Electric vehicle charging network integrated platform based on mutual assistance mode

Abstract

The invention provides an electric vehicle charging network integrated platform based on a mutual assistance mode, and belongs to the technical field of electric vehicle charging networks. The device comprises a bidirectional DC / DC module, a bidirectional DC / DC charging control module, a bidirectional DC / DC discharging control module, a bidirectional AC / DC module, a bidirectional AC / DC charging control module, a bidirectional AC / DC discharging control module and a filter. The invention discloses a current metering device which comprises a peripheral control circuit based on an F288M35 dual-core chip. The peripheral control circuit comprises a main control device, a data acquisition module (comprising an AC sampling module and a DC sampling module), an IGBT driving module, a CAN bus communication module, a man-machine interface interaction module, a DC voltage sampling module, a DC current sampling module, an AC voltage sampling module, an AC current sampling module and a power supply module. And the vehicle networking system is used for reading parameters of the electric vehicle and comprises an OBD (On-Board Diagnostic) terminal, a background system and a mobile phone application program.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric vehicle charging networks, and in particular relates to an electric vehicle charging network integration platform based on a mutual assistance mode. Background Art

[0002] With the rapid development of the new energy electric vehicle industry, the number of electric vehicle charging piles in cities has increased dramatically, which has put higher requirements on the operational efficiency and profitability of the charging network.

[0003] The main problems currently facing electric vehicle charging technology include but are not limited to: First, the problem of long charging time. Due to the current charging technology and hardware costs, the market generally adopts the more popular fast charging technology, which takes 1.5 hours to fully charge a whole battery, greatly wasting the owner's time and efficiency, and will also cause congestion at charging stations, further affecting people's enthusiasm for buying electric vehicles; second, the growth rate of electric vehicles is much faster than the construction speed of charging piles, which makes it difficult to search for charging piles and charge after searching; third, the current power grid system has load balancing problems, and the disorderly charging of electric vehicles will lead to "peak on peak" situations, reducing the operating efficiency of the power grid; fourth, the planning and maintenance of charging piles. At present, the construction of charging piles is generally planned based on the historical data of electric vehicle ownership and regional distribution. If the data changes or the regional distribution changes, the layout needs to be re-arranged, which greatly wastes resources. In addition, charging piles as outdoor hardware facilities require regular maintenance, but this is rarely mentioned, which seriously affects the promotion and popularity of electric vehicles. Summary of the invention

[0004] The purpose of the present invention is to provide an integrated platform for electric vehicle charging network based on a mutual assistance mode, aiming to solve the problems in the prior art that seriously affect the promotion and popularity of electric vehicles.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solution: an electric vehicle charging network integrated platform based on a mutual assistance mode, comprising:

[0006] An AC / DC voltage conversion device for an electric vehicle power supply, the device comprising a bidirectional DC / DC module, a bidirectional DC / DC charging control module, a bidirectional DC / DC discharging control module, a bidirectional AC / DC module, a bidirectional AC / DC charging control module, a bidirectional AC / DC discharging control module and a filter;

[0007] A current metering device, the device includes a peripheral control circuit based on an F288M35 dual-core chip, the peripheral control circuit includes a main control device, a data acquisition module (including an AC sampling module and a DC sampling module), an IGBT drive module, a CAN bus communication module, a human-machine interface interaction module, a DC voltage sampling module, a DC current sampling module, an AC voltage sampling module, an AC current sampling module and a power supply module;

[0008] The vehicle networking system for reading electric vehicle parameters includes an OBD terminal, a backend system, and a mobile phone application. The OBD terminal is used to collect vehicle status information and analyze and process it through the backend system to determine whether the vehicle needs to be charged and whether it can supply power to the outside;

[0009] The platform supervision system includes an information collection module, a data processing module, a data analysis module, a cost adjustment module, a revenue level assessment module, a security supervision module, and a maintenance module;

[0010] Among them, the platform supervision system also includes a user behavior analysis module, which is used to collect user charging habits, travel patterns and preferences, and provide customized charging plan recommendations for each user.

[0011] Preferably, the information collection module is used to collect the main body information, environmental information and vehicle information of the new energy electric vehicle charging piles in the target area, obtain the main body information set, environmental information set and vehicle information set and transmit them together to the data processing module.

[0012] Preferably, the data processing module is used to process the ontology information set, the environment information set and the vehicle information set respectively to obtain an ontology data set, an environment data set and a vehicle data set, and transmit the ontology data set and the vehicle data set together to the data analysis module.

[0013] Preferably, the platform also includes an electric vehicle battery pack, a wireless charging device, an intelligent charging management system and a remote fault warning system.

[0014] Preferably, the battery pack is composed of a plurality of batteries stacked in series, a typical battery pack contains 96 batteries, the total voltage exceeds 400V, and the voltage of each battery is independently monitored to ensure the health status of the battery pack;

[0015] The wireless charging device includes a system control unit, a wireless power transmitting module, a wireless power receiving module, a wireless charging coil, a current detection module, a digital controller and an input / output I / O interface. The system control unit is connected to the internal circuit of the device through the I / O interface and communicates with the functional software in the device to control the working state of the wireless power transmitting module or the wireless power receiving module. The wireless power receiving module includes a power receiving unit and a communication and control unit. The communication and control unit communicates with the system control unit and starts the power receiving unit to work. The wireless charging coil is connected to the power transmitting unit and the power receiving unit respectively to realize energy exchange between devices.

[0016] The intelligent charging management system can automatically adjust the charging rate according to the user's travel plan and grid load conditions to optimize the charging time.

[0017] Preferably, the peripheral control circuit is used to realize the current metering function of car workshop charging, and the Internet of Vehicles system also includes an OBD terminal for reading and analyzing vehicle data through a device inserted into the vehicle's OBD interface, and then analyzing whether the vehicle needs to be charged and whether it can supply power to the outside.

[0018] Preferably, the platform also includes a mechanism for monitoring and controlling the voltage of each battery in the battery pack to prevent a battery in the battery pack from entering a deep discharge state and causing damage, and a dynamic layout planning module, which uses a machine learning algorithm to predict the growth trend and regional distribution changes of electric vehicles in the next few years, and dynamically adjusts the layout planning of charging piles based on this.

[0019] In this solution, the safety supervision module is used to perform safety evaluation on a separate new energy electric vehicle charging pile according to the ontology data set and the environmental data set, and decide whether to issue an abnormal signal according to the safety evaluation result, wherein the safety value is calculated as follows:

[0020] QXi=q1·∑(a1 i ·|AQ1 i -u1 i |)+q2·∑(a2 i ·|AQ2 i -u2 i |)

[0021] Among them, AQ1 i For the main safety data, AQ2 i is the environmental safety data, q1, q2 are specific proportional coefficients, u1 i The main safety data AQ1 i The corresponding preset standard value, a1 i The main safety data AQ1i The corresponding preset body influence coefficient, u2 i Environmental Safety Data AQ2 i The corresponding preset standard value, a2 i Environmental Safety Data AQ2 i The corresponding preset environmental impact coefficient, QXi is the safety value, and the safety value QXi is compared with the preset safety threshold. When the safety value QXi is greater than or equal to the preset safety threshold, an abnormal signal is issued. When the safety value QXi is less than the preset safety threshold, no abnormal signal is issued.

[0022] In this solution, the fee adjustment module is used to adjust the preset charging standards for different time periods according to the preset fee adjustment strategy and the entity analysis value and the vehicle analysis value, and transmit the adjustment results to the revenue level evaluation module; wherein the fee adjustment is calculated as follows:

[0023] BLi=g1·CFi+g2·BFi

[0024] Among them, g1 and g2 are both preset specific coefficients, BLi is the proportion value, and then the proportion interval-cost adjustment plan form in the preset cost adjustment strategy is searched according to the proportion value BLi, and the cost adjustment plan corresponding to the proportion interval in which the proportion value BLi falls is adjusted.

[0025] The preferred solution of this invention is that the remote fault warning system predicts possible problems in advance by monitoring the status of the charging piles and environmental changes, and automatically sends warning information to the maintenance team and users before a fault or extreme weather occurs. Simple faults can be quickly resolved through remote control technology, and for complex faults, the emergency response procedure is automatically triggered and maintenance personnel are dispatched to handle them on site.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This electric vehicle charging network integration platform based on the mutual assistance model has a unique market entry angle and innovative charging concept. The vehicle-to-electricity interconnection mode V2G and VEG mode are electric vehicle charging concepts proposed by some people in the industry. The excess electricity of electric vehicles is returned to the power grid. The charging concept in the Mo-ECar project is different from these, making charging more convenient and, to some extent, solving the problem of disturbance to the power grid. Leading advantage of automobile parameter reading technology. The electric vehicle non-stop charging collaborative network platform based on the crowdsourcing model is based on the automobile data collection system made by the Internet of Vehicles team of the BDCCL laboratory. The system has a set of mature automobile parameter reading models and corresponding service pages, which can provide users with good visual recommendation services.

[0028] The algorithm advantage is to query, decompose, combine and process the large-scale information generated when the car is used. Based on the data storage and reading based on big data and cloud services, this system will adopt various advanced technical methods such as coordinated optimization of data mining and information statistics, parallel access, predictive analysis, etc., to promote various data operations to be carried out quickly and accurately. At the same time, the scalability of the algorithm should also be considered. When the amount of data increases, the calculation is complex, and the user access volume is large, the system can support automatic optimization and integration of data resources, dynamically increase the number of service nodes, and distribute the load in parallel to each computing resource, so as to meet the processing requirements of massive information and improve the efficiency of system use.

[0029] 2. This integrated electric vehicle charging network platform based on the mutual assistance model realizes comprehensive monitoring and management of charging piles by integrating multiple modules such as information collection, data processing, data analysis, cost adjustment, and income level assessment, thereby improving the operational efficiency and profitability of the charging pile network. This integrated management method ensures that all relevant data can be effectively collected, processed, and analyzed, thus providing a solid foundation for subsequent decision-making. By intelligently analyzing users' charging needs and behavior patterns, the platform can provide users with more reasonable prices and services and improve user satisfaction. The introduction of user behavior analysis and personalized services enables the platform to better meet users' personalized needs and improve the overall user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0031] Figure 1 A block diagram of the automobiles of the present invention charging each other through induction current;

[0032] Figure 2 A control flow chart of the automobiles of the present invention charging each other through induction current;

[0033] Figure 3 It is a flow chart of the electric vehicle charging network integration platform based on the mutual assistance mode of the present invention;

[0034] Figure 4 It is a flow chart of the information acquisition module of the present invention;

[0035] Figure 5 is a flow chart of a data processing module of the present invention;

[0036] Figure 6 Flow chart of the user behavior analysis module of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Embodiment 1:

[0039] See also Figure 1-Figure 6 The present invention provides the following technical solutions: an electric vehicle charging network integration platform based on a mutual assistance mode, comprising:

[0040] An AC / DC voltage conversion device for an electric vehicle power supply, the device comprising a bidirectional DC / DC module, a bidirectional DC / DC charging control module, a bidirectional DC / DC discharging control module, a bidirectional AC / DC module, a bidirectional AC / DC charging control module, a bidirectional AC / DC discharging control module and a filter;

[0041] A current metering device, the device includes a peripheral control circuit based on an F288M35 dual-core chip, the peripheral control circuit includes a main control device, a data acquisition module (including an AC sampling module and a DC sampling module), an IGBT drive module, a CAN bus communication module, a human-machine interface interaction module, a DC voltage sampling module, a DC current sampling module, an AC voltage sampling module, an AC current sampling module and a power supply module;

[0042] The vehicle networking system for reading electric vehicle parameters includes an OBD terminal, a backend system, and a mobile phone application. The OBD terminal is used to collect vehicle status information and analyze and process it through the backend system to determine whether the vehicle needs to be charged and whether it can supply power to the outside;

[0043] The platform supervision system includes an information collection module, a data processing module, a data analysis module, a cost adjustment module, a revenue level assessment module, a security supervision module, and a maintenance module;

[0044] Among them, the platform supervision system also includes a user behavior analysis module, which is used to collect user charging habits, travel patterns and preferences, and provide customized charging plan recommendations for each user.

[0045] In this embodiment, the user behavior analysis module is used to collect user charging habits, travel patterns and preferences, and provide customized charging plan suggestions for each user. The user interface can allow users to set preferences, such as charging speed, cost budget, etc., to meet the personalized needs of different users.

[0046] In this embodiment, the information collection module is used to collect the new energy electric vehicle charging pile body information, environmental information, and vehicle information in the target area, obtain the body information set, environmental information set, and vehicle information set, and transmit them together to the data processing module.

[0047] In this embodiment, the information collection module is used to collect the main body information, environmental information, and vehicle information of the new energy electric vehicle charging pile in the target area, obtain the main body information set, environmental information set, and vehicle information set, and transmit these information sets to the data processing module. The main body information includes but is not limited to the model, location, status, charging rate, etc. of the charging pile. The environmental information includes but is not limited to the temperature, humidity, light intensity, etc. around the charging pile. The vehicle information includes but is not limited to the type of vehicle entering the charging pile area, the license plate number, the charging demand, etc.

[0048] In this embodiment, the data processing module is used to process the ontology information set, the environment information set, and the vehicle information set respectively to obtain the ontology data set, the environment data set, and the vehicle data set, and transmit the ontology data set and the vehicle data set together to the data analysis module.

[0049] In this embodiment, the data processing module is used to process the ontology information set, the environment information set, and the vehicle information set respectively to obtain the ontology data set, the environment data set, and the vehicle data set, and transmit the ontology data set and the vehicle data set together to the data analysis module. The data processing includes data cleaning, conversion, and standardization to ensure the accuracy of subsequent analysis.

[0050] In this embodiment, the platform also includes an electric vehicle battery pack, a wireless charging device, an intelligent charging management system, and a remote fault warning system.

[0051] In this embodiment, the battery pack is composed of a plurality of batteries stacked in series. A typical battery pack contains 96 batteries with a total voltage of more than 400V, and the voltage of each battery is independently monitored to ensure the health status of the battery pack; although the automotive power system regards the battery pack as a single high-voltage battery and charges and discharges the entire battery pack each time, the battery control system must consider the situation of each battery independently. If the capacity of one battery in the battery pack is slightly lower than that of the other batteries, then after multiple charge / discharge cycles, its charge state will gradually deviate from the other batteries. If the charge state of this battery is not periodically balanced with the other batteries, it will eventually enter a deep discharge state, resulting in damage and eventually forming a battery pack failure. To prevent this from happening, the voltage of each battery must be monitored to determine the charge state.

[0052] In this embodiment, the wireless charging device includes a system control unit, a wireless power transmitting module, a wireless power receiving module, a wireless charging coil, a current detection module, a digital controller and an input / output I / O interface. The system control unit is connected to the internal circuit of the device through the I / O interface and communicates with the functional software in the device to control the working state of the wireless power transmitting module or the wireless power receiving module. The wireless power receiving module includes a power receiving unit and a communication and control unit. The communication and control unit communicates with the system control unit and starts the power receiving unit to work. The wireless charging coil is connected to the power transmitting unit and the power receiving unit respectively to realize energy exchange between devices.

[0053] In this embodiment, the wireless power transmitting module or the wireless power receiving module is started to work, and the induced current is sent and received through the current detection module and the digital controller to realize the wireless charging function; the wireless power receiving module includes a power receiving unit and a communication and control unit, and the communication and control unit communicates with the system control unit, and starts the power receiving unit to work, and transmits the battery power of the external device through the wireless charging coil to the battery in the device. The wireless power transmitting module and the receiving module are set together, and the system control unit communicates with the functional software in the device. The functional software can set the device as a power supply or a power receiver, so that when the battery energy of the device is in urgent need, but there is no charging pile nearby, and charging is urgently needed, the power of other vehicles around can be temporarily supplemented by wireless charging. Similarly, when the power of other vehicles around is in urgent need, the assistance mode can be turned on to transfer the battery power of this device to it. Mutual assistance of battery energy between devices is realized, and charging and discharging processing is guaranteed in emergency situations. The wireless charging coil is connected to the power transmitting unit and the power receiving unit respectively.

[0054] The intelligent charging management system can automatically adjust the charging rate according to the user's travel plan and grid load conditions to optimize the charging time.

[0055] In this embodiment, the peripheral control circuit is used to realize the current metering function of the car workshop charging. The car networking system also includes an OBD terminal for reading and analyzing the vehicle data through a device inserted into the vehicle OBD interface, and then analyzing whether the vehicle needs to be charged and whether it can supply power to the outside.

[0056] In this embodiment, the platform also includes a mechanism for monitoring and controlling the voltage of each battery in the battery pack to prevent a battery in the battery pack from entering a deep discharge state and causing damage, as well as a dynamic layout planning module that uses a machine learning algorithm to predict the growth trend and regional distribution changes of electric vehicles in the next few years, and dynamically adjusts the layout planning of charging piles based on this.

[0057] In this embodiment, the safety supervision module is used to perform safety evaluation on a separate new energy electric vehicle charging pile according to the ontology data set and the environmental data set, and decide whether to issue or not an abnormal signal according to the safety evaluation result, wherein the safety value is calculated as follows:

[0058] QXi=q1·∑(a1 i ·|AQ1 i -u1 i |)+q2·∑(a2 i ·|AQ2 i -u2 i |)

[0059] Among them, AQ1 i For the main safety data, AQ2 i is the environmental safety data, q1, q2 are specific proportional coefficients, u1 i The main safety data AQ1 i The corresponding preset standard value, a1 i The main safety data AQ1 i The corresponding preset body influence coefficient, u2 i Environmental Safety Data AQ2 i The corresponding preset standard value, a2 i Environmental Safety Data AQ2 i The corresponding preset environmental impact coefficient, QXi is the safety value, and the safety value QXi is compared with the preset safety threshold. When the safety value QXi is greater than or equal to the preset safety threshold, an abnormal signal is issued. When the safety value QXi is less than the preset safety threshold, no abnormal signal is issued.

[0060] In this embodiment, the fee adjustment module is used to adjust the preset charging standards for different time periods according to the preset fee adjustment strategy and the entity analysis value and the vehicle analysis value, and transmit the adjustment results to the revenue level evaluation module; wherein the fee adjustment is calculated as follows:

[0061] BLi=g1·CFi+g2·BFi

[0062] Among them, g1 and g2 are both preset specific coefficients, BLi is the proportion value, and then the proportion interval-cost adjustment plan form in the preset cost adjustment strategy is searched according to the proportion value BLi, and the cost adjustment plan corresponding to the proportion interval in which the proportion value BLi falls is adjusted.

[0063] In this embodiment, the remote fault warning system monitors the status of the charging pile and environmental changes, predicts possible problems in advance, and automatically sends warning information to the maintenance team and users before a fault or extreme weather occurs. It quickly resolves simple faults through remote control technology, and automatically triggers emergency response procedures for complex faults, dispatching maintenance personnel to handle them on site.

[0064] In this embodiment, the profit level assessment module performs profit level assessment according to the adjustment result and issues a corresponding assessment grade; wherein the profit assessment is calculated as follows: SYi = [y1·(Z1 i -F1 i )+y2·(Z2 i -F2 i )+y3·(Z3 i -F3 i )](1-w i )

[0065] Among them, Z1 i For the adjusted charging data, Z2 i For the adjusted service charge data, Z3 i is the adjusted delayed parking fee data, w i is the preset floating coefficient corresponding to the cost adjustment plan in the adjustment result, y1, y2, y3 are all preset proportional coefficients and are positive values, SYi is the income value, and then all the income values ​​SYi are summed up to get the evaluation value, and the evaluation value is compared with the preset evaluation threshold. When the evaluation value is greater than or equal to the preset evaluation threshold, the issued evaluation level is level one, and when the evaluation value is less than the preset evaluation threshold, the issued evaluation level is level two.

[0066] When the maintenance module receives an abnormal signal from the safety supervision module, it dispatches maintenance personnel to repair the fault of the target new energy electric vehicle charging pile.

[0067] The data analysis module analyzes the ontology data set and the vehicle data set to obtain the ontology analysis values ​​and vehicle analysis values ​​of different preset time periods, and summarizes the ontology analysis values ​​and vehicle analysis values ​​of all time periods and transmits them to the cost adjustment module.

[0068] The working principle and use process of the present invention: When the electric vehicle charging network integrated platform based on the mutual assistance mode is in use, the OBD terminal reads the vehicle data and sends it to the background system through the CAN bus communication module. The background system determines whether the vehicle needs to be charged or can be powered externally based on the received data. According to the data analysis results, the background system communicates with the vehicle through a mobile phone application or directly, and issues charging or discharging instructions. The vehicle prepares to charge or discharge according to the instructions and activates the bidirectional DC / DC or AC / DC module. If wireless charging is used, the system control unit starts the wireless power transmitting module or receiving module; if a wired connection is used, energy is transmitted directly through the DC / DC or AC / DC module. During the entire charging or discharging process, the current detection module and the battery monitoring system continuously monitor various indicators and feed back the data to the background system.

[0069] Through the sensors and other data acquisition devices installed on the charging piles, the status information of the charging piles (such as charging status, fault records, etc.), surrounding environment information (such as temperature, humidity, etc.) and vehicle entry and exit information (such as license plate number, arrival time, departure time, etc.) are collected. The data processing module receives the data from the information acquisition module and pre-processes it, including but not limited to removing invalid data, filling missing values, data format conversion, etc., to ensure the accuracy and consistency of the data. The data analysis module uses statistical methods and machine learning algorithms to calculate key indicators such as charging demand and user behavior in different time periods based on the collected data. The maintenance module receives abnormal signals from the safety supervision module and arranges maintenance personnel to troubleshoot and repair through the scheduling system to ensure the stable operation of the charging pile network.

[0070] Embodiment 2:

[0071] An integrated electric vehicle charging network platform based on a mutual assistance mode, in addition to the basic modules in the first embodiment, can also add the following modules according to the budget and use environment:

[0072] Dynamic charging rate regulation and energy optimization distribution system: This system combines the real-time load data of the smart grid and the user's travel plan to predict the future load trend of the power grid through advanced algorithms. Based on the prediction results, the intelligent charging management system not only adjusts the charging rate of a single electric vehicle, but also optimizes the distribution of electric energy in the entire charging network to avoid overloading during peak hours of the power grid, while ensuring that electric vehicles get the required power in the shortest time. This system also considers the health status of the electric vehicle battery and extends the battery life by adjusting the charging strategy.

[0073] Enhanced wireless charging and inter-vehicle energy sharing: Integrate more efficient energy transmission technology into wireless charging devices to improve the efficiency and distance of wireless charging, so that vehicles can start charging without precise alignment when parked. Introduce inter-vehicle energy sharing function, allowing electric vehicles to directly charge wirelessly under certain conditions (such as emergency or with the owner's consent) to balance power demand.

[0074] Integrated environmental and meteorological monitoring system: Environmental and meteorological sensors are installed on charging piles to monitor key meteorological parameters such as temperature, humidity, wind speed, rainfall, and environmental data such as air quality in real time. These data are used to optimize charging strategies, such as automatically adjusting the charging rate or suspending charging in extreme weather conditions to protect the safety of equipment and users. At the same time, these data also provide the platform with additional data sources for more accurate analysis of user behavior and charging needs.

[0075] Advanced user behavior analysis and personalized recommendation system: The user behavior analysis module uses more advanced machine learning algorithms to combine the user's charging history, driving habits, preference settings, and real-time environmental data to generate a more accurate user profile. Based on the user profile, the platform provides personalized charging plan recommendations, including the best charging time, charging site selection, charging rate adjustment, etc., to improve user satisfaction and charging efficiency.

[0076] Intelligent maintenance and fault prediction system: Based on the remote fault warning system, more advanced predictive maintenance technology is introduced to identify potential fault signs in advance by analyzing the real-time data of charging piles and electric vehicle batteries. The system automatically triggers maintenance requests and dispatches the maintenance team to perform preventive maintenance, thereby reducing the occurrence of faults and improving the overall reliability of equipment and networks.

[0077] The implementation of this embodiment significantly improves the overall performance and user experience of the integrated platform for electric vehicle charging networks based on the mutual assistance model. The dynamic charging rate regulation and energy optimization distribution system effectively balances the grid load and electric vehicle charging needs, and enhances the stability and efficiency of the grid. The enhanced wireless charging and vehicle-to-vehicle energy sharing functions improve the flexibility and convenience of charging, especially providing electric vehicles with an additional source of power in emergency situations. The integrated environmental and meteorological monitoring system not only protects the safety of equipment and users, but also provides data support for more sophisticated user behavior analysis. The advanced user behavior analysis and personalized recommendation system as well as the intelligent maintenance and fault prediction system further improve the user experience and network operation efficiency.

[0078] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An integrated electric vehicle charging network platform based on a mutual assistance model, characterized in that: include: An AC / DC voltage conversion device for an electric vehicle power supply, the device comprising a bidirectional DC / DC module, a bidirectional DC / DC charging control module, and a bidirectional DC / DC discharging control module; A current metering device, the device comprising a peripheral control circuit based on an F288M35 dual-core chip, the peripheral control circuit comprising a main control device, a data acquisition module, an IGBT drive module, an AC voltage sampling module, an AC current sampling module and a power supply module; An Internet of Vehicles system for reading electric vehicle parameters, the system comprising an OBD terminal, a backend system, and a mobile phone application. The OBD terminal is used to collect vehicle status information and analyze and process it through the backend system; The platform supervision system includes an information collection module, a data processing module, a data analysis module, a cost adjustment module, a revenue level assessment module, a security supervision module, and a maintenance module; Among them, the platform supervision system also includes a user behavior analysis module, which is used to collect user charging habits, travel patterns and preferences, and provide customized charging plan recommendations for each user.

2. The electric vehicle charging network integrated platform based on the mutual assistance mode according to claim 1 is characterized by: The information collection module is used to collect the new energy electric vehicle charging pile body information, environmental information, and vehicle information in the target area, obtain the body information set, environmental information set, and vehicle information set, and transmit them together to the data processing module.

3. The electric vehicle charging network integrated platform based on the mutual assistance mode according to claim 2 is characterized by: The data processing module is used to process the ontology information set, the environment information set, and the vehicle information set respectively to obtain an ontology data set, an environment data set, and a vehicle data set, and transmit the ontology data set and the vehicle data set together to the data analysis module.

4. The electric vehicle charging network integrated platform based on the mutual assistance mode according to claim 3 is characterized by: The platform also includes electric vehicle battery packs, wireless charging devices, intelligent charging management systems, and remote fault warning systems.

5. The electric vehicle charging network integrated platform based on the mutual assistance mode according to claim 4 is characterized in that: The battery pack is composed of multiple batteries stacked in series. A typical battery pack contains 96 batteries with a total voltage of more than 400V, and the voltage of each battery is independently monitored to ensure the health status of the battery pack; The wireless charging device includes a system control unit, a wireless power transmitting module, a wireless power receiving module, a wireless charging coil, a current detection module, a digital controller and an input / output I / O interface. The system control unit is connected to the internal circuit of the device through the I / O interface and communicates with the functional software in the device to control the working state of the wireless power transmitting module or the wireless power receiving module. The wireless power receiving module includes a power receiving unit and a communication and control unit. The communication and control unit communicates with the system control unit and starts the power receiving unit to work. The wireless charging coil is connected to the power transmitting unit and the power receiving unit respectively to realize energy exchange between devices. The intelligent charging management system can automatically adjust the charging rate according to the user's travel plan and grid load conditions to optimize the charging time.

6. The electric vehicle charging network integrated platform based on the mutual assistance mode according to claim 5 is characterized by: The peripheral control circuit is used to realize the current metering function of the car workshop charging. The car networking system also includes an OBD terminal for reading and analyzing the vehicle data through a device inserted into the vehicle OBD interface, and then analyzing whether the vehicle needs to be charged and whether it can supply power to the outside.

7. The electric vehicle charging network integrated platform based on mutual assistance mode according to claim 6 is characterized by: The platform also includes a mechanism for monitoring and controlling the voltage of each battery cell in the battery pack to prevent a battery in the battery pack from entering a deep discharge state and causing damage, as well as a dynamic layout planning module that uses machine learning algorithms to predict the growth trend and regional distribution changes of electric vehicles in the next few years, and dynamically adjusts the layout planning of charging piles based on this.

8. The electric vehicle charging network integrated platform based on mutual assistance mode according to claim 7 is characterized by: The safety supervision module is used to evaluate the safety of a single new energy electric vehicle charging pile according to the ontology data set and the environmental data set, and decide whether to issue an abnormal signal according to the safety evaluation result, wherein the safety value is calculated as follows: <h2 style=";text-align:left;direction:ltr">QXi=q1·∑(a1<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> ·|AQ1<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> -u1<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> |)+q2·∑(a2<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> ·|AQ2<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> -u2<h2 style=";text-align:left;direction:ltr"> i <h2 style=";text-align:left;direction:ltr"> |) Among them, AQ1 i For the main safety data, AQ2 i is the environmental safety data, q1, q2 are specific proportional coefficients, u1 i The main safety data AQ1 i The corresponding preset standard value, a1 i The main safety data AQ1 i The corresponding preset body influence coefficient, u2 i Environmental Safety Data AQ2 i The corresponding preset standard value, a2 i Environmental Safety Data AQ2 i The corresponding preset environmental impact coefficient, QXi is the safety value, and the safety value QXi is compared with the preset safety threshold. When the safety value QXi is greater than or equal to the preset safety threshold, an abnormal signal is issued. When the safety value QXi is less than the preset safety threshold, no abnormal signal is issued.

9. The electric vehicle charging network integrated platform based on mutual assistance mode according to claim 8, characterized in that: The fee adjustment module is used to adjust the preset charging standards for different time periods according to the preset fee adjustment strategy and the entity analysis value and the vehicle analysis value, and transmit the adjustment results to the income level evaluation module; wherein the fee adjustment is calculated as follows: BLi=g1·CFi+g2·BFi Among them, g1 and g2 are both preset specific coefficients, BLi is the proportion value, and then the proportion interval-cost adjustment plan form in the preset cost adjustment strategy is searched according to the proportion value BLi, and the cost adjustment plan corresponding to the proportion interval in which the proportion value BLi falls is adjusted.

10. The electric vehicle charging network integrated platform based on mutual assistance mode according to claim 9, characterized in that: The remote fault warning system monitors the status of the charging piles and environmental changes, predicts possible problems in advance, and automatically sends warning information to the maintenance team and users before a failure or extreme weather occurs. It quickly resolves simple faults through remote control technology, and automatically triggers emergency response procedures for complex faults, dispatching maintenance personnel to handle them on site.

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