Electric vehicle interconnection, intercommunication and sharing charging operation method and device and storage medium

Abstract

The invention relates to the field of new energy automobile power supply, and provides an electric automobile interconnection sharing charging operation method and device and a storage medium, the method comprises the following steps: realizing heterogeneous system interconnection of a multi-source charging platform and a supervision platform through a standardized interface protocol, and establishing a cross-platform data channel; a dynamic user authentication system is constructed based on a cross-platform data channel, user registration and authority distribution of the electric vehicle are completed in a multi-mode identity authentication mode to obtain a user authority level, and an authentication result is fed back to the supervision platform; performing intelligent charging pile matching based on the real-time multi-dimensional charging resource atlas according to the user permission level, and generating a dynamic service instruction containing a navigation path and charging parameters; and in a charging service execution process, a bidirectional supervision data flow is created through a cross-platform data channel, full-life-cycle supervision of the charging process is executed in real time, and a service strategy is dynamically adjusted based on a feedback instruction of a supervision platform. According to the technical scheme, the electric vehicle can be cooperatively charged.

Description

Technical Field

[0001] The present application relates to the field of new energy vehicle power supply, and in particular to a method, device and storage medium for interconnected and shared charging operations of electric vehicles. Background Art

[0002] As the global energy transition accelerates, electric vehicles, as a key vehicle for clean energy applications, require intelligent, networked operation of their charging infrastructure, a core requirement for industry development. Currently, charging operators often rely on platform-based management systems to connect charging stations and provide user services. However, due to differing technical standards across platforms, a single user authentication method, and insufficient dynamic scheduling capabilities for charging resources, cross-platform collaboration is inefficient, making it difficult to meet the real-time charging needs of large-scale electric vehicle users.

[0003] Existing charging operation platforms typically employ a closed, single-platform architecture, static user rights management, offline resource matching strategies, and one-way regulatory data reporting. However, these existing technologies suffer from numerous significant flaws, including poor interoperability across multiple platforms, disconnected user authentication and rights management, insufficient resource matching dynamism, and delayed regulatory feedback. Summary of the Invention

[0004] The present application provides an electric vehicle interconnected and shared charging operation method, device and storage medium, which can achieve cross-platform stable interconnection, intelligent scheduling and coordinated optimization of closed-loop supervision when charging electric vehicles.

[0005] In one aspect, the present application provides a method for operating interconnected and shared charging of electric vehicles, the method comprising: Through standardized interface protocols, heterogeneous systems of multi-source charging platforms and regulatory platforms can be interconnected to establish cross-platform data channels; Building a dynamic user authentication system based on the cross-platform data channel, using a multimodal identity authentication method to complete electric vehicle user registration and authority allocation to obtain user authority levels, and feeding back the authentication results to the supervision platform; According to the user's permission level, intelligent charging pile matching is performed based on a real-time multi-dimensional charging resource map, and dynamic service instructions including navigation routes and charging parameters are generated; During the execution of the charging service, a two-way supervision data flow is created through the cross-platform data channel, the full life cycle supervision of the charging process is performed in real time, and the service strategy is dynamically adjusted based on the feedback instructions of the supervision platform.

[0006] On the other hand, the present application provides an electric vehicle interconnection and shared charging operation device, the device comprising: Channel establishment module, used to interconnect heterogeneous systems of multi-source charging platforms and supervision platforms through standardized interface protocols, and establish cross-platform data channels; An authentication module, configured to construct a dynamic user authentication system based on the cross-platform data channel, complete electric vehicle user registration and authority allocation using a multimodal identity authentication method to obtain user authority levels, and feed back authentication results to the supervision platform; An instruction generation module is used to perform intelligent charging pile matching based on the real-time multi-dimensional charging resource map according to the user's authority level and generate dynamic service instructions including navigation paths and charging parameters; The supervision module is used to create a two-way supervision data flow through the cross-platform data channel during the execution of the charging service, perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on the feedback instructions of the supervision platform.

[0007] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the technical solution of the above-mentioned electric vehicle interconnection and shared charging operation method are implemented.

[0008] In a fourth aspect, the present application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the technical solution of the above-mentioned electric vehicle interconnection and shared charging operation method.

[0009] From the technical solutions provided by the present application, it can be seen that, on the one hand, by establishing a cross-platform data channel through a standardized interface protocol, and verifying and optimizing the interface version compatibility and transmission stability, the problem of protocol differences between different charging platforms and regulatory systems is effectively solved, ensuring efficient intercommunication of multi-source data, and implementing multi-modal identity authentication based on the cross-platform data channel, dynamically associating user registration with authority allocation, not only realizes the real-time adaptation of the electric vehicle user authority level, but also enhances the platform's security protection capabilities; on the other hand, by integrating dynamic parameters such as geographic location, charging pile status, and grid load to construct a charging resource map, and combining electric vehicle user permissions to generate collaborative optimization instructions containing navigation paths and charging parameters, the accuracy of resource matching is significantly improved; thirdly, by uploading charging process data in real time through a two-way regulatory data stream and receiving regulatory instruction feedback, the dynamic adjustment of charging strategies and rapid response to abnormal events can be achieved, which can ensure the compliance and safety of charging services. In summary, the technical solution of the present application enables the coordinated optimization of cross-platform stable interconnection, intelligent scheduling, and closed-loop supervision when charging electric vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0011] Figure 1 This is a flow chart of the electric vehicle interconnection and shared charging operation method provided in an embodiment of the present application; Figure 2 This is a structural diagram of an electric vehicle interconnection and shared charging operation device provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0013] In this specification, adjectives such as first and second may be used only to distinguish one element or action from another element or action, without necessarily requiring or implying any actual such relationship or order. Where circumstances permit, reference to an element or component or step (etc.) should not be construed as being limited to only one of the elements, components, or steps, but may be one or more of the elements, components, or steps, etc.

[0014] In this specification, for the convenience of description, the sizes of various parts shown in the drawings are not drawn according to the actual proportions.

[0015] As the global energy transition accelerates, electric vehicles, as a key vehicle for clean energy applications, require intelligent, networked operation of their charging infrastructure, a core requirement for industry development. Currently, charging operators often rely on platform-based management systems to connect charging stations and provide user services. However, due to differing technical standards across platforms, a single user authentication method, and insufficient dynamic scheduling capabilities for charging resources, cross-platform collaboration is inefficient, making it difficult to meet the real-time charging needs of large-scale electric vehicle users.

[0016] In existing technologies, charging operation platforms typically adopt the following solutions: 1) Single-platform closed architecture: Each charging operator independently builds an operation platform with inconsistent interface protocols, resulting in compatibility barriers for cross-platform data interaction; 2) Static user authority management: User authentication relies on the traditional account and password system, lacks a dynamic authority adjustment mechanism, and is difficult to prevent the risk of identity theft; 3) Offline resource matching strategy: Charging station recommendations rely on static database queries, and fail to integrate multi-dimensional dynamic parameters such as traffic conditions and grid load in real time, resulting in recommendation results that deviate from actual user needs; 4) One-way regulatory data reporting: Regulatory data upload is separated from policy execution, making it impossible to achieve closed-loop supervision of the entire life cycle of the charging process.

[0017] However, the above-mentioned existing technologies have the following significant defects: 1) Poor compatibility of multi-platform interconnection: Protocol differences lead to unstable data transmission when heterogeneous systems are connected, affecting the continuity of cross-platform services; 2) Disconnection between user authentication and authority management: Static authentication methods cannot dynamically associate parameters such as user credit and vehicle status, posing a security risk; 3) Insufficient dynamic resource matching: Offline-generated charging instructions are difficult to respond to real-time environmental parameters such as changes in road conditions and fluctuations in electricity prices in a timely manner; 4) Delayed regulatory feedback: The one-way data reporting mechanism leads to delayed adjustments to regulatory policies, which cannot effectively prevent charging safety accidents.

[0018] In response to the above problems of the prior art, this application proposes a method for interconnecting and sharing charging operations of electric vehicles, the flow chart of which is shown in the attached figure. Figure 1 As shown, it mainly includes steps S101 to S104, which are detailed as follows: Step S101: The heterogeneous systems of the multi-source charging platform and the supervision platform are interconnected through a standardized interface protocol to establish a cross-platform data channel.

[0019] On the one hand, since different charging platforms and regulatory platforms (e.g., public security, traffic management, and power departments) employ heterogeneous technical architectures, standardized protocols are essential for eliminating semantic ambiguity and enabling data interoperability. In other words, without a unified protocol, the failure rate of cross-platform command parsing will increase significantly. On the other hand, when charging platforms are iteratively upgraded, new and old versions of the interface may add or remove fields or change semantics. Version verification effectively prevents data parsing errors caused by version differences. Therefore, to address compatibility issues caused by platform and version iterations and achieve industry interoperability, the present application can interconnect heterogeneous systems of multiple charging platforms and regulatory platforms through standardized interface protocols, establishing a cross-platform data channel. It should be noted that since universal transmission protocols (e.g., TCP) cannot meet the customized stability requirements of charging scenarios, and logging functions are deeply coupled with the protocol parsing layer, they cannot be fully replaced by external tools. Therefore, the above-mentioned embodiments can optimize transmission stability during the establishment of the cross-platform data channel. Specifically, transmission reliability is ensured through mechanisms such as heartbeat detection, data retransmission, and / or flow control. At the same time, system connection logs are generated to facilitate subsequent fault tracing and compliance audits.

[0020] As an embodiment of the present application, a standardized interface protocol is used to interconnect heterogeneous systems of a multi-source charging platform and a supervision platform. Establishing a cross-platform data channel can be achieved through steps S1011 to S1013, as detailed below: Step S1011: Deep packet inspection technology is used to identify differences in interface specifications when performing protocol conversion tests on each access platform.

[0021] Each access platform here includes the multi-source charging platform and the supervision platform in the aforementioned embodiment. Specifically, when performing protocol conversion testing on each access platform, using deep packet inspection technology to identify interface specification differences can be achieved through the following steps S10111 to S10115: Step S10111: Initialize the simulation test environment of each access platform.

[0022] Specifically, it includes building a simulation test environment that includes the target charging platform and the regulatory platform, deploying protocol probe nodes, loading the standard protocol template library, establishing a standard field mapping table, and finally, configuring the probe packet capture rules and setting trigger conditions. For example, initiating deep analysis when non-standard fields are detected.

[0023] Step S10112: Capture protocol interaction data.

[0024] The specific implementation method of step S10112 can be: sending a standardized test instruction set for charging start, stop and status query to each access platform, the probe captures the platform response data stream, stores the original message according to the session ID classification, and performs middleman decryption on the encrypted message to obtain the plaintext payload.

[0025] Step S10113: parse the protocol structure of each access platform layer by layer.

[0026] The specific implementation of step S10113 can be: extracting message transport layer features (including TCP port number, SSL fingerprint, etc.), identifying the basic protocol type, then parsing the application layer protocol structure, and finally outputting structured parsing results such as field name, data type, and position offset. It should be noted that for the HTTP protocol, the above-mentioned parsing of the application layer protocol structure mainly includes disassembling the header and body, extracting the RESTful API path and parameters, etc. For the MQTT protocol, it mainly parses the topic level and payload binary structure. For private protocols, the protocol structure is parsed by reverse analyzing the magic number and length identifier in the message header.

[0027] Step S10114: Analyze the correlation of the difference points.

[0028] The specific implementation method of step S10114 can be to compare the parsing results of the protocol structure of each access platform with the standard template field by field to generate a difference matrix, and then perform semantic tracing on the difference fields in the difference matrix, including tracing the original message interaction process, determining the business scenarios of the difference fields (such as charging power control) and the dependencies between the parsed fields, etc.

[0029] Step S10115: Evaluate the difference impact.

[0030] Here, the impact assessment of differences primarily involves categorizing differences based on business scenarios. A difference analysis report is then generated, with recommended handling strategies (including conversion, ignoring, and alerting). Finally, key differences are input into the protocol conversion middleware configuration system, triggering the generation of adaptation rules. In the above embodiment, the difference levels primarily include blocking-level differences that cause core functionality failure (e.g., missing charging instruction codes), compatibility-level differences that require logic conversion (e.g., inconsistent time formats), and extension-level differences for platform-specific functionality (e.g., extended fields for scheduled charging).

[0031] Step S1012: constructing a protocol conversion middleware based on the analysis results of the differences in the interface specifications.

[0032] In an embodiment of the present application, the protocol conversion middleware mainly includes a business logic allocation layer and a data encapsulation layer, wherein the business logic adaptation layer is used to realize the mutual conversion of control instruction sets of different platforms, and the data encapsulation layer is used to unify the data packet format and encryption standard. As an embodiment of the present application, the construction of the business logic adaptation layer based on the analysis results of the differences in the interface specifications can be: performing binary instruction set mapping conversion on the charging pile control instructions, retaining the core operation code and rewriting the parameter bit structure; implementing AES-GCM encryption conversion on the electric vehicle user identity field to generate an encrypted data unit containing a version identifier; when converting billing data, dynamically loading the central bank exchange rate API to obtain the real-time benchmark exchange rate for currency conversion. As for the construction of the business logic adaptation layer based on the analysis results of the differences in the interface specifications, it can be achieved through the following steps S10121 to S10124: Step S10121: Generate field mapping rules.

[0033] Generating field mapping rules specifically involves reading the field mapping relationships in the difference analysis report, defining a conversion function library, including type conversion, semantic conversion, and structural conversion, and finally generating a field mapping configuration file in formats such as XML and JSON.

[0034] Step S10122: Construct a dynamic packaging pipeline.

[0035] The construction of the dynamic encapsulation pipeline mainly includes two steps: designing the data packet assembly pipeline and realizing the atomicization of conversion logic. Among them, the design of the data packet assembly pipeline mainly receives the original platform data at the access layer, triggers the field mapping rules, performs type / semantic / structure conversion at the conversion layer, and assembles data packets according to the standard format at the encapsulation layer, etc., while realizing the atomicization of conversion logic mainly includes encapsulating each field conversion into an independent microservice and establishing a conversion dependency graph. For example, the station_id conversion must take precedence over the charge_power conversion.

[0036] Step S10123: Protect the data packet.

[0037] Here, data packet protection mainly involves encryption and integrity protection. Specifically, based on the encryption differences identified during the protocol testing phase, if the platform uses AES-CBC, the encapsulation layer is uniformly upgraded to AES-GCM, and HMAC-SHA256 signatures are added to unencrypted fields; the platform key exchange process is intercepted at the encapsulation layer and the standard negotiation protocol is injected; the key version identifier is embedded in the data header, etc.

[0038] Step S10124: Verify and optimize data flow.

[0039] Data flow verification and optimization mainly include: injecting test data flow to verify the correctness of encapsulation, then optimizing performance by enabling cache conversion for high-frequency fields (such as charging status) and using zero-copy technology to reduce memory copy overhead. Finally, the final encapsulation layer configuration parameters are output and synchronized to the protocol conversion middleware.

[0040] Step S1013: establishing a dual-channel redundant transmission link based on the protocol conversion middleware.

[0041] In the embodiment of the present application, the dual-channel redundant transmission link mainly refers to the main channel and the backup channel. The main channel uses the websocket protocol to maintain a long connection and transmit real-time control instructions, while the backup channel configures the MQTT protocol for offline data retransmission to ensure business continuity.

[0042] From steps S1011 to S1013 of the above embodiment, it can be seen that, on the one hand, by constructing a protocol conversion middleware (data encapsulation layer + business logic adaptation layer) and adopting a dual-channel redundant transmission mechanism (WebSocket + MQTT), the communication interruption problem caused by differences in multi-platform protocols is effectively solved; on the other hand, the data format and encryption standards of different platforms are unified through the data encapsulation layer to avoid parsing errors, and the business logic adaptation layer is used to achieve accurate mapping of the instruction set to ensure the reliable execution of cross-platform control instructions. The dual-channel design automatically switches to the backup channel when the main channel is abnormal, ensuring the real-time and continuity of the charging control instructions, and preventing charging interruptions or safety accidents due to network fluctuations.

[0043] Step S102: Build a dynamic user authentication system based on the established cross-platform data channel, use a multimodal identity authentication method to complete electric vehicle user registration and authority allocation to obtain user authority levels, and feed back the authentication results to the supervision platform.

[0044] Considering that if only a single verification method is used, it will not be able to meet the identity confirmation requirements of high-security scenarios (for example, high-voltage operation of charging piles), and static permission allocation cannot adapt to real-time risk changes. In addition, the regulatory platform also needs to grasp the legitimacy of the user's identity and the scope of operating permissions in real time. Therefore, in order to improve the accuracy of identity authenticity verification, prevent unauthorized operations (for example, charging of non-certified vehicles), and facilitate the regulatory platform to implement risk intervention, after establishing a cross-platform data channel, a dynamic user authentication system can be constructed based on the established cross-platform data channel, and a multi-modal identity authentication method can be used to complete electric vehicle user registration and permission allocation to obtain user permission levels, and the authentication results can be fed back to the regulatory platform. Specifically, as an embodiment of the present application, constructing a dynamic user authentication system based on the established cross-platform data channel and using a multi-modal identity authentication method to complete electric vehicle user registration and permission allocation to obtain user permission levels can be achieved through steps S1021 to S1023, as detailed below: Step S1021: Generate a biometric template through liveness detection and document OCR recognition, and perform online verification with the public security database.

[0045] Step S1022: Dynamically generate a user authority token based on the verification result of the online verification.

[0046] Here, the user authority token includes: a charging power limit based on the electric vehicle user's credit rating, a whitelist of available time periods associated with grid load characteristics, and a payment method permission adapted to the vehicle's battery parameters, etc. The calculation method of the electric vehicle user's credit rating can be implemented as follows: extract the on-time performance rate from the user's historical charging records ; Obtain the credit coefficient provided by the third-party credit reporting platform ;According to the punctuality rate of performance and the credit factor provided by a third-party credit reporting platform , calculate the dynamic power cap ,in, Standard power supply for the regional power grid.

[0047] Step S1023: Bind the user authority token to the cross-platform data channel. When a cross-platform operation is detected, the token parameters are parsed through the business logic adaptation layer to trigger the distributed identity authentication service for real-time authentication.

[0048] Specifically, the user authority token is bound to the cross-platform data channel. When a cross-platform operation is detected, the token parameters are parsed by the business logic adaptation layer, and the distributed identity authentication service is triggered to perform real-time authentication. This can be achieved through the following steps S10231 to S10233: Step S10231: Bind the user authority token to the cross-platform data channel.

[0049] Specifically, it can be: by mapping and registering the URI of the user permission token to the ID of the cross-platform data channel, adding the token fingerprint in the channel metadata to establish a binding relationship table, then injecting the token metadata during the Websocket long connection handshake phase, and implementing channel cascade control by configuring the MQTT topic tree and the subscription relationship between the token permissions. Finally, start the heartbeat monitoring mechanism, for example, verifying the token validity period and the channel activity status every 60 seconds, automatically renewing the user permission token that is about to expire, and so on.

[0050] Step S10232: Detect and analyze cross-platform operations.

[0051] Specifically, the detection and analysis of cross-platform operations mainly include identifying request traffic characteristics, extracting user authority token parameters, and associating analysis context. Among them, identifying request traffic characteristics is mainly achieved by capturing cross-platform API calls in the data channel and parsing the X-Platform-Transfer identifier in the HTTP Header, while extracting user authority token parameters is mainly achieved by disassembling the encrypted token through the business logic adaptation layer, such as verifying the validity of the digital signature, decrypting the power limit, time period whitelist and other core parameters, and parsing the blockchain hash to verify data integrity, etc. As for the associating analysis context, it can be achieved by matching the current operation scenario with the time and space constraints of the token authority (for example, whether the current time is within the available time period) and detecting the consistency of the device fingerprint with the initial authentication device.

[0052] Step S10233: Execute distributed real-time authentication.

[0053] When performing distributed real-time authentication, the authentication service cluster is first triggered, then multi-dimensional authentication is performed, and finally, dynamic policy instructions are returned, including full permission passed, partial permission passed or authentication failure, etc. Among them, the authentication service cluster can be triggered by selecting the nearest authentication node according to the token URI hash value and sending a lightweight authentication request package. The execution of multi-dimensional authentication includes power authentication to compare the requested charging power with the token upper limit value, time period authentication to verify whether the operation time is in the available whitelist, payment authentication to verify whether the payment method is in the permitted list, and device authentication to confirm the association between the operation terminal and the authentication terminal, etc.

[0054] Step S103: According to the user's authority level, intelligent charging pile matching is performed based on the real-time multi-dimensional charging resource map to generate dynamic service instructions including navigation routes and charging parameters.

[0055] Considering that the traditional GPS distance-based recommendation algorithm ignores key parameters such as electricity prices and road conditions, resulting in user decision-making deviations, and multi-dimensional data such as charging pile status (for example, idle or occupied), electricity prices, and traffic conditions change dynamically, they need to be aggregated into a spatiotemporal graph to support accurate recommendations; on the other hand, user permissions (for example, maximum charging power) directly affect the range of available charging piles. If permission constraints are ignored, charging piles that users cannot use may be recommended, and static instructions cannot cope with dynamic changes in the environment. Therefore, according to the user's permission level, intelligent charging pile matching can be performed based on the real-time multi-dimensional charging resource map to generate dynamic service instructions containing navigation paths and charging parameters. As an embodiment of the present application, according to the user's permission level, intelligent charging pile matching can be performed based on the real-time multi-dimensional charging resource map to generate dynamic service instructions containing navigation paths and charging parameters. This can be achieved through steps S1031 to S1034, as detailed below: Step S1031: real-time aggregation of multi-platform charging pile status data to construct a real-time multi-dimensional charging resource map including geographic location, interface type and real-time electricity price.

[0056] Specifically, we can first use cross-platform data channels to pull the charging pile data streams such as geographic location data, status parameters and device attributes of the access platform in real time and standardize them. Then, we can encode the charging pile locations into grid blocks and establish an R-tree index to accelerate regional queries to build a spatiotemporal data fusion model. Finally, we can trigger real-time layer refresh through status change data (for example, the charging pile changes from occupied to idle), establish an incremental update pipeline, and process abnormal data by retaining location information for offline pile data and taking the optimal status value for data from multiple platforms at the same location.

[0057] Step S1032: Dynamically calculate the charging demand urgency index based on the user's current vehicle SOC value, battery capacity and destination information.

[0058] The vehicle SOC value is the battery state of charge (SOC) of an electric vehicle, that is, the percentage of the battery's current remaining power. Specifically, based on the user's current vehicle SOC value, battery capacity and destination information, the dynamic calculation of the charging demand urgency index can be achieved in the following ways: real-time collection of parameters such as the vehicle SOC value, battery health and battery rated capacity through the on-board OBD interface; when the user enters information such as the destination coordinates and the preset arrival time, the vehicle status parameters are obtained; the basic urgency is generated by estimating the remaining mileage and calculating the travel distance requirement; finally, the weight of the urgency is dynamically adjusted by correcting time sensitivity and battery protection.

[0059] Step S1033: Based on the charging demand urgency index and the real-time multi-dimensional charging resource map, a multi-objective optimization algorithm is used to generate a charging station recommendation sequence.

[0060] In an embodiment of the present application, the optimization objectives in the multi-objective optimization algorithm include a weighted evaluation of time cost, economic cost, and battery health loss.

[0061] Step S1034: Generate a dynamic navigation route through the path planning engine and use the charging strategy optimizer to calculate the optimal charging parameter combination.

[0062] In an embodiment of the present application, the working method of the path planning engine includes constructing a charging time estimation model and performing the following steps: a) Establish a vehicle routing problem model with a time window and integrate the real-time reachable radius output by the charging time estimation model.

[0063] Specifically, the real-time reachable radius is calculated as follows:

[0064] in, For charging efficiency, for Charging power available at all times, is the driving power consumption function, is the real-time vehicle speed, is the battery capacity.

[0065] b) Generate a dynamic road resistance function based on the real-time reachable radius, where the road resistance weight of the dynamic road resistance function is inversely proportional to the estimated charging time.

[0066] c) The ant colony optimization algorithm is used to solve the optimal path, and its pheromone update rule is: , , in, is the pheromone volatility coefficient, and its value is positively correlated with the time sensitivity of the charging time estimation model output. is the pheromone baseline intensity (or pheromone total constant), which represents the baseline value of the total amount of pheromone released by a single ant on a unit path. For path The travel time is calculated in real time through the dynamic road resistance function. is a small constant to prevent division by zero errors.

[0067] From the above embodiments, it can be seen that by integrating dynamic parameters such as charging pile status, traffic conditions, and grid load, a time-space-related resource heat map is constructed, and navigation path planning and charging parameter calculation are performed simultaneously to avoid the separation of path selection and charging strategy in traditional solutions. Dynamically updating service instructions according to changes in resource maps can respond to fluctuations in charging pile status and changes in electric vehicle user demand, thereby significantly improving the efficiency of charging resource matching, reducing electric vehicle users' time and charging costs in searching for piles, and balancing regional grid load distribution. Step S104: During the execution of the charging service, a two-way supervision data flow is created through a cross-platform data channel to perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on feedback instructions from the supervision platform.

[0068] On the one hand, a one-way data flow cannot achieve two-way control, and the supervision platform also needs to receive charging data (such as power, temperature) in real time and issue control instructions; on the other hand, the charging process needs to cover all-stage monitoring such as startup preparation, charging execution, and abnormal termination to avoid supervision blind spots. Phased supervision may also miss startup parameter violations or termination exceptions. Therefore, according to the user authority level, after performing intelligent charging pile matching based on the real-time multi-dimensional charging resource map and generating dynamic service instructions containing navigation paths and charging parameters, a two-way supervision data stream can be created through a cross-platform data channel during the execution of the charging service, and the full life cycle supervision of the charging process can be performed in real time, and the service strategy can be dynamically adjusted based on the feedback instructions of the supervision platform. Specifically, as an embodiment of the present application, during the execution of the charging service, a two-way supervision data stream can be created through a cross-platform data channel, and the full life cycle supervision of the charging process can be performed in real time, and the service strategy can be dynamically adjusted based on the feedback instructions of the supervision platform. This can be achieved through steps S1041 to S1043, as detailed below: Step S1041: When charging starts, a filing data packet containing the electric vehicle user identity hash value, charging pile code and plan parameters is sent to the supervision platform, and the data packet is marked as the supervision baseline.

[0069] Step S1042: Upload multi-dimensional supervision data according to a preset sampling period during the charging process.

[0070] The above-mentioned multi-dimensional regulatory data includes real-time charging curve data, user operation logs, and device status monitoring data, etc. Among them, the real-time charging curve data is used to synchronize the charging pile code in the filing data package, and associate the second-level sampling values ​​of voltage, current and temperature. The user operation log records the timestamps and operation content of all interaction events, triggering policy conflict detection. The device status monitoring data is used to collect the charging module temperature and insulation impedance parameters, and perform deviation analysis with the regulatory baseline.

[0071] In the above embodiment, the implementation method of policy conflict detection can be: establishing a policy priority matrix, defining the effectiveness level of different regulatory instructions, wherein the effectiveness level is associated with the deviation threshold of the regulatory baseline; detecting the compatibility of the user reservation parameters with the new policy requirements, and when there is a conflict: a) for adjustable parameters, calling the collaborative optimization instruction set to generate a compensation plan, and push it to the electric vehicle user for confirmation; b) for non-adjustable parameters, triggering the service termination process and refunding the prepaid fees, while updating the regulatory baseline; recording the policy change impact assessment report, and feeding back the assessment results to the update module of the real-time multi-dimensional charging resource map. Among them, calling the collaborative optimization instruction set to generate a compensation plan can be achieved by calculating the expected cost difference under the new and old strategies. , the generated face value is (in, The user receives a voucher compensation of a preset coefficient and writes the compensation data into the user authority token; analyzes the available alternative charging stations, calls the path planning engine to replan the navigation route, and estimates the time difference. ;when Longer than the preset duration When charging, the service exchange interface with the cooperating merchant is activated to provide free lounge access during the charging waiting period, and the service exchange record is synchronized to the regulatory data flow.

[0072] Step S1043: After receiving the policy update instruction issued by the supervision platform, perform policy conflict detection and generate a service parameter adjustment queue.

[0073] Among them, the priority of the service parameter adjustment queue is dynamically determined by the deviation analysis results of the charging module temperature, insulation resistance parameters and the regulatory baseline.

[0074] In order to form a "monitoring-isolation-repair-optimization" closed loop, shorten the fault recovery time, and avoid system-level paralysis caused by a single charging device anomaly, in an embodiment of the present application, multi-level abnormality monitoring can also be implemented in the entire charging cycle, specifically: in the entire charging cycle, the charging pile controller collects the device abnormality code in real time, classifies it into communication failure, hardware failure and safety alarm, and marks the classification result as an abnormal event label; starts a differentiated processing process according to the abnormal event label: for communication failure, link self-inspection and channel switching are enabled, and the switching record is synchronized to the cross-platform data channel; for hardware failure, the device is marked as unavailable and a maintenance work order is dispatched, and the real-time multi-dimensional charging resource map is updated at the same time; for safety alarms, the emergency stop protection is triggered and the fire supervision platform is notified, and an emergency event log is generated and transmitted back to the two-way supervision data stream; a user-side abnormality report is generated, including a fault impact analysis and a solution time estimate, and the report data is input into the module for optimizing dynamic service instructions. In the process of implementing the above-mentioned multi-level abnormality monitoring, when the temperature of the charging gun of the charging pile is detected to be abnormal, the following processing steps are performed: a) Real-time monitoring of the charging gun temperature ,when ( (for a preset warning threshold): reduce the output power at a preset rate gradient (for example, 0.5°C / s) and start the cooling fan; synchronize the temperature data to the supervision data stream; b) if the temperature continues to rise after the gradient power reduction and ( c) Triggering the early warning linkage mechanism: broadcasting early warning signals to surrounding charging piles, triggering preventive detection of similar devices; associating early warning events with abnormal event tags, and generating cross-platform security logs.

[0075] In order to transform the distributed charging load of electric vehicles into dispatchable resources, improve the elasticity of the power grid, and reduce the dependence on fossil energy peak load regulation, the method of the above embodiment further includes: receiving the power grid dispatch instructions in the two-way regulatory data stream in real time, parsing the demand response coefficient and the time-of-use electricity price incentive signal; calculating the adjustable capacity margin according to the obtained vehicle battery status, and feeding the adjustable capacity margin back to the power adjustment module; the power adjustment module dynamically adjusts the output power curve of the charging pile according to the adjustable capacity margin; writing the adjustment result of the output power curve of the charging pile into the two-way regulatory data stream and triggering the billing policy update. In the above embodiment, if the demand response coefficient is , the current battery state of charge is , the total rated capacity of the battery is , the capacity margin can be adjusted It can be expressed as , and the power adjustment module dynamically adjusts the output power curve of the charging pile according to the adjustable capacity margin. It can be: for high priority vehicles, maintain the lowest rate (in, is the maximum allowable reverse power), synchronized to the real-time multi-dimensional charging resource map; for adjustable loads, based on the value of the time-of-use electricity price incentive signal Calculating V2G reverse power supply ,like ,in, is the electricity price incentive threshold for starting V2G, is the power release coefficient, is the maximum allowable reverse power.

[0076] It should be noted that in order to solve the problems of key leakage risk, privacy data abuse and operation denial in traditional solutions, and provide a trusted basis for multi-platform collaboration, the method of the above embodiment of the present application also includes a data security enhancement system throughout the above steps S101 to S104, and executes the following collaborative protection steps S61 to S63: Step S61, during the data transmission process across the cross-platform data channel of step S1, a one-time encryption key is generated by using quantum random numbers, and end-to-end encryption is implemented for the control instructions; the encrypted data packet is attached with a digital signature and synchronized to the blockchain node of step S63; Step S62, in the process of authenticating electric vehicle users in the dynamic user authentication system, Paillier semi-homomorphic encryption is implemented on the biometric template, and the encryption result of Paillier semi-homomorphic encryption is used as the basis for generating a user authority token; Step S63, the timestamp hash of key operations is recorded in the two-way regulatory data stream to the blockchain to form an audit chain, and the encryption key rotation strategy of step S61 is dynamically updated based on the blockchain evidence result. Furthermore, the data security enhancement system also includes: using fully homomorphic encryption for dynamic service instructions of charging parameters, so that the third-party billing system can execute the following in ciphertext: 1) fee settlement, i.e. fee ,in, Indicates the charging capacity of electric vehicles Encryption, Indicates the rate; 2) The settlement result is decrypted and written into the bidirectional regulatory data stream; 3) The key rotation mechanism is linked to the grid dispatch instruction: when the grid demand response coefficient is detected to change by more than a preset threshold (for example, 10%), the key rotation is triggered in advance; 4) The new key hash value is synchronized to the authorized node through the cross-platform data channel.

[0077] From the above attached Figure 1From the example of the electric vehicle interconnection and shared charging operation method, it can be seen that, on the one hand, a cross-platform data channel is established through a standardized interface protocol, and the interface version compatibility and transmission stability are verified and optimized, which effectively solves the problem of protocol differences between different charging platforms and regulatory systems, and ensures the efficient intercommunication of multi-source data. Based on the cross-platform data channel, multimodal authentication is implemented, and user registration and authority allocation are dynamically associated, which not only realizes the real-time adaptation of the electric vehicle user authority level, but also enhances the platform's security protection capabilities; on the other hand, by integrating dynamic parameters such as geographic location, charging pile status, and grid load to construct a charging resource map, and combining electric vehicle user permissions to generate collaborative optimization instructions containing navigation paths and charging parameters, the resource matching accuracy is significantly improved; thirdly, through the two-way supervision data stream, the charging process data is uploaded in real time and the supervision instruction feedback is received, which realizes the dynamic adjustment of the charging strategy and the rapid response to abnormal events, and can ensure the compliance and safety of the charging service. In summary, the technical solution of the present application enables the coordinated optimization of cross-platform stable interconnection, intelligent scheduling and closed-loop supervision when charging electric vehicles.

[0078] Please see the attached Figure 2 , is an electric vehicle interconnection and shared charging operation device provided in an embodiment of the present application, which may include a channel establishment module 201, an authentication module 202, an instruction generation module 203 and a supervision module 204, as detailed below: Channel establishment module 201, used to interconnect heterogeneous systems of multi-source charging platforms and supervision platforms through standardized interface protocols and establish cross-platform data channels; Authentication module 202 is used to build a dynamic user authentication system based on cross-platform data channels, complete electric vehicle user registration and authority allocation using a multi-modal identity authentication method to obtain user authority levels, and feed back the authentication results to the supervision platform; Instruction generation module 203, configured to perform intelligent charging pile matching based on a real-time multi-dimensional charging resource map according to the user's authority level and generate dynamic service instructions including navigation paths and charging parameters; The supervision module 204 is used to create a bidirectional supervision data flow through a cross-platform data channel during the execution of the charging service, perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on feedback instructions from the supervision platform.

[0079] Optionally, Figure 2 The exemplary electric vehicle interconnection and shared charging operation device may further include a classification module, a differentiation processing module, and an exception generation module, wherein: The classification module is used to collect device abnormality codes in real time through the charging pile controller during the entire charging cycle, classify them into communication failures, hardware failures and safety alarms, and mark the classification results as abnormal event labels; A differentiated processing module is used to initiate differentiated processing processes based on abnormal event tags: for communication failures, link self-checking and channel switching are enabled, and the switching records are synchronized to the cross-platform data channel; for hardware failures, the device is marked as unavailable and a maintenance work order is issued, while the real-time multi-dimensional charging resource map is updated; for safety alarms, emergency stop protection is triggered and the fire supervision platform is notified, and an emergency event log is generated and sent back to the bidirectional supervision data stream; The exception generation module is used to generate a user-side exception report, including a fault impact analysis and a solution time estimate, and input the report data into the module for optimizing the dynamic service instructions.

[0080] Optionally, Figure 2 The exemplary electric vehicle interconnection and shared charging operation device may further include a parsing module, a calculation module, an adjustment module, and an update module, wherein: The parsing module is used to receive grid dispatch instructions in the bidirectional regulatory data stream in real time and parse the demand response coefficient and time-of-use electricity price incentive signal; a calculation module, configured to calculate an adjustable capacity margin based on the acquired vehicle battery status, and feed the adjustable capacity margin back to the power adjustment module; An adjustment module is used to dynamically adjust the output power curve of the charging pile according to the adjustable capacity margin by the power adjustment module; The update module is used to write the adjustment results of the charging pile output power curve into the bidirectional supervision data stream and trigger the billing policy update.

[0081] From the above attached Figure 2 From the example of the electric vehicle interconnection and shared charging operation device, it can be seen that, on the one hand, a cross-platform data channel is established through a standardized interface protocol, and the interface version compatibility and transmission stability are verified and optimized, which effectively solves the problem of protocol differences between different charging platforms and regulatory systems, and ensures efficient intercommunication of multi-source data. Based on the cross-platform data channel, multimodal authentication is implemented, and user registration and authority allocation are dynamically associated, which not only realizes the real-time adaptation of the electric vehicle user authority level, but also enhances the platform's security protection capabilities; on the other hand, by integrating dynamic parameters such as geographic location, charging pile status, and grid load to construct a charging resource map, and combining electric vehicle user permissions to generate collaborative optimization instructions containing navigation paths and charging parameters, the resource matching accuracy is significantly improved; thirdly, through the two-way supervision data stream, the charging process data is uploaded in real time and the supervision instruction feedback is received, which realizes the dynamic adjustment of the charging strategy and the rapid response to abnormal events, and can ensure the compliance and safety of the charging service. In summary, the technical solution of the present application enables the coordinated optimization of cross-platform stable interconnection, intelligent scheduling and closed-loop supervision when charging electric vehicles.

[0082] Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 3 As shown, the electronic device 3 of this embodiment mainly includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program for the electric vehicle interconnection and shared charging operation method. When the processor 30 executes the computer program 32, the steps in the embodiment of the electric vehicle interconnection and shared charging operation method are implemented, such as Figure 1 Alternatively, when the processor 30 executes the computer program 32, the functions of the modules / units in the above-mentioned device embodiments are realized, for example Figure 2 The functions of the channel establishment module 201, the authentication module 202, the instruction generation module 203 and the supervision module 204 are shown.

[0083] Exemplarily, the computer program 32 for the electric vehicle interconnected shared charging operation method primarily includes: interconnecting heterogeneous systems of multiple charging platforms and a supervisory platform through standardized interface protocols, establishing a cross-platform data channel; constructing a dynamic user authentication system based on the cross-platform data channel, using multimodal authentication to complete electric vehicle user registration and permission allocation to obtain user permission levels, and feeding the authentication results back to the supervisory platform; performing intelligent charging pile matching based on a real-time, multi-dimensional charging resource map based on user permission levels, and generating dynamic service instructions containing navigation paths and charging parameters; during the charging service execution process, creating a bidirectional supervisory data stream through the cross-platform data channel, performing real-time full-lifecycle supervision of the charging process, and dynamically adjusting service strategies based on feedback instructions from the supervisory platform. The computer program 32 can be divided into one or more modules / units, one or more of which are stored in the memory 31 and executed by the processor 30 to implement the present application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 32 in the electronic device 3. For example, the computer program 32 can be divided into the functions of a channel establishment module 201, an authentication module 202, an instruction generation module 203 and a supervision module 204 (modules in the virtual device), and the specific functions of each module are as follows: the channel establishment module 201 is used to realize the heterogeneous system interconnection between the multi-source charging platform and the supervision platform through a standardized interface protocol, and establish a cross-platform data channel; the authentication module 202 is used to build a dynamic user authentication system based on the cross-platform data channel, and use a multimodal identity authentication method to complete the electric vehicle user registration and authority allocation to obtain the user authority level, and feed back the authentication result to the supervision platform; the instruction generation module 203 is used to perform intelligent charging pile matching based on the real-time multi-dimensional charging resource map according to the user authority level, and generate dynamic service instructions including navigation paths and charging parameters; the supervision module 204 is used to create a two-way supervision data stream through the cross-platform data channel during the execution of the charging service, perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on the feedback instructions of the supervision platform.

[0084] The electronic device 3 may include but is not limited to a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of electronic device 3 and does not constitute a limitation of electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0085] The processor 30 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0086] The memory 31 can be an internal storage unit of the electronic device 3, such as the hard drive or memory of the electronic device 3. The memory 31 can also be an external storage device of the electronic device 3, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, the memory 31 can include both the internal storage unit of the electronic device 3 and an external storage device. The memory 31 is used to store computer programs and other programs and data required by the electronic device. The memory 31 can also be used to temporarily store data that has been output or is about to be output.

[0087] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0088] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0089] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0090] In the embodiments provided in this application, it should be understood that the disclosed devices / equipment and methods can be implemented in other ways. For example, the device / equipment embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0091] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0092] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0093] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program of the electric vehicle interconnection and shared charging operation method can be stored in a storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments, that is, to realize the heterogeneous system interconnection of the multi-source charging platform and the supervision platform through a standardized interface protocol, and establish a cross-platform data channel; to build a dynamic user authentication system based on the cross-platform data channel, and use a multi-modal identity authentication method to complete the electric vehicle user registration and authority allocation to obtain the user authority level, and feedback the authentication result to the supervision platform; according to the user authority level, perform intelligent charging pile matching based on the real-time multi-dimensional charging resource map, and generate dynamic service instructions including navigation paths and charging parameters; during the execution of the charging service, create a two-way supervision data stream through the cross-platform data channel, perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on the feedback instructions of the supervision platform. Computer programs include computer program code, which may be in source code, object code, executable files, or some intermediate form. Storage media may include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunications signals, and software distribution media. It should be noted that the content of storage media may be appropriately expanded or reduced based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, storage media do not include electric carrier signals or telecommunications signals.

[0094] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application. The specific implementation methods described above further explain the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above description is only the specific implementation method of the present application and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included in the protection scope of the present invention.

Claims

1. A method for interconnected and shared charging operation of electric vehicles, characterized in that: The method comprises: Through standardized interface protocols, heterogeneous systems of multi-source charging platforms and regulatory platforms can be interconnected to establish cross-platform data channels; Building a dynamic user authentication system based on the cross-platform data channel, using a multimodal identity authentication method to complete electric vehicle user registration and authority allocation to obtain user authority levels, and feeding back the authentication results to the supervision platform; According to the user's permission level, intelligent charging pile matching is performed based on a real-time multi-dimensional charging resource map, and dynamic service instructions including navigation routes and charging parameters are generated; During the execution of the charging service, a two-way supervision data flow is created through the cross-platform data channel, the full life cycle supervision of the charging process is performed in real time, and the service strategy is dynamically adjusted based on the feedback instructions of the supervision platform.

2. The electric vehicle interconnection and shared charging operation method according to claim 1, characterized in that: The interconnection of the heterogeneous systems of the multi-source charging platform and the supervision platform through the standardized interface protocol and the establishment of a cross-platform data channel include: When performing protocol conversion tests on each access platform, deep packet inspection technology is used to identify differences in interface specifications; Building a protocol conversion middleware based on the analysis results of the differences in the interface specifications; A dual-channel redundant transmission link is established based on the protocol conversion middleware.

3. The electric vehicle interconnection and shared charging operation method according to claim 1, characterized in that: The dynamic user authentication system is constructed based on the cross-platform data channel, and a multi-modal authentication method is used to complete electric vehicle user registration and authority allocation to obtain user authority levels, including: Generate biometric templates through liveness detection and document OCR recognition, and conduct online verification with public security databases; Dynamically generate a user authority token based on the verification result of the online verification; The user authority token is bound to the cross-platform data channel. When a cross-platform operation is detected, the token parameters are parsed through the business logic adaptation layer to trigger a distributed identity authentication service for real-time authentication.

4. The electric vehicle interconnection and shared charging operation method according to claim 1, characterized in that: The method includes performing intelligent charging pile matching based on a real-time multi-dimensional charging resource map according to the user authority level and generating a dynamic service instruction including a navigation path and charging parameters, including: Real-time aggregation of charging pile status data from multiple platforms to build a real-time multi-dimensional charging resource map including geographic location, interface type and real-time electricity price; Dynamically calculate the charging demand urgency index based on the user's current vehicle SOC value, battery capacity and destination information; Based on the charging demand urgency index and the real-time multi-dimensional charging resource map, a multi-objective optimization algorithm is used to generate a charging station recommendation sequence; The path planning engine generates dynamic navigation routes and uses the charging strategy optimizer to calculate the optimal charging parameter combination.

5. The electric vehicle interconnection and shared charging operation method according to claim 4, characterized in that: The working method of the path planning engine includes building a charging time estimation model and performing the following steps: Establish a vehicle routing problem model with a time window and integrate the real-time reachable radius output by the charging time estimation model; generating a dynamic road resistance function based on the real-time reachable radius, wherein a road resistance weight of the dynamic road resistance function is inversely proportional to an estimated charging time; The ant colony optimization algorithm is used to solve the optimal path, and its pheromone update rule is: , , described is the pheromone volatility coefficient, and its value is positively correlated with the time sensitivity of the output of the charging time estimation model. is the pheromone baseline intensity or pheromone total constant, representing the baseline value of the total amount of pheromone released by a single ant on a unit path. For path The travel time is calculated in real time by the dynamic road resistance function. is a small constant to prevent division by zero errors.

6. The electric vehicle interconnection and shared charging operation method according to claim 1, characterized in that: The method further comprises: During the entire charging cycle, the charging pile controller collects device abnormality codes in real time, classifies them into communication failures, hardware failures, and safety alarms, and marks the classification results as abnormal event labels; Differentiated processing flows are initiated based on abnormal event tags: for communication failures, link self-checking and channel switching are enabled, and switching records are synchronized to the cross-platform data channel; for hardware failures, the device is marked as unavailable and a maintenance work order is issued, while the real-time multi-dimensional charging resource map is updated; for safety alarms, emergency stop protection is triggered and the fire monitoring platform is notified, and an emergency event log is generated and transmitted back to the bidirectional monitoring data stream; Generate a user-side exception report, including fault impact analysis and solution time estimate, and input the report data into the module for optimizing the dynamic service instructions.

7. The electric vehicle interconnection and shared charging operation method according to claim 1, characterized in that: The method further comprises: receiving in real time the grid dispatching instructions in the bidirectional regulatory data stream, and parsing the demand response coefficient and the time-of-use electricity price incentive signal; Calculating an adjustable capacity margin based on the acquired vehicle battery status, and feeding the adjustable capacity margin back to the power adjustment module; The power adjustment module dynamically adjusts the output power curve of the charging pile according to the adjustable capacity margin; The adjustment result of the charging pile output power curve is written into the bidirectional supervision data flow and triggers the billing policy update.

8. An electric vehicle interconnection and shared charging operation device, characterized in that: The device comprises: Channel establishment module, used to interconnect heterogeneous systems of multi-source charging platforms and supervision platforms through standardized interface protocols, and establish cross-platform data channels; An authentication module, configured to construct a dynamic user authentication system based on the cross-platform data channel, complete electric vehicle user registration and authority allocation using a multimodal identity authentication method to obtain user authority levels, and feed back authentication results to the supervision platform; An instruction generation module is used to perform intelligent charging pile matching based on the real-time multi-dimensional charging resource map according to the user's authority level and generate dynamic service instructions including navigation paths and charging parameters; The supervision module is used to create a two-way supervision data flow through the cross-platform data channel during the execution of the charging service, perform real-time full life cycle supervision of the charging process, and dynamically adjust the service strategy based on the feedback instructions of the supervision platform.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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