electric vehicle charging station system, and more particularly, to an electric vehicle charging station system that prevents an overload of an operation server that manages and controls a charger and predicts the power consumption of the charging station to provide a stable charging station operation.
In this invention, a plurality of chargers installed in a charging station, each provided with a charging cable, and transmitting charger data through a network, and set and registered in the network to receive the charger data, process the charger data, or the charger Connect a plurality of operation servers that transmit commands to, and the charger and the operation server, and distribute the server by port in response to the connection request signal of the charger to connect any one of the chargers to any one operation server. It includes a distributed processing module.

Description

Electric vehicle charging station system {EV CHARGING STATION SYSTEM}

The present invention relates to an electric vehicle charging station system, and more particularly, to an electric vehicle charging station system that prevents an overload of an operation server that manages and controls a charger and predicts the power consumption of the charging station to provide a stable charging station operation.

Electric vehicles (EV) were manufactured earlier than gasoline or diesel vehicles, but were not put into practical use due to problems such as the heavy weight of the battery and the time it takes to charge, but they do not use fossil energy due to the recent depletion of fossil energy and environmental pollution. As interest in electric vehicles that use electric energy increases, research on this is being actively conducted.

Such an electric vehicle requires a charging station infrastructure for charging the battery because it drives the vehicle by rotating a motor with electricity charged in the battery.According to this need, the charging data and charger information of the charger are stored for efficient use and user convenience of the electric vehicle. A charging infrastructure operating system that collects and provides has existed and operated.

Meanwhile, as the supply of electric vehicles continues to increase in order to suppress environmental pollution and the government's policy, the supply of chargers is continuously increasing, and the establishment of charging stations not only by public but also enterprises is increasing.

As a conventional technology for an electric vehicle charging station system, there is Registration Patent No. 10-2095260 (March 25, 2020) (hereinafter referred to as the prior art), and the prior art is charged in consideration of the amount of current used by the load during rapid charging of an electric vehicle. Disclosed is a charging control device and method for shortening the rapid charging time of an electric vehicle, which prevents an increase in the rapid charging time due to the use of a load by variably requesting a charging current from a rapid charger (EVSE) that supplies current.

However, in general, a charging station is provided with a plurality of chargers, each of which is controlled by an operation server, and the operation server generates a load associated with managing the plurality of chargers. This may occur not only in a situation in which a number of chargers are operated by one server, but also when a charger with more than a load is interlocked with one server in the process of operating a plurality of chargers by a plurality of servers.

Conventional technologies, including the prior art, have not been able to provide a way to relieve the overload of such an operation server, and furthermore, do not provide a way to operate a charging station more efficiently through calculation of power consumption and residual power. have.

The present invention was conceived to solve the above problem, and in the process of operating in conjunction with a plurality of chargers and a plurality of operation servers, it is recognized that an overload is applied to a specific operation server, so that the charger to be connected to the corresponding operation server is not spared. It aims to provide an electric vehicle charging station system that distributes the load by connecting it to an operation server.

In addition, it has not been able to provide a way to make charging stations more efficient by calculating the power consumption and residual power of each charger and charging station.

The present invention for the purpose of solving the above problems is a plurality of chargers installed in a charging station, each provided with a charging cable, and transmitting charger data through a network, and set and registered in the network to receive the charger data, and the charger A plurality of operation servers that process data or transmit commands to the charger, and the charger and the operation server are connected, and the server is distributed to each port in response to the connection request signal from the charger to connect to any one of the chargers. It includes a distributed processing module that connects any one operation server.

In addition, at least one of the plurality of operation servers includes a power amount calculation part that calculates power consumption and residual power amount of the charger, and the power amount calculation part includes a plurality of charging time data and a plurality of power amount data corresponding thereto from the charger. A data receiving unit receiving a data receiving unit, a data processing unit generating a plurality of regression models using the charging time data, calculating an estimated power amount by inputting the charging time data into the regression model, and comparing the calculated estimated power amount with the power amount data A model verification unit that calculates an error value of each regression model and a model determination unit that selects any one of a regression model based on the error value, and the power amount calculation part is charged to the regression model determined by the model determination unit. It is characterized in that it may be configured to input time data and finally calculate an expected amount of power.

In addition, the model verification unit replaces and selects the regression model only when the regression model generated and selected using the currently received charging time data and power amount data has an error value smaller than that of the past regression model. In the case of having an error value, it is characterized in that it can be configured to maintain the past regression model as it is.

The present invention having the above configuration and features distributes the server by port in response to the connection request signal of the charger, and through a distributed processing module that connects any one of the chargers to any one operation server, an overload is applied to a specific operation server. The load is distributed by connecting the charger to be connected to the corresponding operation server to another idle operation server.

In addition, by introducing a function that calculates the expected power amount using the charging time data and the power amount data, it has the effect that the charging station can be operated more efficiently by calculating the power consumption and residual power amount of each charger and charging station.

1 is a block diagram schematically showing the configuration of the distributed processing of the present invention.
Fig. 2 is an explanatory diagram showing the distributed processing operation of the present invention.
Fig. 3 is a block diagram schematically illustrating a configuration related to calculating an amount of power according to the present invention.
Figure 4 is an algorithm for calculating the amount of power of the present invention.
5 is a further embodiment of the present invention.

The present invention will be described in detail in the text of the bar, implementation (態樣, aspect) (or embodiment) that can apply various changes and can have various forms. However, this is not intended to limit the present invention to a specific form of disclosure, it should be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention.

The terms used in the present specification are only used to describe specific embodiments (sun, 態樣, aspect) (or embodiments), and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as ~comprise~ or ~consist~ are intended to designate the existence of features, numbers, steps, actions, components, parts, or a combination thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance the possibility of the presence or addition.

Unless otherwise defined, all terms used herein including technical or scientific terms have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in the present application. Does not.

The ~1~, ~2~ and the like described in the present specification are only referred to to distinguish different constituent elements, and are not limited to the order of manufacture, and their names in the detailed description and claims of the invention It may not match.

Hereinafter, an electric vehicle charging station system (hereinafter, the present system (C)) according to the present invention will be described in detail.

This system (C) relates to an electric vehicle charging station system that prevents overloading of the operation server 2 and provides a stable charging station operation by predicting the power consumption of the charging station. As shown in FIG. 1, a plurality of chargers 1, It includes a plurality of operation servers (2) and distributed processing module (4).

Specifically, the charger 1 is a component that performs electric charging of an electric vehicle, is installed in a charging station, has a charging cable, and is configured to transmit charger data through a network. The charger 1 is provided in plural, and the charger data transmitted from the charger 1 is transmitted to the operation server 2 to be utilized throughout the operation of the charging station.

For example, it is possible to monitor the current state of the charger 1, notify an occurrence of an abnormality in the charger 1, calculate the amount of power used for charging in each charger 1, or the like.

Next, the operation server 2 is configured to control and manage the charger 1, and is configured to receive charger data by setting and registering in the network, to process the charger data, or to transmit a command to the charger (1). It is preferable that the operation server 2 is also provided in plural, and the specific implementation of the operation server 2 may have various forms depending on the service or function of the charging station, and may follow conventional knowledge.

Next, the distributed processing module 4 is a configuration that serves as a relay connecting the charger 1 and the operation server 2, and the operation server 2 is connected to the operation server 2 in response to the connection request signal of the charger 1 It is configured to be distributed by port to connect any one of the chargers (1) to any one of the operating servers (2).

In FIG. 1, the charger 1 includes first to third chargers 11, 12, 13, and the operation server 2 includes the first to third operation servers 21, 22, and 23. Including, it can be seen that the distributed processing module 4 is provided between the charger 1 and the operation server 2 to be relayed. Here, each of the first to third chargers 11, 12, 13, and the first to third operation servers 21, 22, and 23 may be one terminal, or a plurality of terminals are grouped. It could be.

In general, a charging station is equipped with a plurality of chargers (1), each charger (1) is controlled by the operation server (2), and the operation server (2) generates a load associated with managing the plurality of chargers (1). It is bound to do. This occurs not only in the situation in which a number of chargers 1 are operated by one server, but also when a charger (1) above the load is interlocked with one server in the process of operating a plurality of chargers (1) by multiple servers. It can be.

In this system (C), when the distributed processing module 4 checks the load status of the operation server 2 and an excessive load is placed on one of the operation servers 2, the charger to be connected to the operation server 2 ( The load is distributed by connecting 1) to another idle operation server (2). That is, the distributed processing module 4 serves as a kind of connection switch, and preferably an L4 switch may be used.

Referring to FIG. 2 for example, in a basic state, the first charger 11 is interlocked with the first operation server 21, and the second charger 12 is interlocked with the second operation server 22. Here, in the case where the first and second chargers 11 and 12 are not a single charger but a group of chargers, excessive processing work may be applied to the second operation server 22 and an overload state may occur. At this time, when the second charger 12 (any one or some of a plurality of chargers) requests a connection to the second operation server 22, the distributed processing module 4 makes the second charger 12 relatively free. It is interlocked with the first operation server 21 so that it can be processed. When the overload of the second operation server 22 is resolved, the data processed by the first operation server 21 is transmitted to and stored in the second operation server 22, and then stored in the first operation server 21. The transmitted charger data of the second charger 12 may be configured to be automatically deleted.

For this purpose, a separate communication means for exchanging the state of the operation server 2 is preferably provided between the distributed processing module 4 and each operation server 2, and the data on the state of the operation server 2 is It is desirable to be configured to be periodically transmitted at every preset time to perform real-time monitoring.

The switching function of the distributed processing module 4 may be performed in a queue matching method like a call center system, and the determination of the load level may be performed in a form of comparing the sizes of threads.

Next, the system C is characterized in that at least one of the plurality of operation servers 2 may include a power amount calculation part 30 that calculates the power consumption amount and the residual power amount of the charger 1. This power amount calculation part 30 contributes to efficient charging station operation by calculating the amount of power consumption and the amount of remaining power of the charger 1.

The power calculation part 30 may be provided in any one of each operation server 2, may be provided in part, or may be provided in all, which is selected by the implementer according to the amount of processing data for calculating the amount of power. This can be done, and if necessary, only a server for calculating the amount of power can be separately constructed.

Specifically, as shown in FIG. 3, the power amount calculation part 30 includes a data receiving unit 31 that receives data, a data processing unit 32 that processes data to generate a regression model, and calculates an error value of the regression model. And a model verification unit 33 and a model determination unit 34 for selecting an optimal regression model.

For each configuration, the data receiving unit 31 is configured to receive a plurality of charging time data and a plurality of wattage data corresponding thereto from the charger 1, and can be realized through a communication module, and the charging time data and wattage data are It may be received directly from the charger 1, or it may receive what has been stored in itself or another server.

Next, the data processing unit 32 is configured to process the data to generate a regression model. As the charging time data is configured in a plurality, the regression model may also be configured in a plurality. Regression model is one of the data mining analysis techniques that systematically and automatically finds statistical rules or patterns in large-scale stored data. Specifically, the relationship between charging time data and power amount data is nonlinearly analyzed through a regression curve. It can be defined, and accordingly, it is possible to obtain a more accurate estimate value compared to the case where the relationship is linearly defined.

For this, the regression model can utilize an n-order polynomial curve as a regression curve. However, the regression model is not necessarily limited thereto, and may be composed of a curve of a method other than a polynomial curve.

Again, the data processing unit 32 may be configured to generate a regression model using data having a value less than or equal to a preset time among the plurality of charging time data. In a preferred embodiment, the preset time is the maximum charging of the electric vehicle. It is decided on the basis of approaching time but not exceeding it. The maximum charging time may mean a time taken from the discharged state of the battery to the fully charged state.

For example, if the charging time data is 15 minutes, 30 minutes, 45 minutes, 60 minutes, and 90 minutes, the preset time can be composed of 60 minutes, and at this time, 90 minutes exceeding 60 minutes create a regression model. It is excluded from the element.

Through this, charging time data representing non-ideal values can be filtered to reduce errors in the regression model.

Next, the model verification unit 33 is configured to calculate an estimated power amount by inputting charging time data into the regression model, and to calculate an error value of each regression model by comparing the calculated estimated power amount with the power amount data. Each regression model calculates an error value by inputting charging time data to calculate the expected amount of power and comparing it with the actual power amount data. In this case, the error value is preferably calculated through the average of each error value obtained by applying a plurality of charging time data to a corresponding regression model.

For example, if charging time data having a value of 60 minutes is input to the regression model to calculate the expected power amount, and when the power amount data corresponding thereto is 200 kW, the error value may be 20 kW.

Next, the model determination unit 34 is configured to select any one of the regression models based on the error value, and may be configured to select a regression model having the smallest error value among the plurality of regression models as the final regression model. . Alternatively, after setting the upper and lower limits of the error values, the regression model having the smallest error value among the regression models having the error values within the upper and lower limit ranges may be selected as the final regression model.

The power amount calculation part 30 is configured to input charging time data received in the regression model determined in the model determination unit 34 to finally calculate the estimated power amount.

In addition, the model verification unit 33 replaces and selects the regression model only when the regression model generated and selected using the currently received charging time data and power amount data has an error value smaller than that of the past regression model. If it has an error value larger than that of the regression model of, it can be configured to maintain the past regression model as it is.

This is to enhance the reliability of the regression model by continuously learning the regression model using artificial intelligence's deep learning method.If the newly created regression model has a larger error value than the previous regression model, there is no need to replace it with a new regression model. It is to keep the regression model of.

Hereinafter, the operation process of the power amount calculation part 30 will be described with reference to FIG. 4. First, the data receiving unit 31 collects charging time data and power amount data, and the data processing unit 32 receives the charging time data. Create a regression model.

Thereafter, the model verification unit 33 receives the collected charging time data and the generated regression model, inputs the charging time data into the regression model, calculates an expected amount of power, and compares this with the collected power amount data to calculate an error value. .

Then, the model determination unit 34 selects the optimal regression model based on the error value, and compares the error value between the selected regression model and the past regression model, and if the current regression model is better (the error value is Small case), the regression model is replaced.

The power amount calculation part 30 finally calculates the estimated amount of power by inputting the charging time data that is continuously collected in the selected regression model. In particular, it is preferable that the calculation of the final expected power amount and the selection of the regression model are performed independently in a separate process, and both are preferably continuously processed in real time.

Meanwhile, the system C is characterized in that it may further include a payment module that processes payment through a payment interface that processes a payment request for charging of each charger 1. Such a payment module may be provided in the charger 1 or may be provided in a user terminal or a charging station terminal interlocked with the charger 1. Also, it may be provided as a mechanical device, or may be provided in the form of a client program such as an application.

In the case of a public certificate as a payment authentication method that has been used in the past, it is very difficult to memorize the password, such as having to enter the public certificate password through the keyboard on the touch screen (D), and recently mixing special characters in the password. In the case of users who are not familiar with smart devices, they are having a lot of trouble with payment authentication.

As a representative of biometric authentication, which has emerged as an alternative to this, there is a possibility that there is a possibility of a security problem in which payments are made by unintended manipulation such as fingerprint recognition. Accordingly, the present invention provides a payment interface capable of simultaneously solving user convenience and security by allowing anyone to quickly and easily process a user's payment request by simply dragging the authentication path output on the touch screen (D). I want to provide.

First, the payment interface displays an authentication path (P1) consisting of any one of a specific character, a specific number, and a portion of a fingerprint shape determined according to a payment authentication method and a coin-shaped icon (I) on a payment screen that processes a user's payment. Will be printed.

In addition, the authentication means here may correspond to a public certificate, a resident registration number, a fingerprint, etc. For example, when a public certificate is set as an authentication method, a character included in the password or a character composed of one of the user's name is used in the authentication method. It can be determined by a specific character determined according to the same principle, and when the fingerprint is set as the authentication means, a part of the shape included in the fingerprint is configured as the authentication path P1.

In other words, the user who has received the authentication request from the server is an authentication path (P1) composed of any one of a specific letter, number, or part of the fingerprint shape determined according to a preset authentication means (authorized certificate, social security number, fingerprint, etc.) and coin-shaped. The icon (I) is displayed on the screen.

In addition, when the icon (I) is dragged along the authentication path (P1), payment authentication is completed. The characteristic point here is that if payment authentication is completed simply when a drag is made, a smartphone, etc., are placed in the pants pocket. In the left state, there is a risk that the drag is completed due to unwanted contact and payment authentication is completed.

Therefore, in the case of the payment interface according to the present invention, an authentication point (P2) having the same shape as the icon (I) is created at any one point of the authentication path (P1) excluding the start point (P11) and the end point (P12). (誤) It is possible to prevent authentication by contact first.

Looking in more detail, as shown in FIG. 5, if the finger is put on the authentication point (P2) while the drag operation is stopped, the effect of gradually filling the inside of the authentication point (P2) is output, and the authentication It is configured so that the drag operation can be resumed only after the points P2 are all filled.

In addition, such an authentication point (P2) can be created in a preset location by the user. For example, if the authentication point (P2) is set at 1 o'clock in the fingerprint-shaped authentication path (P1) as shown in FIG. 5 Authentication is completed only when the authentication point (P2) is properly filled in that part. In addition, when the authentication point P2 is filled in a location different from the location previously set by the user, the path is removed and payment authentication cannot be performed.

In addition, although only one authentication point P2 is shown in FIG. 5, a plurality of authentication points P2 may be set to further strengthen security.

And when the icon (I) displayed on the payment screen is clicked once more, an enlarged screen of the icon (I) is displayed. As described above, even a user suffering from presbyopia completes the authentication path (P1) very easily. By doing so, you can complete the payment verification.

In addition, in the case of the existing password input method, it is not easy to memorize, such as the need to unconditionally include special characters in the password, and there are frequent problems that become more vulnerable to security, such as entering into a notepad of a smart device for memorization. I did.

And even though this method of filling the authentication point (P2) is provided, there is also a risk that the authentication point (P2) is completely filled due to incorrect contact. As a countermeasure for this, the authentication point (P2) is filled in the process. If the inside of the point P2 is not filled or is overfilled, the authentication path P1 is configured to disappear, so that authentication due to incorrect contact can be secondarily prevented.

The present invention described above with reference to the accompanying drawings can be variously modified and changed by a person skilled in the art, and such modifications and changes that are not limited through the claims should be construed as being included in the scope of the present invention.

C: This system (electric vehicle charging station system)
1: charger
2: Operation server
30: power calculation part
31: data receiving unit 32: data processing unit
33: model verification unit 34: model determination unit
4: Distributed processing module

Claims (4)

A plurality of chargers installed in the charging station, each having a charging cable, and transmitting charger data through a network;
A plurality of operation servers configured and registered in the network to receive the charger data, process the charger data, or transmit a command to the charger; And
A distributed processing module that connects the charger to the operation server, and distributes the server to each port in response to a connection request signal from the charger to connect any one of the chargers to any one operation server;
Including,
Further comprising a payment module that processes payment through a payment interface that processes a payment request for charging of each of the chargers,
The payment interface outputs a coin-shaped icon and an authentication path composed of any one of a specific character, a specific number, and a part of a fingerprint shape determined according to a payment authentication means on a payment screen that processes a user's payment, and the icon Payment verification is completed only when dragged along the verification path,
An authentication point having the same shape as the icon is created at any one point of the authentication path excluding a start point and an end point,
When the drag operation is stopped at the authentication point, an effect of gradually filling the inside of the authentication point is output, and the drag operation is resumed only after the authentication point is filled.
The method according to claim 1,
At least one of the plurality of operation servers includes a power amount calculation part for calculating a power consumption amount and a residual power amount of the charger,
The power calculation part includes a data receiving unit receiving a plurality of charging time data and a plurality of wattage data corresponding thereto from the charger, a data processing unit generating a plurality of regression models using the charging time data, and the regression model. A model verification unit that calculates an estimated power amount by inputting charging time data and compares the calculated estimated power amount with the power amount data to calculate an error value of each regression model, and a model that selects any one of a regression model based on the error value Including the decision part,
The electric vehicle charging station system, characterized in that the electric vehicle charging station system finally calculates the estimated electric energy by inputting the charging time data received in the regression model determined in the model determination unit.
The method according to claim 2,
The model verification unit replaces and selects the regression model only when the regression model generated and selected using the currently received charging time data and power amount data has a smaller error value than the past regression model, and has a larger error than the past regression model. If it has a value, the electric vehicle charging station system, characterized in that configured to maintain the past regression model as it is.
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