C-V2X-based intelligent charging system and method thereof

Abstract

The invention discloses a C-V2X-based intelligent charging system and method, and belongs to the technical field of intelligent charging, and the system specifically comprises a cloud platform which is used for calculating income information according to the real-time electricity price and the power grid load information when a target vehicle enters a cellular network area, transmitting the income information to a vehicle-mounted unit, and transmitting the income information to the vehicle-mounted unit when the vehicle sends a charging demand; the corresponding charging terminal is locked, and connection with the vehicle-mounted unit is established through the road side unit; the vehicle-mounted unit is used for displaying the charging suggestion, the charging time and the predicted income to a vehicle owner according to the current electric quantity, the charging demand and the income condition of the vehicle, and sending a charging request to the cloud platform after receiving a charging voice instruction of the vehicle owner; the road side unit is used for planning an optimal path according to the vehicle position information and guiding the vehicle to automatically drive to the charging terminal; the charging terminal is used for carrying out two-way charging and discharging interaction between the electric vehicle and a power grid; according to the invention, intelligent interconnection between the vehicle and the charging facility is realized through the C-V2X communication technology.

Description

Technical Field

[0001] The present application relates to the field of vehicle-grid interaction technology, and specifically to a C-V2X-based smart charging system and method thereof. Background Art

[0002] As the world pays more and more attention to environmental protection, the market demand for new energy vehicles is growing. However, traditional charging methods have problems such as low efficiency and waste of resources. In order to solve these problems, smart charging systems have emerged. As one of the key technologies of intelligent connected vehicles, C-V2X technology can realize real-time communication between vehicles and vehicles, and vehicles and infrastructure, providing a new solution for smart charging. At the same time, V2G technology enables electric vehicles to participate in grid dispatch as distributed energy storage units, further improving energy utilization efficiency.

[0003] The existing intelligent charging system mainly integrates the on-board unit (OBU), roadside unit (RSU), charging terminal and cloud platform to achieve intelligent interconnection and efficient charging between vehicles and charging facilities. Among them, the charging terminal is a distributed energy storage system with V2G function, which can realize two-way interaction between electric vehicles and power grid.

[0004] Although the existing intelligent charging system has solved the problems of traditional charging methods to a certain extent, there are still some problems. First, the existing intelligent charging system has delays in information transmission, which may lead to reduced charging efficiency. Secondly, the existing intelligent charging system lacks intelligence in charging scheduling and cannot be dynamically adjusted according to actual needs. Finally, the existing intelligent charging system is relatively simple in user interaction and cannot provide personalized charging services, which affects the user experience. Summary of the invention

[0005] The purpose of this application is to provide a C-V2X-based smart charging system and method to solve the following technical problems: The existing intelligent charging system lacks intelligence in charging scheduling and cannot be dynamically adjusted according to actual needs. Finally, the existing intelligent charging system is relatively simple in user interaction and cannot provide personalized charging services.

[0006] The purpose of this application can be achieved through the following technical solutions: A C-V2X-based smart charging system includes an on-board unit, a roadside unit, a charging terminal, an energy storage system and a cloud platform, wherein: The cloud platform is used to calculate and publish the V2G-based revenue information of the charging terminal according to the real-time electricity price and grid load information when the target vehicle enters the cellular network area, and send the revenue information to the on-board unit through LTE-V2X technology. When the vehicle issues a charging demand, it locks the corresponding charging terminal and establishes a connection with the on-board unit through the roadside unit; The vehicle-mounted unit is used to receive the revenue information, and display charging suggestions, charging time and estimated revenue to the vehicle owner according to the current power level of the vehicle, charging demand and V2G revenue situation, and send a charging request to the cloud platform through the vehicle-mounted unit after receiving the charging voice command from the vehicle owner; Roadside unit, which is used to plan the optimal route based on the vehicle's location information and guide the vehicle to automatically drive to the charging terminal; Charging terminals, used for bidirectional charging and discharging interaction between electric vehicles and the power grid, including distributed energy storage systems with V2G functions; The energy storage system is used to store excess electricity in the power grid into energy storage batteries. When the vehicle is charging, the electricity in the energy storage battery is used to charge the vehicle first.

[0007] As a further solution of the present application: the cloud platform is also used to collect and analyze data from the on-board unit, roadside unit and charging terminal, register and manage vehicle owner accounts, record user charging history and preference settings, and transmit data based on a private protocol.

[0008] As a further solution of the present application: the cloud platform collects information such as the vehicle's location, speed, battery level, etc. through the roadside unit and the on-board unit; collects information such as the current load condition and available power of the charging station, and calculates the time required for the vehicle to reach the nearest charging station; predicts the estimated remaining power of the vehicle when it arrives at the charging station, and selects the best charging station and charging time based on the prediction results and the load condition of the charging station; sends a scheduling instruction to the selected charging station, instructing it to reserve charging resources for a specific vehicle.

[0009] As a further solution of the present application: the specific process of the vehicle-mounted unit recognizing the charging voice instruction of the vehicle owner is as follows: The charging voice instruction is recognized as a question text, the question text data is mapped into a text vector, and the text vector is encoded and sorted through position embedding. The power feature and the geographical feature are output through a text extraction model. When the power feature and the geographical feature exist at the same time, the sentence containing the geographical feature is contextually analyzed to identify the owner's origin and destination, and the corresponding common routes are selected according to the origin and destination. The estimated power consumption of the journey is calculated according to the common routes. When the power consumption of the journey is greater than the current vehicle power, the location of the charging terminal is recommended to the owner, and the optimal route to the charging terminal is planned.

[0010] As a further solution of the present application: the process of the on-board unit identifying the power characteristics and geographical characteristics is as follows: The question text is segmented and split into several words. The words are input into the BERT layer of the text extraction model, each word is mapped to a corresponding word vector, and then the word vector is sent to the BiLSTM layer. The context feature information between the word vectors is captured and learned through deep learning. After the BiLSTM layer, the model outputs the label probability corresponding to each text information and generates an entity sequence. The entity sequence is input into the CRF layer for sorting, or the entity sequence that makes the objective function reach the optimal value is screened based on the preset dictionary to extract the power characteristics and geographic characteristics.

[0011] As a further solution of the present application: when the electric vehicle battery is sufficiently charged and the grid electricity price is higher than a set value, the charging terminal prompts the owner to transfer the vehicle's excess electricity back to the grid; and when the grid power is sufficient and the grid electricity price is low, the charging terminal prompts the electric vehicle to obtain electricity from the grid to charge the battery.

[0012] The present application also includes a C-V2X-based smart charging method, which is applied to the above-mentioned C-V2X-based smart charging system, and includes the following steps: When the target vehicle enters the cellular network area, the cloud platform calculates and publishes the V2G-based revenue information of the charging terminal based on the real-time electricity price and grid load information, and sends the revenue information to the vehicle-mounted unit through LTE-V2X technology; After receiving the revenue information, the on-board unit will show the owner the charging suggestions, charging time and estimated revenue according to the vehicle's current power, charging demand and V2G revenue. When receiving the owner's voice command for charging, the on-board unit will send a charging request to the cloud platform; After receiving the request, the cloud platform locks the corresponding charging terminal and establishes a connection with the vehicle-mounted unit through the roadside unit. The roadside unit plans the optimal path based on the vehicle's location information and guides the vehicle to automatically drive to the charging terminal. After the vehicle arrives at the charging terminal, it automatically completes docking and starts charging. According to the needs of the power grid, when the power grid is insufficient, the vehicle will participate in the power grid dispatch as a distributed energy storage unit to realize the V2G function. When the power grid is redundant, the excess power of the power grid will be stored in the energy storage battery.

[0013] Beneficial effects of this application: This application realizes the intelligent interconnection between vehicles and charging facilities through C-V2X communication technology, and can obtain the status and electricity price information of charging terminals in real time, so as to optimize the charging strategy, reduce waiting time and improve charging efficiency; the charging terminal of this application has V2G function, which can charge when the electricity price is low and discharge when the electricity price is high, so as to realize peak shaving and valley filling and improve the stability and economy of the power grid; this application provides personalized charging suggestions and profit information, allowing users to independently choose the charging time and method to improve the charging experience; and can perform intelligent navigation according to the voice commands of the car owner; this application promotes the deep integration of intelligent connected vehicles and smart grids, and provides strong support for the sustainable development of the new energy vehicle industry; this will greatly promote the development of the new energy vehicle market and has important social and economic significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present application is further described below in conjunction with the accompanying drawings.

[0015] Figure 1 This is a flow chart of the smart charging method based on C-V2X in this application. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0017] See also Figure 1 As shown, the present application is a C-V2X-based smart charging system, including a vehicle-mounted unit, a roadside unit, a charging terminal, an energy storage system and a cloud platform, wherein: Step 1: Build a smart charging system based on C-V2X. The system includes an onboard unit (OBU), a roadside unit (RSU), a charging terminal, and a cloud platform. The charging terminal is a distributed energy storage system with V2G function, such as Tesla's Model S electric car.

[0018] Step 2: Use C-V2X communication technology to publish and receive information. When the target vehicle enters the cellular network area, the cloud platform calculates and publishes the V2G-based revenue information of the charging terminal based on real-time electricity prices, grid load and other information. This information is sent to the OBU via LTE-V2X technology. For example, if the real-time electricity price is 0.8 yuan / kWh and the grid load is 70%, then the V2G revenue information of the charging terminal is 0.56 yuan per hour.

[0019] Step 3: Intelligent scheduling through decision-making and request. After receiving the information, the OBU combines the vehicle's current power, charging demand and V2G revenue to show the owner charging suggestions, including charging time, estimated revenue, etc. For example, if the vehicle's current power is 20% and the charging demand is full charge, then the charging time is 2 hours and the estimated revenue is 1.12 yuan. After the owner decides to charge, he sends a charging request to the cloud platform through the OBU.

[0020] Step 4: Achieve precise positioning and driving through request processing and navigation. After receiving the request, the cloud platform locks the corresponding charging terminal and establishes a connection with the OBU through the RSU. The RSU plans the optimal path based on the vehicle's location information and guides the vehicle to drive automatically to the charging terminal. For example, if the vehicle is currently at point A and the target charging terminal is at point B, the RSU will plan the shortest path so that the vehicle can reach point B as quickly as possible.

[0021] Step 5: Use V2G bidirectional charging and discharging technology to realize charging and V2G interaction. After the vehicle arrives at the charging terminal, it automatically completes docking and starts charging. At the same time, according to the needs of the power grid, the vehicle can participate in the grid dispatch as a distributed energy storage unit to realize the V2G function. For example, if the grid demand is to increase the power supply, then the vehicle can discharge when the electricity price is peak to help the grid meet the demand.

[0022] Step 6: Use intelligent scheduling and optimization technology to achieve intelligent prediction and scheduling of charging demand. The cloud platform combines big data and AI algorithms to intelligently predict and schedule charging demand, optimize the layout of charging stations and equipment utilization. For example, if it is predicted that tomorrow's charging demand will increase, the cloud platform can dispatch more charging terminals in advance to meet tomorrow's charging demand.

[0023] In another preferred embodiment of the present application, the cloud platform is also used to collect and analyze data from the on-board unit, roadside unit and charging terminal, register and manage vehicle owner accounts, record user charging history and preference settings, and transmit data based on a private protocol.

[0024] In another preferred embodiment of the present application, the cloud platform collects information such as the vehicle's location, speed, battery level, etc. through the roadside unit and the on-board unit; collects information such as the current load condition and available power of the charging station, and calculates the time required for the vehicle to reach the nearest charging station; predicts the estimated remaining power of the vehicle when it arrives at the charging station, and selects the best charging station and charging time based on the prediction results and the load condition of the charging station; and sends a scheduling instruction to the selected charging station, instructing it to reserve charging resources for a specific vehicle.

[0025] In another preferred embodiment of the present application, the specific process of the onboard unit recognizing the charging voice instruction of the vehicle owner is as follows: The charging voice instruction is recognized as a question text, the question text data is mapped into a text vector, and the text vector is encoded and sorted through position embedding. The power feature and the geographical feature are output through a text extraction model. When the power feature and the geographical feature exist at the same time, the sentence containing the geographical feature is contextually analyzed to identify the owner's origin and destination, and the corresponding common routes are selected according to the origin and destination. The estimated power consumption of the journey is calculated according to the common routes. When the power consumption of the journey is greater than the current vehicle power, the location of the charging terminal is recommended to the owner, and the optimal route to the charging terminal is planned.

[0026] In another preferred embodiment of the present application, the process of the on-board unit identifying the power characteristics and geographical characteristics is: The question text is segmented and split into several words. The words are input into the BERT layer of the text extraction model, each word is mapped to a corresponding word vector, and then the word vector is sent to the BiLSTM layer. The context feature information between the word vectors is captured and learned through deep learning. After the BiLSTM layer, the model outputs the label probability corresponding to each text information and generates an entity sequence. The entity sequence is input into the CRF layer for sorting, or the entity sequence that makes the objective function reach the optimal value is screened based on the preset dictionary to extract the power characteristics and geographic characteristics.

[0027] In another preferred embodiment of the present application, when the electric vehicle battery is sufficiently charged and the grid electricity price is higher than a set value, the charging terminal prompts the owner to transfer excess electric energy of the vehicle back to the grid; and when the grid power is sufficient and the grid electricity price is low, the charging terminal prompts the electric vehicle to obtain electric energy from the grid to charge the battery.

[0028] The present application also includes a C-V2X-based smart charging method, which is applied to the above-mentioned C-V2X-based smart charging system, and includes the following steps: When the target vehicle enters the cellular network area, the cloud platform calculates and publishes the V2G-based revenue information of the charging terminal based on the real-time electricity price and grid load information, and sends the revenue information to the vehicle-mounted unit through LTE-V2X technology; After receiving the revenue information, the on-board unit will show the owner the charging suggestions, charging time and estimated revenue according to the vehicle's current power, charging demand and V2G revenue. When receiving the owner's voice command for charging, the on-board unit will send a charging request to the cloud platform; After receiving the request, the cloud platform locks the corresponding charging terminal and establishes a connection with the vehicle-mounted unit through the roadside unit. The roadside unit plans the optimal path based on the vehicle's location information and guides the vehicle to automatically drive to the charging terminal. After the vehicle arrives at the charging terminal, it automatically completes docking and starts charging. According to the needs of the power grid, when the power grid is insufficient, the vehicle will participate in the power grid dispatch as a distributed energy storage unit to realize the V2G function. When the power grid is redundant, the excess power of the power grid will be stored in the energy storage battery.

[0029] Due to the advanced nature of this technical solution, it can be widely used in application fields such as intelligent connected vehicles, electric vehicle charging, and intelligent transportation systems. First, this application realizes the intelligent interconnection between vehicles and charging facilities through C-V2X communication technology, greatly improves the charging efficiency, and meets the needs of intelligent connected vehicles for efficient and convenient charging. Secondly, this application enables electric vehicles to participate in grid dispatching as distributed energy storage units through V2G technology, which helps to balance the supply and demand of the grid, improve the stability and economy of the grid, and meet the needs of new energy power systems for flexible adjustment. Finally, this application improves the equipment utilization rate of charging stations through intelligent scheduling and optimization, and meets the needs of charging facility operators to improve equipment utilization. At the same time, this application improves the user experience by providing personalized charging services, and meets the needs of electric vehicle users for high-quality charging services. Therefore, this application has broad market demand and good application prospects.

[0030] The above is a detailed description of an embodiment of the present application, but the content is only a preferred embodiment of the present application and cannot be considered to limit the scope of implementation of the present application. All equivalent changes and improvements made within the scope of the present application should still fall within the scope of the patent coverage of the present application.

Claims

1. A C-V2X-based smart charging system, characterized in that: It includes on-board unit, roadside unit, charging terminal, energy storage system and cloud platform, including: The cloud platform is used to calculate and publish the V2G-based revenue information of the charging terminal according to the real-time electricity price and grid load information when the target vehicle enters the cellular network area, and send the revenue information to the on-board unit through LTE-V2X technology. When the vehicle issues a charging demand, it locks the corresponding charging terminal and establishes a connection with the on-board unit through the roadside unit; The vehicle-mounted unit is used to receive the revenue information, and display charging suggestions, charging time and estimated revenue to the vehicle owner according to the current power level of the vehicle, charging demand and V2G revenue situation, and send a charging request to the cloud platform through the vehicle-mounted unit after receiving the charging voice command from the vehicle owner; Roadside unit, which is used to plan the optimal route based on the vehicle's location information and guide the vehicle to automatically drive to the charging terminal; Charging terminals, used for bidirectional charging and discharging interaction between electric vehicles and the power grid, including distributed energy storage systems with V2G functions; The energy storage system is used to store excess electricity in the power grid into energy storage batteries. When the vehicle is charging, the electricity in the energy storage battery is used to charge the vehicle first.

2. The C-V2X-based smart charging system according to claim 1, characterized in that: The cloud platform is also used to collect and analyze data from the on-board unit, roadside unit and charging terminal, register and manage vehicle owner accounts, record users' charging history and preference settings, and transmit data based on private protocols.

3. The C-V2X-based smart charging system according to claim 1, characterized in that: The cloud platform collects information such as the vehicle's location, speed, and battery level through the roadside unit and the on-board unit; collects information such as the current load and available power of the charging station, and calculates the time required for the vehicle to reach the nearest charging station; predicts the estimated remaining power of the vehicle when it arrives at the charging station, and selects the best charging station and charging time based on the prediction results and the load conditions of the charging station; and sends a scheduling instruction to the selected charging station, instructing it to reserve charging resources for a specific vehicle.

4. The C-V2X-based smart charging system according to claim 1, characterized in that: The specific process of the on-board unit recognizing the owner's charging voice command is as follows: The charging voice instruction is recognized as a question text, the question text data is mapped into a text vector, and the text vector is encoded and sorted through position embedding. The power feature and the geographical feature are output through a text extraction model. When the power feature and the geographical feature exist at the same time, the sentence containing the geographical feature is contextually analyzed to identify the owner's origin and destination, and the corresponding common routes are selected according to the origin and destination. The estimated power consumption of the journey is calculated according to the common routes. When the power consumption of the journey is greater than the current vehicle power, the location of the charging terminal is recommended to the owner, and the optimal route to the charging terminal is planned.

5. The C-V2X-based smart charging system according to claim 1, characterized in that: The process of the on-board unit identifying the power characteristics and geographical characteristics is as follows: The question text is segmented and split into several words. The words are input into the BERT layer of the text extraction model, each word is mapped to a corresponding word vector, and then the word vector is sent to the BiLSTM layer. The context feature information between the word vectors is captured and learned through deep learning. After the BiLSTM layer, the model outputs the label probability corresponding to each text information and generates an entity sequence. The entity sequence is input into the CRF layer for sorting, or the entity sequence that makes the objective function reach the optimal value is screened based on the preset dictionary to extract the power characteristics and geographic characteristics.

6. The C-V2X-based smart charging system according to claim 1, characterized in that: When the electric vehicle battery is fully charged and the grid electricity price is higher than a set value, the charging terminal prompts the owner to transfer excess electric energy of the vehicle back to the grid. When the grid power is sufficient and the grid electricity price is low, the charging terminal prompts the electric vehicle to obtain electric energy from the grid to charge the battery.

7. A C-V2X-based smart charging method, applied to a C-V2X-based smart charging system according to any one of claims 1 to 6, characterized in that: The following steps are involved: When the target vehicle enters the cellular network area, the cloud platform calculates and publishes the V2G-based revenue information of the charging terminal based on the real-time electricity price and grid load information, and sends the revenue information to the vehicle-mounted unit through LTE-V2X technology; After receiving the revenue information, the on-board unit will show the owner the charging suggestions, charging time and estimated revenue according to the vehicle's current power, charging demand and V2G revenue. When receiving the owner's voice command for charging, the on-board unit will send a charging request to the cloud platform; After receiving the request, the cloud platform locks the corresponding charging terminal and establishes a connection with the vehicle-mounted unit through the roadside unit. The roadside unit plans the optimal path based on the vehicle's location information and guides the vehicle to automatically drive to the charging terminal. After the vehicle arrives at the charging terminal, it automatically completes docking and starts charging. According to the needs of the power grid, when the power grid is insufficient, the vehicle will participate in the power grid dispatch as a distributed energy storage unit to realize the V2G function. When the power grid is redundant, the excess power of the power grid will be stored in the energy storage battery.

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