Method, system, device and medium for function implementation of charging operation system

Abstract

This disclosure provides a method, system, device, and medium for implementing the functions of a charging operation system. It deploys at least one service module on a client side using a microservice architecture. The service modules interact with each other through a preset communication method, which is at least one of the following: remote call based on a service interface, or publish / subscribe based on a message queue. Each service module includes at least one functional unit. Some service modules are configured to dynamically load the implementation class of at least one functional unit through a plug-in mechanism, thereby integrating at least one functional unit in a plug-in manner. This disclosure deploys at least one service module using a microservice architecture and achieves a flexible, pluggable deployment of functional units through the factory pattern mechanism of the application framework, improving the system's scalability.

Description

Technical Field

[0001] This disclosure relates to microservice technology and information processing technology, and in particular to a method, system, device and medium for implementing the functions of a charging operation system. Background Technology

[0002] The construction and deployment of charging operation systems have a significant impact on the popularization and promotion of new energy vehicles. Since charging involves users' personal data, privatized deployment of charging operation systems has become the mainstream deployment method to ensure the security of this data during the vehicle charging process.

[0003] In related technologies, a monolithic architecture is used to deploy the charging operation system privately. However, with the diversification of charging demand, the functions provided by the charging operation system also need to be continuously expanded. However, the deployment scheme of the monolithic architecture has poor scalability and cannot support diversified charging needs. Summary of the Invention

[0004] To address the aforementioned technical problems, embodiments of this disclosure provide a method, system, device, and medium for implementing the functions of a charging operation system.

[0005] According to one aspect of the present disclosure, a charging operation system is provided, comprising: at least one service module deployed on a client in a microservice architecture; the service modules in the at least one service module interact with each other through a preset communication method, the preset communication method being at least one of the following: a remote call method based on a service interface, a publish-subscribe method based on a message queue; each service module in the at least one service module includes at least one functional unit; at least some of the service modules in the at least one service module are respectively configured to dynamically load the implementation class of at least one functional unit through a plug-in mechanism, thereby integrating at least one functional unit in a plug-in form.

[0006] According to one aspect of the present disclosure, a method for implementing the functions of a charging operation system is provided. The method includes: traversing the module configuration files corresponding to at least some of the service modules in at least one service module to obtain key-value information of at least one functional unit to be loaded in each of the at least some service modules, wherein the module configuration files record the key-value information of the functional unit to be loaded; based on the key-value information of the functional unit to be loaded, obtaining the implementation class of the functional unit to be loaded, and dynamically loading the implementation class of the at least one functional unit to be loaded through a decoupling extension mechanism, thereby realizing the integration of the at least one functional unit to be loaded in a plug-in manner.

[0007] According to another aspect of the present disclosure, a computer-readable storage medium is provided, which stores computer program instructions that, when executed, implement the above-described method for implementing the functions of the charging operation system.

[0008] According to another aspect of the present disclosure, an electronic device is provided, the electronic device comprising:

[0009] Memory, used to store computer program products;

[0010] A processor is used to execute a computer program product stored in a memory, and when the computer program product is executed, it implements the functional implementation method of the above-mentioned charging operation system.

[0011] According to another aspect of the present disclosure, a computer program product is provided, including computer program instructions, characterized in that, when the computer program instructions are executed by a processor, they implement the above-described method for implementing the functions of the charging operation system.

[0012] Based on the embodiments of this disclosure, for a charging operation system, at least one service module is deployed on the client side using a microservice architecture. These service modules interact through a preset communication method. Each service module includes at least one functional unit. At least some of the service modules dynamically load the implementation class of the at least one functional unit through a plug-in mechanism, achieving integration of the at least one functional unit in a plug-in manner. Therefore, this disclosure improves the scalability of the charging operation system by deploying at least one service module on the client side using a microservice architecture. Furthermore, the plug-in mechanism enables flexible deployment of at least one functional unit included in some service modules. Since the flexible deployment method supports hot deployment, the functions of the service modules can be dynamically updated and maintained without stopping the charging operation system. This makes functional expansion more convenient and flexible, reduces system downtime, optimizes the functional expansion and resource utilization efficiency of each service module in the system, and further enhances the scalability of the charging operation system.

[0013] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0014] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of the embodiments thereof in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0015] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein:

[0016] Figure 1 This is a schematic diagram of the structure of one embodiment of the charging operation system disclosed herein;

[0017] Figure 2 This is a schematic diagram of another embodiment of the charging operation system disclosed herein;

[0018] Figure 3 This is a schematic diagram of another embodiment of the charging operation system disclosed herein;

[0019] Figure 4 This diagram illustrates the deployment of the charging extension service module of the charging operation system disclosed herein in a plug-in manner.

[0020] Figure 5 A flowchart illustrating one embodiment of the functional implementation method of the charging operation system disclosed herein;

[0021] Figure 6 A flowchart illustrating another embodiment of the functional implementation method of the charging operation system disclosed herein;

[0022] Figure 7 This is a structural diagram of an electronic device provided as an illustrative embodiment of the present disclosure. Detailed Implementation

[0023] Hereinafter, exemplary embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present disclosure, and not all embodiments of the present disclosure, and it should be understood that the present disclosure is not limited to the exemplary embodiments described herein.

[0024] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this disclosure.

[0025] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0026] It should also be understood that in the embodiments disclosed herein, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0027] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.

[0028] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship.

[0029] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0030] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0031] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0032] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0033] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0034] The embodiments disclosed herein can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0035] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0036] This disclosure outlines

[0037] In the process of realizing this disclosure, the inventors discovered through research that when a charging operation system is deployed using a monolithic architecture, it lacks flexible configuration for different scales and needs, and is difficult to adapt to rapidly changing market demands. For example, when deploying a charging operation system, charging station 1 does not have photovoltaic and energy storage equipment and only wants to deploy core charging services and extended charging services, without needing to deploy photovoltaic, energy storage, and charging services. However, a monolithic architecture-deployed charging operation system cannot meet this deployment requirement.

[0038] In order to improve the scalability of the charging operation system and support diverse charging needs, the inventors have proposed the technical solution disclosed herein.

[0039] Exemplary System

[0040] Figure 1 This is a schematic diagram of the structure of one embodiment of the charging operation system disclosed herein. Figure 1 As shown, the charging operation system includes at least one service module 101 deployed on the client in a microservice architecture;

[0041] At least one service module interacts with each other through a preset communication method, which is at least one of the following: remote call method based on service interface, or publish-subscribe method based on message queue;

[0042] Each service module in at least one service module includes at least one functional unit;

[0043] At least some of the service modules in at least one service module are configured to dynamically load the implementation class of at least one functional unit through a plug-in mechanism, thereby integrating at least one functional unit in a plug-in manner.

[0044] Specifically, at least one service module 101 can be deployed on the client in a private deployment manner to provide users with corresponding charging services.

[0045] In this disclosure, at least one service module 101 deployed in a microservice architecture includes at least one of the following: a charging core service module 11, a charging extension service module 12, a device connection service module 13, a photovoltaic-storage-charging service module 14, a background task service module 15, and an administrative docking service module 16. The charging core service module 11 is a core service that the entire system must guarantee high availability for. If the charging core service module is unavailable, it will directly affect the charging of user vehicles. The device connection service module 13 provides connection services with charging pile equipment, thereby enabling charging of user vehicles through this connection. If the device connection service module 13 is unavailable, it will directly affect the charging of user vehicles. Therefore, the charging operation system includes at least the charging core service module 11 and the device connection service module 13.

[0046] In this disclosure, at least one service module 101 interacts with other service modules through a preset communication method, which is at least one of the following: a remote call method based on a service interface, or a publish-subscribe method based on a message queue. Specifically, for interactions between service modules requiring immediate response, efficient Remote Procedure Call (RPC) can be implemented through the Dubbo interface. For interactions between service modules with less stringent immediate response requirements, distributed subscription via a message queue is sufficient. Because message queues offer high performance, high reliability, and high throughput, the publish-subscribe interaction mode supports rapid storage and transmission of massive amounts of messages, making it suitable for scenarios such as real-time message processing, traffic shaping, and data synchronization.

[0047] At least some of the service modules 101 mentioned above include at least one functional unit. For example, the charging core service module 11, the charging extension service module 12, the photovoltaic energy storage and charging service module 14, and the background task service module 15 all include at least one functional unit. Other service modules may only include one functional unit, such as the device connection service module 13. The at least some service modules including at least one functional unit utilize a plug-in mechanism, such as the factory pattern mechanism of the Spring framework, to dynamically load the implementation class of at least one functional unit, thus integrating at least one functional unit in a plug-in manner.

[0048] The charging operation system disclosed herein deploys at least one service module on the client side using a microservice architecture. These service modules interact through a pre-defined communication method. Each service module includes at least one functional unit, and at least some of the service modules dynamically load the implementation class of the at least one functional unit through a plug-in mechanism, thus integrating the at least one functional unit in a plug-in manner. Therefore, this disclosure improves the scalability of the charging operation system by deploying at least one service module on the client side using a microservice architecture. Furthermore, the plug-in mechanism enables flexible deployment of at least one functional unit included in some service modules. Since the flexible deployment method supports hot deployment, the functions of service modules can be dynamically updated and maintained without stopping the charging operation system. This makes functional expansion more convenient and flexible, reduces system downtime, optimizes the functional expansion and resource utilization efficiency of each service module in the system, and further enhances the scalability of the charging operation system.

[0049] Figure 2 This is a schematic diagram of another embodiment of the charging operation system disclosed herein, as shown below. Figure 2 As shown, the charging operation system also includes at least one big data intelligence module 102 deployed on a server. The at least one big data intelligence module 102 is configured to provide data computing services to some functional units in at least one service module through an application programming interface.

[0050] The data computing services provided by the big data intelligence module can include data analysis services, intelligent prediction services, etc.

[0051] When some functional units in at least one service module 101 deployed on the client server need to call the big data intelligence module to perform functions, they can send the data to be processed to the corresponding big data intelligence module through the application programming interface provided by at least one big data intelligence module 102, so that the big data intelligence module can process the data to be processed and obtain the processing result.

[0052] For example, the charging extended service module 12 includes a safety function unit. This unit performs overvoltage protection, leakage protection, overcurrent protection, overtemperature protection, and overload protection to ensure the safe operation of the charging pile under various abnormal conditions and protect the equipment. After acquiring charging data such as voltage and current during vehicle charging, the safety function unit can send the acquired charging data to the big data intelligent module 102 by calling the API interface of the big data intelligent module. The big data intelligent module analyzes and processes the charging data and then returns charging safety protection data to the safety function unit.

[0053] To enhance system data security, anonymized data was used for training the big data intelligence module (big data model). For example, when training the charging safety protection intelligent module, sensitive data such as order information and user information were avoided. Instead, only non-sensitive data such as voltage, current, maximum temperature, individual cell temperature difference, and individual cell pressure difference during the charging process were used. This avoids the need to obtain users' personal information when processing data using the big data intelligence module, ensuring that the big data intelligence module will not use or leak user information. Therefore, when the big data intelligence module receives a data packet to be processed, it can utilize the pre-trained big data model to process the data packet and obtain the processing result.

[0054] In this implementation, by deploying the big data intelligence module on the cloud server in API mode, it is possible to provide big data analysis, prediction and other computing services to each privately deployed tenant through the API interface, ensuring that the system has good big data intelligence module capabilities, and is more efficient and secure.

[0055] In some alternative implementations, the above Figure 1 The illustrated embodiment describes at least one of the following service modules: a charging core service module 11, a charging extension service module 12, a device connection service module 13, a photovoltaic energy storage and charging service module 14, a background task service module 15, and an administrative docking service module 16. The functions of each service module are described below.

[0056] The charging core service module 11 is used to provide charging services for vehicles via the power grid. This module involves the most critical service functional units of the charging business, including user units, order units, charging link units, site units, and transaction units. The charging core service module is a core service for which the entire system must be highly available; its unavailability will directly affect vehicle charging. Specifically, the user unit manages user information, including user registration, login, and authentication, enabling user authentication and access control to ensure system security. The order unit processes user-submitted order information, including order creation, modification, and querying, enabling order management and processing. The payment unit processes user payment requests for charging orders, including payment method selection and payment amount calculation, providing secure and reliable payment functionality. The charging link unit handles charging-related functions, including monitoring charging status and calculating charging fees; it also enables monitoring and management of charging equipment. The site unit manages charging station information, including site creation, maintenance, and querying. The transaction unit is responsible for handling transaction-related functions, including generating transaction records and querying transaction status. Through the transaction unit, transactions can be tracked and managed.

[0057] It should be noted that the management and verification of user information involved in the above-mentioned user module in this technical solution comply with the provisions of relevant laws and regulations and do not violate good morals.

[0058] The Charging Extension Service Module 12 provides additional services to the core charging service module. This module primarily handles business units not directly related to the core charging business, such as the reporting unit, operation and maintenance unit, safety unit, work order / task unit, spare parts unit, marketing activity unit, and points unit. Specifically, the reporting unit is used to statistically analyze charging station usage, such as charging volume statistics, equipment utilization rate, and user behavior analysis. The operation and maintenance unit is used for remote monitoring and management of charging piles, and for remote diagnosis, maintenance, and repair of faults detected at charging piles. The safety unit performs overvoltage protection, leakage protection, overcurrent protection, overtemperature protection, and overload protection to ensure the safe operation of charging piles under various abnormal conditions and protect equipment safety. The work order / task unit creates corresponding work orders for user after-sales service requests and assigns them to appropriate after-sales personnel for processing, effectively managing charging after-sales service needs. The spare parts unit provides various spare parts for the safe operation of charging piles, such as power supply units and communication units. The Marketing Activities unit is responsible for various promotional activities within the charging operation system, including discounts, spending thresholds, and free gifts. The Points unit is responsible for automatically awarding points upon completion of user top-ups or charging payments.

[0059] In this disclosed technical solution, by deploying the charging extension service module 12 and the charging core service module 11 separately, it helps to prevent improper operation or unavailability of the various functional modules of the charging extension service module from affecting the use of the charging core service module, thereby ensuring the high availability of the charging core service.

[0060] Device connection service module 13 provides connection services between the charging pile and the charging station equipment. This module interfaces with the charging station protocols of mainstream charging station manufacturers and maintains a persistent connection with the charging pile through an asynchronous network application framework (such as Netty). The charging pile reports data packets via the Message Queuing Telemetry Transport (MQTT) protocol. The server parses and decrypts the data packets reported by the charging pile, encrypts the final processed reply packet, and then sends it back to the charging pile via the MQTT protocol, thus ensuring communication connectivity with the charging pile.

[0061] In this disclosed technical solution, the device connection service module does not need to be updated frequently, and charging pile companies generally do not update their protocols frequently. Therefore, the device connection service module does not need to be updated often. By deploying the device connection service module separately from other services, it helps to ensure that the core service of charging piles maintains connectivity, and further ensures the stability of the charging business.

[0062] The photovoltaic-storage-charging service module 14 is used to provide charging services for vehicles through photovoltaic and energy storage equipment. This module primarily targets charging stations with installed photovoltaic and energy storage equipment and includes functional units such as a photovoltaic and energy storage asset management unit, a governance management unit, a project operation unit, a strategy management unit, and an equipment connection unit. Each functional unit is responsible for handling the equipment connection, operating status, and load demand of the photovoltaic and energy storage equipment; intelligently allocating energy resources; optimizing energy utilization efficiency; and promptly diagnosing, maintaining, and repairing faults in the photovoltaic and energy storage equipment to ensure the stable operation of the module and promote the development of green energy.

[0063] In the technical solution disclosed herein, the business attributes of the photovoltaic storage and charging service module are relatively independent and not closely related to the charging business. By deploying the photovoltaic storage and charging service module separately from other service modules, the charging operation system is not affected, and the charging operation system of charging stations that do not involve photovoltaic storage and charging business does not need to deploy this service module.

[0064] The background task service module 15 is used to periodically complete the system's background tasks. The charging operation system needs to execute a series of periodic or delayed-triggered background tasks to ensure the smooth operation of business processes and timely data updates, such as periodically compiling statistical report data, periodically updating site status, reissuing coupons, and processing abnormal orders, etc.

[0065] In this disclosed technical solution, the background task service module periodically consumes significant system resources. Deploying the background task service module separately from other service modules helps reduce the impact on the core charging service and avoids system instability caused by task timeouts or resource contention. The background task service module can run on specific servers or clusters, which facilitates task optimization and maintenance, as well as subsequent task updates, configuration management, and fault recovery, thereby enhancing the overall maintainability of the system.

[0066] The Administrative Connection Service Module 16 provides connection services with preset platforms. This module allows charging station operators to apply for new energy vehicle subsidies by submitting the charging station's information and operator data to the new energy vehicle subsidy platform. Since the eligibility criteria for operating subsidies for charging stations vary across different administrative regions, this module connects with new energy vehicle subsidy platforms in different regions to help charging station operators receive subsidies.

[0067] In this embodiment, the administrative docking service module is relatively independent from the charging core service module. Moreover, it needs to push data such as orders, device status, and charging status to other platforms, which will consume a lot of system resources. Therefore, deploying the administrative docking service module separately from other service modules helps to reduce the impact on the charging core service module and enhances the overall maintainability of the system.

[0068] In some optional implementations, the charging operation system also includes a service registry cluster, a deployment log module, a service tracing module, and a storage module. The service registry cluster provides registration services for service providers (service nodes in each service module) and stores their registration and configuration information, facilitating service autonomy within the charging operation system. The service registry cluster is implemented based on the Zookeeper component, but other implementations such as Eureka or Nacos can also be used. The log module provides log collection, storage, and query functions, collecting log information of operations occurring on each service node, providing log records for subsequent maintenance and problem localization. The service tracing module provides alarm services; when problems are detected in services provided by the system's microservice cluster, such as overvoltage protection or leakage protection issues, timely alarms are provided through terminal devices. The storage module includes storage services such as object storage, caching services, and data persistence read / write separation, used to store business data in various forms; it also includes message subscription functionality for information exchange between different services; a scheduled task function for managing and planning the execution of background task services; and a continuous integration / continuous deployment (CI / CD) module for frequently updating and deploying the system.

[0069] It should be noted that the service module is an illustration. As the charging operation system expands, it may include other microservice modules, or the microservices of the charging operation system may be divided in a new way to obtain different service modules. For example, the user unit in the core charging service module may be divided into the extended charging service module as a functional unit of the extended charging service module. The functional units included in the above service modules are also illustrative. Each service module may include more or fewer functional units. For example, the extended charging service module may also include an orderly charging unit, a reconciliation unit, etc.

[0070] Figure 3 This is a schematic diagram of another embodiment of the charging operation system disclosed herein, as shown below. Figure 3 As shown, the charging operation system includes a private cluster (in which are deployed...) Figure 1 At least one service module 101), a gateway device, and at least one big data intelligence module deployed on a server.

[0071] Private clusters 1, 2, and 3 each deploy at least one service module using a microservice architecture; while at least one big data intelligence module is deployed on the cloud server. The business layer of the big data intelligence module provides computing services to some functional units within the service modules of the private clusters, such as data analysis services (e.g., charging safety protection services) and intelligent prediction services (e.g., project calculation services). The foundation layer is used for basic data processing operations, such as data cleaning, data transformation, and data storage.

[0072] In this disclosure, at least one functional unit in a service module is configured to send a call request message to a gateway device through the application programming interface provided by the big data intelligence module when a call to the big data intelligence module is required. The call request message carries data to be processed. The gateway device is configured to receive the call request message, forward the data to be processed, and then send it to the big data intelligence module. The forwarding processing includes at least one of the following: data encryption, data decryption, routing forwarding, flow control, and load balancing. The big data intelligence module is configured to process the data packet to be processed, obtain the processing result, and return the processing result to the corresponding functional unit through the gateway device.

[0073] To ensure data security, when functional units in at least one service module communicate with the gateway device (e.g., a functional unit sends a call request message to the gateway device, and the gateway device returns a processing result to the functional unit), the transmitted data needs to be encrypted. Therefore, the receiving end needs to decrypt the received data to obtain it. The encryption and decryption algorithms are negotiated and determined by the sending and receiving ends; for example, they can be symmetric encryption algorithms, asymmetric encryption algorithms, hash algorithms, etc.

[0074] The gateway device forwards the received data to be forwarded through the routing table it maintains, and when there are multiple available transmission paths, it distributes the traffic evenly to different transmission paths to achieve traffic control and load balancing.

[0075] In practice, the private clusters (such as private cluster 1, private cluster 2, and private cluster 3) send application programming interface (API) requests via the HTTPS protocol. After receiving the API request, the gateway device can decrypt the data in the API request and route it to the corresponding big data intelligence module. After receiving the data, the corresponding big data intelligence module performs business processing based on the data through business layer services (charging safety protection, project calculation, etc.) and returns the processing results to the corresponding private cluster through the gateway device.

[0076] The private cluster is a service cluster for the charging operation system deployed at each charging station. In addition to encrypting, decrypting, and routing data, the gateway can also perform functions such as access control, traffic control, and load balancing for cluster access requests to prevent sudden traffic attacks. This ensures the high availability of the big data intelligent module as a whole and guarantees data security from multiple dimensions.

[0077] To enhance system security, anonymized data can be used for training the big data intelligence module (big data model). For example, when training the charging safety protection intelligent module, sensitive data such as order information and user information are avoided. Instead, only non-sensitive data such as voltage, current, maximum temperature, individual cell temperature difference, and individual cell pressure difference during the charging process are used. This avoids the need to obtain users' personal information when processing data using the big data intelligence module later, ensuring that the big data intelligence module will not use or leak user information. Therefore, when the big data intelligence module receives a data packet to be processed, it can utilize the pre-trained big data model to process the data packet and obtain the processing result.

[0078] This implementation method enables the deployment of big data intelligent modules in API mode, which rely on the accumulation of large amounts of data. This ensures the desensitization of sensitive data, the security of data transmission, and the control of data permissions, thereby improving the stability, efficiency, and security of the charging operation system.

[0079] Figure 4 This diagram illustrates the deployment of the charging extension service module of the charging operation system disclosed herein in a plug-in manner; such as Figure 4 As shown, this illustrates the process of deploying each functional unit of a charging extension service module, which includes at least one functional unit, in a plug-in manner. The process of the service module loading the implementation class of at least one functional unit through the factory pattern mechanism of the application framework includes: traversing the corresponding module configuration file to obtain the key-value information of at least one functional unit to be loaded, which is recorded in the module configuration file; obtaining the implementation class of at least one functional unit to be loaded based on the key-value information of at least one functional unit to be loaded; and loading the implementation class of at least one functional unit to be loaded through the factory pattern mechanism of the application framework.

[0080] For example, see Figure 4The charging extension service module provides functional units such as reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, orderly charging unit, user unit, role unit, and permission unit. Among these, the reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, and orderly charging unit can be loaded or unloaded as plug-in units as needed. For example, when private client 1 deploys a charging operation system, based on the configuration information in the unit configuration file, a charging operation system including the reconciliation unit, operation and maintenance unit, spare parts unit, points unit, and orderly charging unit can be deployed for private client 1's charging extension service. When deploying a charging operation system for private client 2, based on the configuration information in the unit configuration file, a charging operation system including the reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, and orderly charging unit can be deployed for private client 2, because private client 2 may have business needs for handling various promotional activities.

[0081] In other alternative implementations, basic units can be set in each service module. These basic units are essential functional units of the service module and cannot be dynamically loaded or unloaded, such as... Figure 4 The diagram illustrates the user unit, role unit, and permission unit within the charging extended service module.

[0082] In some optional implementations, the service module obtains the key-value information of at least one functional unit to be loaded by traversing the corresponding module configuration file. The module configuration file records the key-value information of the functional units to be loaded. Based on the key-value information of the at least one functional unit to be loaded, the implementation class of the at least one functional unit to be loaded is obtained. For example, for the spring.factories configuration file of the points unit, the points unit can be loaded into or unloaded from the charging extension service module as needed, providing an efficient way to expand and update the functions of the charging operation system.

[0083] In practice, the Spring Boot Spring Factories extension mechanism is used. The Spring FactoriesLoader class loader locates and loads each spring.factories file, parses the configuration line by line, and caches it in memory for subsequent calls.

[0084] This embodiment discloses an implementation method for deploying service modules in a plug-in manner. By using the factory pattern mechanism of the application framework, a flexible plug-in deployment method for each functional unit is realized. This flexible plug-in deployment method can support plug-in hot deployment, so dynamic updates and maintenance can be performed without stopping the operation of the charging operation system. The expansion of functions is more convenient and flexible, and the system downtime is reduced. It optimizes the functional expansion and resource utilization efficiency of each service module in the system, and further improves the scalability of the charging operation system.

[0085] Exemplary methods

[0086] Figure 5 This is a flowchart illustrating one embodiment of the charging operation system disclosed herein; the charging operation system can be applied to terminal devices (such as computer systems, servers, etc.). Figure 5 As shown, the charging operation system includes the following steps 501 to 502. Each step is explained below.

[0087] In step 501, the module configuration files corresponding to at least some of the service modules in at least one service module are traversed to obtain the key-value information of at least one functional unit to be loaded in each service module in at least some of the service modules. The module configuration file records the key-value information of the functional unit to be loaded.

[0088] In this disclosure, a charging operation system can be modularized using service configuration files to obtain at least one service module. The service configuration file records the service functions that the charging operation system can provide and the business resources required to support these services. The aforementioned modularization refers to decomposing the charging operation system into multiple independent service modules, enabling the independent development, testing, deployment, and maintenance of these service modules. Furthermore, by combining different service modules, a charging operation system that meets the needs of various charging stations can be quickly constructed, thereby improving the scalability and reusability of the charging operation system and providing a better user experience.

[0089] For example, when deploying a charging operation system for private customer 1, based on the service functions and business resources in the service configuration file, a charging operation system including a core charging service module, a charging extension service module, a device connection service module, and a background task service module can be deployed for charging station 1; when deploying a charging operation system for private customer 2, based on the service functions and business resources in the service configuration file, a charging operation system including a core charging service module, a charging extension service module, a device connection service module, a photovoltaic energy storage and charging service module, and a background task service module can be deployed for private customer 2, because private customer 2 may have installed or plan to install photovoltaic energy storage equipment, and therefore needs to deploy a photovoltaic energy storage and charging service module.

[0090] Each service module can include at least one functional unit, and the module configuration file corresponding to each service module can record the configuration information of the functional units that each service module of the charging operation system can provide. Based on the module configuration file corresponding to each service module, the functional units to be loaded for each service module can be obtained, and each service module can be implemented in a plug-in deployment architecture. The key-value information of the functional units to be loaded includes the interface and implementation class of the functional units to be loaded.

[0091] Understandably, each charging operation system can configure the functional units included in each service module according to its needs, and configure the functionality of the functional units into the corresponding service modules based on the corresponding JAR files. For each functional unit, the corresponding Java class files, metadata, and resource files are aggregated into a single file, resulting in a JAR file. Subsequently, when configuring the functional units included in each service module, this JAR file can be relied upon to load the functional unit in the Spring framework of the service module.

[0092] For example, see Figure 4 The charging extension service module provides functional units such as reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, orderly charging unit, user unit, role unit, and permission unit. Among these, the reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, and orderly charging unit can be loaded or unloaded as plug-in units as needed. For example, when private client 1 deploys a charging operation system, based on the configuration information in the unit configuration file, a charging operation system including the reconciliation unit, operation and maintenance unit, spare parts unit, points unit, and orderly charging unit can be deployed for private client 1's charging extension service. When deploying a charging operation system for private client 2, based on the configuration information in the unit configuration file, a charging operation system including the reconciliation unit, operation and maintenance unit, spare parts unit, marketing activity unit, points unit, and orderly charging unit can be deployed for private client 2, because private client 2 may have business needs for handling various promotional activities.

[0093] In other alternative implementations, basic units can be set in each service module. These basic units are essential functional units of the service module and cannot be dynamically loaded or unloaded, such as... Figure 4 The diagram illustrates the user unit, role unit, and permission unit within the charging extended service module.

[0094] In this example, the various services of the charging operation system can interact with each other through a preset communication method, which is at least one of the following: remote call method based on service interface, or publish-subscribe method based on message queue.

[0095] In practical implementation, for interactions between services requiring immediate responses, efficient Remote Procedure Calls (RPCs) can be achieved through the Dubbo interface. The Dubbo interfaces for each service module can be obtained from the system's service registry cluster.

[0096] For interactions between services where immediate response time is not particularly high, a distributed subscription approach using message queues can be used. Message queues are characterized by high performance, high reliability, and high throughput. Through the publish-subscribe model, they support the rapid storage and transmission of massive amounts of messages, making them suitable for scenarios such as real-time message processing, traffic shaping, and data synchronization.

[0097] In step 502, based on the key-value information of the functional unit to be loaded, the implementation class of the functional unit to be loaded is obtained, and through the decoupling extension mechanism, the implementation class of at least one functional unit to be loaded is dynamically loaded, so as to realize the integration of at least one functional unit to be loaded in the form of a plug-in.

[0098] In this example, the functional units within each service module can be implemented using the decoupled extension mechanism of Spring Boot Factories, thus achieving a plug-in deployment architecture. This allows for the dynamic combination and assembly of functional units within the service module, meeting the needs of different application scenarios and improving the scalability and maintainability of the system.

[0099] Spring Factories is implemented based on Java's ServiceLoader mechanism and the Spring framework's reflection and configuration loading capabilities. It uses the `spring.factories` file to achieve modular, pluggable automatic configuration loading. Specifically, service interfaces or abstract classes for each functional unit can be defined, and external modules can implement these interfaces or abstract classes, which are automatically wired into the service context when the service module starts. For example, certain autowiring classes (AutoConfiguration classes) perform autowiring under specified conditions. After defining the service interfaces or abstract classes for each functional unit, a `spring.factories` file can be included in the `META-INF` directory of each functional unit. The `spring.factories` file uses key-value pairs to map interfaces and implementation classes. Through the above definition and configuration, when the service module starts, the Spring framework scans and traverses the module configuration files corresponding to each service to obtain the functional units to be loaded, and automatically finds and loads the corresponding implementation classes based on the `spring.factories` files in all classpaths.

[0100] Through steps 501 and 502 above, at least one service module is deployed using a microservice architecture, with some service modules within that module integrating various functional units in a plug-in manner. Therefore, this disclosure improves the scalability of the charging operation system by deploying at least one service module on the client side using a microservice architecture. Furthermore, the plug-in mechanism enables flexible deployment of at least one functional unit included in each service module. Since the flexible plug-in deployment method supports hot deployment, the functions of the service modules can be dynamically updated and maintained without stopping the charging operation system. This makes functional expansion more convenient and flexible, reduces system downtime, optimizes the functional expansion and resource utilization efficiency of each service module in the system, and further enhances the scalability of the charging operation system.

[0101] Figure 6 This is a flowchart illustrating another embodiment of the functional implementation method of the charging operation system disclosed herein; this embodiment uses the example of how a functional unit in a service module deployed on a client side calls a big data intelligent module for illustrative purposes. Figure 6 As shown, the process includes steps 601 to 603. The following is a description of each step:

[0102] In step 601, at least one functional unit in the service module sends a call request message to the gateway device through the application programming interface provided by the big data intelligence module deployed on the server. The call request message carries data to be processed.

[0103] The big data intelligence module is used to direct intelligent units trained on a large amount of industry data. This module can include a big data model that outputs target data based on the business data of the charging operation system. For example, during vehicle charging, voltage and current data are input into the big data model, which can output charging safety protection data for the charging vehicle. Alternatively, when a charging merchant needs to deploy a new charging station, information such as the planned location, scale, and administrative region of the station is input into the big data model, which can output cost information for deploying the new charging station.

[0104] This implementation achieves API mode deployment of big data intelligent modules that rely on large amounts of accumulated data, ensuring the desensitization of sensitive data, the security of data transmission, and the control of data permissions, thereby improving the stability, efficiency, and security of the charging operation system.

[0105] In this disclosure, the big data intelligence module may also include complex big data algorithms to provide complex computing functions for the charging operation system.

[0106] In this embodiment, the big data intelligence module, which requires a large amount of industry data for training, is deployed on a cloud server in a centralized application programming interface (API) deployment mode. Thus, each privately deployed charging operation system transmits anonymized data to the system supplier's server through the API interface. The system supplier's server can call the big data intelligence module through the API interface to provide big data processing services for the privately deployed charging operation system.

[0107] In this embodiment, by independently deploying the big data intelligence module on a cloud server, a unified big data processing service, such as data analysis and intelligent prediction service, can be provided for each privately deployed charging operation system, ensuring that the charging operation system has good real-time performance, flexibility, efficiency and security.

[0108] In step 602, after receiving the call request message, the gateway device forwards the data to be processed and sends it to the big data intelligence module. The forwarding process includes at least one of the following: data encryption, data decryption, routing forwarding, traffic control, and load balancing.

[0109] To ensure data security, when functional units in at least one service module communicate with the gateway device (e.g., a functional unit sends a call request message to the gateway device, and the gateway device returns a processing result to the functional unit), the transmitted data needs to be encrypted. Therefore, the receiving end needs to decrypt the received data to obtain it. The encryption and decryption algorithms are negotiated and determined by the sending and receiving ends; for example, they can be symmetric encryption algorithms, asymmetric encryption algorithms, hash algorithms, etc.

[0110] The gateway device forwards the received data to be forwarded through the routing table it maintains, and when there are multiple available transmission paths, it distributes the traffic evenly to different transmission paths to achieve traffic control and load balancing.

[0111] In step 603, the big data intelligence module processes the data to be processed, obtains the processing result, and returns the processing result to the corresponding functional unit through the gateway device.

[0112] The big data intelligence module can include a big data model that can output processing results based on the data to be processed from the charging operation system. For example, during vehicle charging, data such as voltage and current are input into the big data model, which can output charging safety protection data for the charging vehicle; or when a charging merchant needs to deploy a new charging station, information such as the planned geographical location, scale, and administrative region of the station is input into the big data model, which can output cost information for deploying the new charging station.

[0113] Through steps 601 to 603 above, by deploying the big data intelligence module on the cloud server in a centralized application programming interface manner, a unified big data processing service can be provided for each privately deployed charging operation system, ensuring that the charging operation system has good real-time performance, flexibility, efficiency and security. Moreover, each privately deployed charging operation system does not need to additionally train the big data model and redeploy the computing resources of the big data intelligence module locally, saving the deployment cost of the charging operation system.

[0114] Exemplary electronic devices, computer program products, and computer-readable storage media

[0115] Below, for reference Figure 7 This describes an electronic device according to embodiments of the present disclosure, wherein apparatus for implementing methods according to embodiments of the present disclosure may be integrated. Figure 7 This is a structural diagram of an electronic device provided in an illustrative embodiment of the present disclosure, such as... Figure 7 As shown, the electronic device includes one or more processors 71, one or more memory 72s of computer-readable storage media, and a computer program stored in the memory and executable on the processor. When the program in the memory 72 is executed, the functional implementation method of the charging operation system described above can be implemented.

[0116] Specifically, in practical applications, the electronic device may also include components such as an input device 73 and an output device 74, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown). Those skilled in the art will understand that... Figure 7 The structure of the electronic device shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or certain components, or different component arrangements.

[0117] in:

[0118] The processor 71 may be a central processing unit (CPU) or other form of processing unit with charging operation system capability and / or instruction execution capability. It performs various functions and processes data by running or executing software programs and / or modules stored in memory 72 and calling data stored in memory 72, thereby performing overall monitoring of the electronic device.

[0119] The memory 72 can store one or more computer program products. The memory can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program products can be stored on the computer-readable storage medium, and the processor 71 can run the computer program products to implement the functional implementation methods of the charging operation system of the various embodiments of this disclosure described above, and / or other desired functions.

[0120] The input device 73 can be used to receive input numerical or character information. The input device 73 may include a keyboard, mouse, joystick, etc., related to user settings and function control.

[0121] The output device 74 can output various information to the outside, including determined distance information, direction information, etc. The output device 74 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0122] Electronic devices may also include a power supply for powering various components, which can be logically connected to the processor 71 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. The power supply may also include one or more DC or AC power sources, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and any other components.

[0123] Of course, for the sake of simplicity, Figure 7 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0124] In addition to the methods and apparatus described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the charging operation system according to various embodiments of this disclosure as described in the "Exemplary Methods" section of this specification.

[0125] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0126] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the charging operation system according to various embodiments of this disclosure as described in the "Exemplary Methods" section above.

[0127] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0129] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0130] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0131] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the method is for illustrative purposes only, and the steps of the method of this disclosure are not limited to the order specifically described above, unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the method according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the method according to this disclosure.

[0132] The description in this disclosure is provided for illustrative and descriptive purposes only and is not intended to be exhaustive or to limit the disclosure to its forms. Many modifications and variations will be apparent to those skilled in the art. The embodiments were chosen and described in order to better illustrate the principles and practical application of this disclosure and to enable those skilled in the art to understand this disclosure and to design various embodiments with various modifications suitable for a particular purpose.

Claims

1. A charging operation system, comprising: At least one service module deployed on the client in a microservice architecture; The service modules in the at least one service module interact with each other through a preset communication method, which is at least one of the following: a remote call method based on a service interface, or a publish-subscribe method based on a message queue; Each of the at least one service module includes at least one functional unit; At least some of the service modules are configured to dynamically load the implementation classes of the at least one functional unit through a plug-in mechanism, thereby integrating the at least one functional unit in a plug-in manner.

2. The system according to claim 1, further comprising: At least one big data intelligence module deployed on a cloud server; The at least one big data intelligence module is configured to provide data computing services to some functional units in the at least one service module through an application programming interface.

3. The system according to claim 2, further comprising: Gateway device; Some functional units in the at least one service module are configured to send a call request message to the gateway device through the application programming interface provided by the big data intelligence module when the big data intelligence module needs to be called; the call request message carries data to be processed. The gateway device is configured to receive the call request message, forward the data to be processed, and then send it to the big data intelligent module. The forwarding process includes at least one of the following: data encryption, data decryption, routing forwarding, traffic control, and load balancing. The big data intelligent module is configured to process the data to be processed, obtain the processing result, and return the processing result to the corresponding functional unit through the gateway device.

4. The system according to claim 3, wherein the big data intelligence module includes a pre-trained big data model; The process of processing the data to be processed to obtain the processing result includes: The pre-trained big data model is used to process the data to be processed to obtain the processing result.

5. The system according to any one of claims 1-4, wherein dynamically loading the implementation class of the at least one functional unit through a plug-in mechanism includes: Traverse the corresponding module configuration files to obtain key-value information of at least one functional unit to be loaded, wherein the module configuration files record the key-value information of the functional units to be loaded. Based on the key-value information of the at least one functional unit to be loaded, obtain the implementation class of the at least one functional unit to be loaded; The implementation class of at least one functional unit to be loaded is dynamically loaded through a decoupling extension mechanism.

6. The system according to any one of claims 1-5, wherein the at least one service module is obtained by modularizing the system based on the system's service configuration file.

7. The system according to any one of claims 1-6, wherein the at least one service module includes at least a charging core service module, a device connection service module, and at least one of the following service modules: a charging extension service module, a photovoltaic energy storage and charging service module, a background task service module, and an administrative docking service module; The charging core service module is used to provide charging services to vehicles through the power grid; The charging extension service module is used to provide additional services to the core charging service; The device connection service module is used to provide connection services with the charging pile equipment; The photovoltaic-storage-charging service module is used to provide charging services for vehicles through photovoltaic storage equipment; The background task service module is used to periodically complete the background tasks of the system. The administrative docking service module is used to provide docking services with the preset platform.

8. A method for implementing the functions of a charging operation system, wherein the charging operation system is the system described in any one of claims 1-7, the method comprising: Traverse the module configuration files corresponding to at least some of the service modules in at least one service module to obtain the key-value information of at least one functional unit to be loaded in each of the at least some service modules, wherein the module configuration file records the key-value information of the functional unit to be loaded. Based on the key-value information of the functional unit to be loaded, the implementation class of the functional unit to be loaded is obtained, and the implementation class of at least one functional unit to be loaded is dynamically loaded through a decoupling extension mechanism, so as to integrate at least one functional unit to be loaded in a plug-in form.

9. The method according to claim 8, further comprising: Some functional units in the at least one service module send call request messages to the gateway device through the application programming interface provided by the big data intelligent module deployed on the server, and the call request messages carry data to be processed. After receiving the call request message, the gateway device forwards the data to be processed and then sends it to the big data intelligent module. The forwarding process includes at least one of the following: data encryption, data decryption, routing forwarding, traffic control, and load balancing. The big data intelligent module processes the data to be processed, obtains the processing result, and returns the processing result to the corresponding functional unit through the gateway device.

10. The method according to claim 9, wherein the big data intelligence module includes a pre-trained big data model; The big data intelligence module processes the data to be processed to obtain the processing results, including: The big data intelligence module uses the pre-trained big data model to process the data to be processed and obtain the processing result.

11. A computer-readable storage medium storing computer program instructions that, when executed, implement the method described in any one of claims 8-10.

12. An electronic device, the electronic device comprising: Memory, used to store computer program products; A processor for executing a computer program product stored in the memory, wherein when the computer program product is executed, it implements the method described in any one of claims 8-10.

13. A computer program product comprising computer program instructions, which, when executed by a processor, implement the method described in any one of claims 8-10.

Images