Charging method, device and system for electric vehicle

Abstract

The invention discloses a charging method, device and system for an electric vehicle. The method comprises the following steps: receiving a charging request corresponding to a charging pile system; in response to the charging request, determining a target charging structure corresponding to the charging equipment according to the charging interface identifier; determining a target allocation strategy and a target resource parameter corresponding to the target charging structure; determining a to-be-called target charging module from charging modules corresponding to the target charging structure according to a target allocation strategy and the target resource parameters, and determining target charging parameters corresponding to the target charging module; and the charging instruction is sent to the corresponding control unit, so that the corresponding control unit is controlled to use the corresponding target charging module, and the electric vehicle is charged according to the corresponding target charging parameters. According to the invention, the technical problem of poor compatibility due to the fact that a single topological structure is usually used in a charging system in the related technology is solved.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging, and more specifically, to a charging method, apparatus, and system for electric vehicles. Background Technology

[0002] With the rapid development of the electric vehicle industry, the hardware topology of charging equipment is showing a trend of diversification. Currently, mainstream charging pile systems include multiple topologies. However, charging systems are usually developed for a single topology. Developing a separate hardware topology requires developing an independent software system, which results in a long development cycle, low code reusability, and poor compatibility.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This invention provides a charging method, apparatus, and system for electric vehicles, which at least solves the technical problem of poor compatibility in charging systems that typically use a single topology.

[0005] According to one aspect of the present invention, a charging method for an electric vehicle is provided, comprising: receiving a charging request corresponding to a charging pile system, wherein the charging request is in response to the generation of a charging gun signal, the charging gun signal being triggered based on a target operation, the target operation including the operation of inserting a charging gun into an electric vehicle charging interface, the charging request carrying a charging interface identifier, the charging interface identifier being used to identify a charging structure of a charging device, the charging structure including one of the following: an integrated topology, a distributed topology, and a shared topology, wherein the integrated topology is used to fixally control multiple first charging modules through a first control unit, the distributed topology is used to dynamically control multiple second charging modules through a second control unit, and the shared topology is used to share control of multiple third charging modules through multiple third control units; in response to the charging request, determining a target charging structure corresponding to the charging device based on the charging interface identifier; and determining a target allocation strategy and target resource parameters corresponding to the target charging structure. The target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. Based on the target allocation strategy and the target resource parameters, a target charging module to be called is determined from the charging modules corresponding to the target charging structure, and a target charging parameter corresponding to the target charging module is determined. A charging command is sent to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameter. The charging command carries the identifier corresponding to the target charging module and the target charging parameter.

[0006] Optionally, based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, including: when the target charging structure is the shared topology, retrieving the target optimization function corresponding to the global multi-objective optimization strategy, wherein the target optimization function aims to have a joint target index corresponding to a predetermined threshold greater than a certain threshold, and the joint target index includes a charging efficiency index, a charging waiting time index, and a continuous idle degree index of the remaining charging modules after allocation; solving the target optimization function based on the target resource parameters in the global resource pool to obtain multiple global charging module combinations, wherein the multiple global charging module combinations include cross-control unit charging module combinations; sending cross-control unit resource locking requests corresponding to the multiple global charging module combinations to the corresponding control units, and receiving locking feedback results corresponding to the multiple global charging module combinations; determining the global charging module combination whose corresponding locking feedback result is successfully locked and whose corresponding joint target index is the highest as the target charging module.

[0007] Optionally, based on the target allocation strategy and the target resource parameters, determining the target charging module to be invoked from the charging modules corresponding to the target charging structure includes: when the target charging structure is the distributed topology, retrieving the local arbitration rule set corresponding to the local dynamic arbitration strategy, wherein the local arbitration rule set includes power redundancy arbitration rules and comprehensive quantitative index arbitration rules, the power redundancy arbitration rules include filtering out charging module combinations whose corresponding total power is greater than the target sum, the target sum being the sum of the requested power and the predetermined redundancy power, and the comprehensive quantitative index arbitration rules include rules for comprehensive arbitration based on multiple quantitative index items, the multiple quantitative index items being... The quantitative indicators include: module health indicators, module load balancing indicators, module historical scheduling indicators, and module response speed indicators. Based on the power redundancy arbitration rules and the target resource parameters corresponding to the local resource pool, power redundancy arbitration is performed to obtain multiple local charging module combinations, wherein the target resource parameters include power redundancy parameters. Under the comprehensive quantitative indicator arbitration rules, the comprehensive quantitative index corresponding to each of the multiple local charging module combinations is determined, wherein the corresponding comprehensive quantitative index is obtained based on the sub-quantitative indices corresponding to each of the multiple quantitative indicators. Based on the multiple comprehensive quantitative indices, the target charging module is determined from the multiple local charging module combinations.

[0008] Optionally, based on the target allocation strategy and the target resource parameters, determining the target charging module to be invoked from the charging modules corresponding to the target charging structure includes: when the target charging structure is the integrated topology, retrieving the target mapping relationship corresponding to the fixed mapping allocation strategy, wherein the target mapping relationship includes the mapping matching relationship between the charging gun and the charging module; determining the charging gun identifier corresponding to the plug-in signal; and determining the fixed charging module matching the charging gun identifier as the target charging module based on the target mapping relationship.

[0009] Optionally, sending a charging command to the corresponding control unit includes: when there are multiple target charging modules, controlling the corresponding control unit to send a parallel control command to the multiple target charging modules so that the multiple target charging modules form a parallel structure; receiving parallel feedback information corresponding to the parallel control command; and when the parallel feedback information indicates that the multiple target charging modules have formed the parallel structure, sending the charging command to the corresponding control unit.

[0010] Optionally, based on the target allocation strategy and the target resource parameters, a target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and target charging parameters corresponding to the target charging module are determined. This includes: if the charging request also carries user demand parameters and electric vehicle status parameters, obtaining the user demand parameters and the electric vehicle status parameters; and based on the target allocation strategy, the target resource parameters, the user demand parameters, and the electric vehicle status parameters, determining the target charging module to be invoked from the charging modules corresponding to the target charging structure, and determining target charging parameters corresponding to the target charging module.

[0011] According to one aspect of the present invention, a charging system for an electric vehicle is provided, comprising: a sensing layer, a communication layer, an application layer, a resource management layer, and a control layer, wherein the sensing layer is used to trigger a charging gun signal based on a target operation, wherein the target operation includes the operation of inserting a charging gun into an electric vehicle charging interface; the communication layer is used to receive a charging request corresponding to a charging pile system, wherein the charging request is in response to the generation of the charging gun signal, the charging request carries a charging interface identifier, the charging interface identifier being used to identify the charging structure of the charging device, the charging structure including one of the following: an integrated topology, a distributed topology, and a shared topology, wherein the integrated topology is used to fix and control multiple first charging modules through a first control unit, the distributed topology is used to dynamically control multiple second charging modules through a second control unit, and the shared topology is used to share and control multiple third charging modules through multiple third control units; the application layer is used to, in response to the charging request, determine a target charging structure corresponding to the charging device based on the charging interface identifier; and determine a target allocation strategy corresponding to the target charging structure. In this context, the target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology; the resource management layer is used to determine the target resource parameters corresponding to the target charging structure, wherein the target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology; based on the target allocation strategy and the target resource parameters, a target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined; the communication layer is used to send a charging command to the corresponding control unit, wherein the charging command carries the identifier corresponding to the target charging module and the target charging parameters; the control layer is used to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters.

[0012] According to one aspect of the present invention, a charging device for an electric vehicle is provided, comprising: a receiving module, configured to receive a charging request corresponding to a charging pile system, wherein the charging request is in response to the generation of a plug-in signal, the plug-in signal being triggered based on a target operation, the target operation including the operation of inserting a charging gun into an electric vehicle charging interface, the charging request carrying a charging interface identifier, the charging interface identifier being used to identify a charging structure of the charging device, the charging structure including one of the following: an integrated topology, a distributed topology, and a shared topology, wherein the integrated topology is used to fix and control multiple first charging modules through a first control unit, the distributed topology is used to dynamically control multiple second charging modules through a second control unit, and the shared topology is used to share and control multiple third charging modules through multiple third control units; a first determining module, configured to determine a target charging structure corresponding to the charging device based on the charging interface identifier in response to the charging request; and a second determining module, configured to determine a target allocation strategy corresponding to the target charging structure and The target resource parameters include the following: the target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology; the target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology; a third determining module is used to determine the target charging module to be called from the charging modules corresponding to the target charging structure according to the target allocation strategy and the target resource parameters, and to determine the target charging parameters corresponding to the target charging module; a sending module is used to send a charging command to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters, wherein the charging command carries the identifier corresponding to the target charging module and the target charging parameters.

[0013] According to one aspect of the present invention, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement a charging method for an electric vehicle as described above.

[0014] According to one aspect of the present invention, a computer-readable storage medium is provided, wherein when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform a charging method for an electric vehicle as described above.

[0015] In this embodiment of the invention, a charging request corresponding to a charging pile system is received. The charging request is responded to by a plug-in signal, which is triggered based on a target operation. The target operation includes the insertion of a charging gun into an electric vehicle charging interface. The charging request carries a charging interface identifier, which identifies the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, or a shared topology. An integrated topology is used to fix and control multiple first charging modules through a first control unit; a distributed topology is used to dynamically control multiple second charging modules through a second control unit; and a shared topology is used to share and control multiple third charging modules through multiple third control units. In response to the charging request, a target charging structure corresponding to the charging device is determined based on the charging interface identifier. A target allocation strategy and target resource parameters corresponding to the target charging structure are determined, wherein the target allocation strategy and target resource parameters are... The allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. Based on the target allocation strategy and the target resource parameters, the target charging module to be called is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined. A charging command is sent to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module and charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier of the target charging module and the target charging parameters. By receiving charging requests carrying charging interface identifiers to identify the target charging structure, calling the corresponding target allocation strategy and target resource parameters according to the target charging structure, determining the target charging module and charging parameters based on the strategy and parameters, and finally controlling the charging execution by sending instructions carrying module identifiers and charging parameters, the core objective of using a single software system to adapt to multiple hardware topologies, achieve unified resource scheduling and business logic reuse is achieved. This results in significantly improving code reusability, significantly shortening the development cycle of new topologies, and effectively reducing maintenance costs. In turn, it solves the technical problem of poor compatibility in charging systems that typically use a single topology. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0017] Figure 1This is a flowchart of a charging method for an electric vehicle according to an embodiment of the present invention;

[0018] Figure 2 This is a seven-layer hierarchical abstract architecture diagram of an optional embodiment of the present invention;

[0019] Figure 3 This is a schematic diagram illustrating the adaptation of the software abstraction method of the optional embodiments of the present invention under various topologies;

[0020] Figure 4 This is a structural block diagram of a charging device for an electric vehicle according to an embodiment of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0023] Example 1

[0024] According to an embodiment of the present invention, an embodiment of a charging method for an electric vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0025] Figure 1 This is a flowchart of a charging method for an electric vehicle according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0026] Step S102: Receive a charging request corresponding to the charging pile system. The charging request is in response to the generation of a plug-in signal. The plug-in signal is triggered based on a target operation, which includes the operation of inserting the charging gun into the electric vehicle charging interface. The charging request carries a charging interface identifier, which is used to identify the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, or a shared topology. The integrated topology is used to fix and control multiple first charging modules through a first control unit. The distributed topology is used to dynamically control multiple second charging modules through a second control unit. The shared topology is used to share and control multiple third charging modules through multiple third control units.

[0027] In step S102 of this application, a charging request generated by the charging pile system is received. This request is triggered by a plug-in signal, which is generated by the operation of inserting the charging gun into the charging interface of the electric vehicle. The charging interface identifier carried in the charging request is used to uniquely identify the hardware topology type of the charging device, thereby providing input basis for subsequent adaptive processing of charging processes with different topologies.

[0028] This involves the insertion signal, which is an electrical or digital signal generated when the charging gun is inserted into the charging interface of an electric vehicle. It is used to sense the connection status of the charging device and trigger the generation and processing of subsequent charging requests.

[0029] This involves the charging interface identifier, a unique identifier embedded in the charging request. It is used to distinguish the hardware topology type of the charging device, such as integrated, distributed, or shared, and is a key parameter for the system to adaptively select subsequent processing strategies.

[0030] This involves the charging structure, which refers to the hardware topology organization of the charging equipment. It can include integrated topology, distributed topology, and shared topology. Each structure corresponds to a different mapping relationship between the control unit and the charging module, affecting resource allocation and charging strategy.

[0031] This involves an integrated topology structure, which is a hardware topology form. Multiple first charging modules are fixedly controlled by a first control unit. It can be used in all-in-one devices. The charging gun and the charging modules have a fixed mapping relationship. The structure is simple but has low flexibility.

[0032] This involves a distributed topology, a hardware topology that dynamically controls multiple second charging modules through a second control unit. It can be used in split-type devices, supports on-demand dynamic allocation of charging modules, and improves resource utilization.

[0033] This involves a shared topology, a hardware topology that allows multiple third-level control units to share control of multiple third-level charging modules. It can be used in complex systems such as charging islands and supports global resource optimization and sharing across control units.

[0034] This step clearly identifies the charging request and the charging structure type, laying the foundation for subsequent adaptive selection of the target charging structure, allocation strategy, and resource parameters. It avoids processing errors caused by topology incompatibility, ensuring that the charging system can uniformly respond to the charging needs of various hardware topologies, thereby improving the system's compatibility and adaptability.

[0035] Step S104: In response to the charging request, determine the target charging structure corresponding to the charging device based on the charging interface identifier;

[0036] In step S104 provided in this application, the system responds to the received charging request, and by parsing the charging interface identifier carried in the charging request, it matches it with the predefined topology type, thereby uniquely determining the specific hardware topology structure adopted by the current charging device, i.e., the target charging structure.

[0037] This involves a target charging structure, which is a hardware topology type of charging equipment determined by the charging interface identifier. It can include an integrated topology, a distributed topology, or a shared topology. The integrated topology uses a first control unit to fix and control multiple first charging modules, the distributed topology uses a second control unit to dynamically control multiple second charging modules, and the shared topology uses multiple third control units to share and control multiple third charging modules.

[0038] Through this step, the system accurately identifies the topology type of the charging device by the charging interface identifier, providing key input for the subsequent selection of matching allocation strategies and resource parameters. This enables automatic adaptation to different hardware topologies, avoiding compatibility errors and resource allocation failures caused by topology misidentification in traditional solutions. It ensures unified management and efficient scheduling of multi-topology charging systems from the source, improving the system's generalization ability and deployment flexibility.

[0039] Step S106: Determine the target allocation strategy and target resource parameters corresponding to the target charging structure. The target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology.

[0040] In step S106 provided in this application, the system selects and determines the target allocation strategy and target resource parameters that are precisely matched with the target charging structure determined in step S104 from the predefined strategy library and parameter set, so as to guide the subsequent calling and parameter configuration of the charging module.

[0041] This involves target allocation strategies, which are resource allocation methods designed for different charging topologies. These strategies can include: a fixed mapping allocation strategy for integrated topologies, which uses a first control unit to control multiple first charging modules and achieve a static one-to-one mapping between charging guns and charging modules; a local dynamic arbitration strategy for distributed topologies, which uses a second control unit to dynamically control multiple second charging modules and allocates resources based on a real-time arbitration module using local rules; and a global multi-objective optimization strategy for shared topologies, which uses multiple third control units to share control of multiple third charging modules and optimizes resource allocation across units. These strategies are based on predefined topology characteristics to ensure that resource allocation is consistent with the hardware architecture.

[0042] This involves target resource parameters, which are a set of parameters describing the resource status and availability of charging modules. These parameters can include resource parameters of integrated charging module groups (describing the static attributes of fixed charging module groups under integrated topology), resource parameters of local resource pools (describing the dynamic resource pool status managed by local control units under distributed topology), and resource parameters of global resource pools (describing the global resource status shared by all control units under shared topology). These parameters reflect resource availability in real time and provide a data basis for allocation decisions.

[0043] Through this step, the system automatically matches the optimal allocation strategy and resource parameters to the target charging structure, realizing adaptive resource management for different hardware topologies. This avoids the compatibility limitations of a single topology strategy, improves the flexibility and resource utilization of the charging system, and ensures the efficiency and reliability of charging module calls by accurately matching strategies and parameters. It also reduces allocation errors or resource conflicts caused by unsuitable strategies, solves the multi-topology compatibility problem, and supports rapid deployment and expansion.

[0044] Step S108: Based on the target allocation strategy and target resource parameters, determine the target charging module to be called from the charging modules corresponding to the target charging structure, and determine the target charging parameters corresponding to the target charging module.

[0045] In step S108 provided in this application, the system executes the core resource allocation logic. By calling the target allocation strategy determined in step S106 and comprehensively analyzing the target resource parameters corresponding to the target charging structure, the system decides and selects one or more target charging modules that are most suitable for the current charging request from the set of available charging modules. At the same time, the system calculates the target charging parameters that match the module based on the module characteristics and charging requirements.

[0046] This involves target charging modules, which are specific modules or combinations of modules selected from the charging module resources of the corresponding topology based on the target allocation strategy and target resource parameters, and are to perform the current charging task. The selection process strictly follows the rules of the corresponding strategy. In the integrated topology, fixed modules are selected based on fixed mapping relationships. In the distributed topology, modules are dynamically selected from the local resource pool through a local arbitration rule set. In the shared topology, the optimal combination of modules across control units is selected from the global resource pool by solving a global multi-objective optimization function.

[0047] This involves target charging parameters, which are specific operating parameters configured for a given target charging module to perform the current charging task. These parameters include at least the output voltage, output current, charging power, and their control logic. The establishment of these parameters requires comprehensive consideration of the target charging module's own capabilities, the system status reflected by the target resource parameters, and the user needs or vehicle status that may be carried in the charging request, in order to ensure the safety, efficiency, and compliance of the charging process.

[0048] Through this step, the system achieves precise and dynamic scheduling and parameter optimization of charging hardware resources, transforming abstract allocation strategies and resource status data into specific execution instructions. It adopts differentiated optimal decision-making mechanisms for different topologies, ensuring the efficiency and rationality of resource allocation in various scenarios, from simple fixed mapping to complex global sharing. It achieves seamless compatibility with multiple topologies, improves the overall resource utilization, response speed, and service quality of the charging system, and solves the technical problems of poor compatibility and rigid resource scheduling in single-topology systems.

[0049] Step S110: Send a charging command to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module and charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier of the target charging module and the target charging parameters.

[0050] In step S110 provided in this application, the system generates a specific charging execution instruction and sends the instruction to the control unit responsible for managing the target charging module. The instruction clearly specifies the unique identifier of the target charging module to be activated and the target charging parameters set for the module, thereby driving the control unit to precisely control the target charging module to start and execute the charging process for the electric vehicle according to the predetermined parameters.

[0051] This involves a control unit, which is a hardware controller in the charging device that directly manages one or more charging modules. It is responsible for receiving and executing charging commands issued by the upper-level system, and specifically implements low-level control functions such as starting and stopping the charging modules and adjusting the power.

[0052] This involves identification, which is a code or identifier used to uniquely distinguish different charging modules. It exists in the charging instructions to ensure that the control unit can accurately identify and locate the specific physical module that needs to be controlled.

[0053] Through this step, the system completes a closed loop from resource decision-making to physical execution. The determined optimal allocation scheme and parameter settings are reliably transmitted to the underlying hardware execution unit via a standardized command interface. This ensures unambiguous transmission and execution on the physical hardware, completing the final transformation from an abstract model to concrete charging behavior. Simultaneously, precise module identification ensures that electrical energy is delivered to the correct physical channel, achieving accurate delivery of charging energy. This improves the overall response efficiency and reliability of the system.

[0054] Through steps S102-S110 above, a charging request corresponding to the charging pile system is received. The charging request is responded to by a plug-in signal, which is triggered by a target operation. The target operation includes inserting the charging gun into the electric vehicle's charging interface. The charging request carries a charging interface identifier, which identifies the charging structure of the charging equipment. The charging structure includes one of the following: an integrated topology, a distributed topology, or a shared topology. An integrated topology is used to fix and control multiple first charging modules through a first control unit; a distributed topology is used to dynamically control multiple second charging modules through a second control unit; and a shared topology is used to share and control multiple third charging modules through multiple third control units. In response to the charging request, a target charging structure corresponding to the charging equipment is determined based on the charging interface identifier. A target allocation strategy and target resource parameters corresponding to the target charging structure are then determined. The target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. Based on the target allocation strategy and the target resource parameters, the target charging module to be called is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined. A charging command is sent to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module and charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier of the target charging module and the target charging parameters. By receiving charging requests carrying charging interface identifiers to identify the target charging structure, calling the corresponding target allocation strategy and target resource parameters according to the target charging structure, determining the target charging module and charging parameters based on the strategy and parameters, and finally controlling the charging execution by sending instructions carrying module identifiers and charging parameters, the core objective of using a single software system to adapt to multiple hardware topologies, achieve unified resource scheduling and business logic reuse is achieved. This results in significantly improving code reusability, significantly shortening the development cycle of new topologies, and effectively reducing maintenance costs. In turn, it solves the technical problem of poor compatibility in charging systems that typically use a single topology.

[0055] As an optional embodiment, based on the target allocation strategy and target resource parameters, the target charging module to be called is determined from the charging modules corresponding to the target charging structure. This includes: when the target charging structure is a shared topology, retrieving the target optimization function corresponding to the global multi-objective optimization strategy, wherein the target optimization function aims to have a joint target index corresponding to a predetermined threshold greater than a predetermined threshold, and the joint target index includes a charging efficiency index, a charging waiting time index, and a continuous idle degree index of the remaining charging modules after allocation; solving the target optimization function based on the target resource parameters in the global resource pool to obtain multiple global charging module combinations, wherein the multiple global charging module combinations include cross-control unit charging module combinations; sending cross-control unit resource locking requests corresponding to the multiple global charging module combinations to the corresponding control units, and receiving locking feedback results corresponding to the multiple global charging module combinations; and determining the global charging module combination whose corresponding locking feedback result is successfully locked and whose corresponding joint target index is the highest as the target charging module.

[0056] This embodiment illustrates the specific process of determining the target charging module using a global multi-objective optimization strategy under a shared topology.

[0057] This involves a global multi-objective optimization strategy, which is a resource allocation strategy specifically designed for shared topologies. Its core is to use a function that comprehensively considers multiple system-level optimization objectives to make decisions, aiming to achieve optimal global resource allocation across control units, rather than local optima.

[0058] This involves an objective optimization function, which is a mathematical expression of a global multi-objective optimization strategy. Its inputs are the system resource status and charging requests, and its outputs are the evaluation values ​​of different combinations of charging modules. The function aims to maximize or minimize a joint objective index composed of multiple indicators.

[0059] This involves the joint target index, which is the output value of the target optimization function. It is a comprehensive quantitative indicator that can be calculated from multiple joint indicator items according to predetermined weights or rules, and is used to comprehensively evaluate the merits of a charging module combination.

[0060] This involves joint indicator items, which are the sub-indicators that constitute the joint target index. These can include charging efficiency indicators, charging waiting time indicators, and the continuous idle time of remaining charging modules after allocation, which together determine the system performance of resource allocation.

[0061] This includes a charging efficiency metric, which is one of the joint metrics used to measure the efficiency of resource allocation. It tends to satisfy power requests with the fewest possible modules, reserving more modules for subsequent requests, thereby improving the overall system throughput.

[0062] This includes a charging waiting time indicator, which is one of the joint indicators used to ensure the fairness of the allocation and to avoid excessively long charging times by measuring the waiting time during charging.

[0063] This involves a predetermined threshold, which is a pass / fail line set for the joint target index, used to initially screen candidate charging module combinations that meet the basic performance requirements.

[0064] This involves a global resource pool, which is a logical set that manages and schedules all charging modules in a unified manner under a shared topology. It contains all available charging module resources across multiple controllers.

[0065] This involves a global charging module combination, which is a series of feasible module allocation schemes obtained by solving the objective optimization function. Each combination contains a set of charging modules selected to serve the current charging request. These modules may come from different control units.

[0066] This involves cross-control unit charging module combinations, which are a special case of global charging module combinations. They refer to combinations in which the charging modules belong to two or more different control units, reflecting the core characteristics of a shared topology.

[0067] This includes the lock feedback result, which is the control unit's response to the resource lock request, indicating whether the designated charging module under its jurisdiction has been successfully locked.

[0068] In this step, firstly, after identifying the target charging structure as a shared topology, the system invokes a pre-defined global multi-objective optimization strategy and its corresponding objective optimization function. Then, based on the real-time status of the global resource pool (target resource parameters) as input, the optimization function is run to generate multiple candidate global charging module combinations containing cross-control unit modules and their corresponding joint objective indices. Next, the system concurrently sends resource locking requests to all control units involved in these candidate combinations and collects their respective locking feedback results. Finally, from the candidate combinations where all modules are successfully locked, the system selects the one with the highest joint objective index and ultimately determines it as the target charging module serving this charging request.

[0069] This approach achieves system-level global optimization in complex shared topologies. Through a multi-objective decision function (comprehensively considering efficiency, waiting time, and resource fragmentation), it ensures that the resource allocation scheme achieves global optimum across control units, rather than local optimum under a single controller, while meeting basic performance requirements (predetermined thresholds). This significantly improves overall resource utilization and system throughput in complex charging scenarios. By concurrently sending cross-control unit resource locking requests and making decisions based on feedback, it effectively solves the problems of resource contention and conflict in multi-controller environments. This ensures the feasibility of immediately deploying the selected optimal module combination after decision-making, avoiding allocation failures due to unexpected resource occupation, and improving scheduling success rate and system reliability. This mechanism combines complex multi-objective optimization with actual resource availability verification, enabling efficient and reliable handling of even the most complex topologies such as charging islands.

[0070] As an optional embodiment, based on the target allocation strategy and target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure. This includes: when the target charging structure is a distributed topology, retrieving the local arbitration rule set corresponding to the local dynamic arbitration strategy. The local arbitration rule set includes power redundancy arbitration rules and comprehensive quantitative index arbitration rules. The power redundancy arbitration rules include selecting charging module combinations whose total power is greater than the target sum, where the target sum is the sum of the requested power and the predetermined redundant power. The comprehensive quantitative index arbitration rules include rules for comprehensive arbitration based on multiple quantitative index items. The quantitative indicators include: module health indicator, module load balancing indicator, module historical scheduling indicator, and module response speed indicator. Based on the power redundancy arbitration rules and the target resource parameters corresponding to the local resource pool, power redundancy arbitration is performed to obtain multiple local charging module combinations. The target resource parameters include power redundancy parameters. Under the comprehensive quantitative indicator arbitration rules, the comprehensive quantitative index corresponding to each of the multiple local charging module combinations is determined. The corresponding comprehensive quantitative index is obtained based on the sub-quantitative indices corresponding to each of the multiple quantitative indicators. Based on the multiple comprehensive quantitative indices, the target charging module is determined from the multiple local charging module combinations.

[0071] This embodiment illustrates the specific process of determining the target charging module through a local dynamic arbitration strategy in a distributed topology.

[0072] This involves a local dynamic arbitration strategy, which is a resource allocation strategy designed specifically for distributed topologies. It can be defined by a local arbitration rule set. Its core is to dynamically select the optimal combination of charging modules within the local resource pool of a single controller through a two-stage arbitration mechanism (power redundancy arbitration and comprehensive quantitative index arbitration).

[0073] This involves a local arbitration rule set, which is a set of specific rules for local dynamic arbitration strategies. It may include power redundancy arbitration rules and comprehensive quantitative index arbitration rules, which together guide the decision-making process of selecting and evaluating candidate charging module combinations from the local resource pool.

[0074] This involves power redundancy arbitration rules, which are the first-stage rules in the local arbitration rule set. The core of these rules is to select charging module combinations whose total output power is greater than the target, so as to ensure that the allocated power has a certain safety margin to cope with possible power fluctuations or slight degradation of module performance.

[0075] This involves a comprehensive quantitative indicator arbitration rule, which is the second-stage rule of the local arbitration rule set. Its core is to comprehensively evaluate and rank the candidate combinations that pass the power redundancy arbitration based on multiple quantitative indicators such as module health, load balancing, historical scheduling and response speed.

[0076] This involves the target sum, which is a key calculated value in the power redundancy arbitration rule. Its value is equal to the sum of the user's charging request power and the system's predetermined redundancy power value, serving as a threshold for selecting module combinations with sufficient power output capability.

[0077] This involves a predetermined redundant power, which is a power buffer value preset to ensure the reliability of the charging process and to cope with uncertainties. This value is added to the requested power to form the target and the target.

[0078] This includes quantitative indicators, which are multi-dimensional parameters used to comprehensively evaluate the performance of the charging module combination. These indicators may include module health indicators, module load balancing indicators, module historical scheduling indicators, and module response speed indicators.

[0079] Among them, the module health index is one of the quantitative indicators used to evaluate the hardware status and reliability of the charging module itself, and tends to select modules with low failure rate and stable operation.

[0080] Among them, the module load balancing metric is one of the quantitative metrics used to evaluate the load uniformity of each module in the system after resource allocation. It tends to select an allocation scheme that can make the overall system load more balanced in order to avoid overloading some modules.

[0081] This includes module historical scheduling metrics, which are one of the quantitative metrics used to consider the historical usage of modules, such as cumulative running time or recent scheduling frequency, to promote fair scheduling and avoid overuse of some modules.

[0082] Among them, the module response speed indicator is one of the quantitative indicators used to evaluate how quickly a module responds from receiving a command to reaching the target power. The indicator tends to select modules with faster response times to improve the charging experience.

[0083] This involves a local resource pool, which is a set of charging module resources managed and scheduled by a single controller in a distributed topology.

[0084] This involves a power redundancy parameter, which is one of the target resource parameters. Its value is the predetermined redundancy power, used for power redundancy arbitration calculation.

[0085] This involves a local charging module combination, which is a collection of one or more charging modules that meet the power redundancy requirements and are initially selected from the local resource pool through power redundancy arbitration.

[0086] This involves a comprehensive quantitative index, which is the overall score of a local charging module combination under the comprehensive quantitative indicator arbitration rules. It can be calculated by sub-quantitative indices corresponding to multiple quantitative indicator items according to a predetermined algorithm.

[0087] This involves sub-quantitative indices, which are scores calculated for individual quantitative indicators and are the basic units that make up the comprehensive quantitative index.

[0088] In this step, firstly, after identifying the target charging structure as a distributed topology, the system invokes a pre-set local dynamic arbitration strategy and its corresponding local arbitration rule set. Then, based on the power redundancy arbitration rules and the target resource parameters of the local resource pool, a first-stage power redundancy arbitration is performed, selecting all feasible local charging module combinations from the resource pool whose total power exceeds the target. Next, for each selected local charging module combination, its sub-quantification index under different quantification index items is calculated according to the comprehensive quantification index arbitration rules, and further synthesized to obtain the comprehensive quantification index for each combination. Finally, based on the calculated comprehensive quantification indices, the system determines the local charging module combination with the optimal comprehensive quantification index and ultimately identifies it as the target charging module.

[0089] This approach, by introducing power redundancy arbitration rules, ensures that the total power of the allocated module combination not only meets user requests but also reserves necessary safety margins. This effectively addresses potential power demand fluctuations or slight performance degradation of individual modules during charging, ensuring the safety and reliability of power allocation. Simultaneously, by introducing comprehensive quantitative indicators including health, load balancing, and historical scheduling for arbitration, resource allocation decisions consider not only instantaneous performance but also the long-term operating status of modules and system balance. This helps prevent premature aging due to overuse of some modules, optimizing the overall system's lifespan and operational stability. This two-stage arbitration mechanism makes dynamic resource allocation in a distributed topology more scientific and precise. It can automatically select the target module that is optimal in terms of power capacity, health status, and load conditions based on real-time system status and module characteristics, improving the intelligence and efficiency of resource utilization.

[0090] As an optional embodiment, based on the target allocation strategy and target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure. This includes: when the target charging structure is an integrated topology, retrieving the target mapping relationship corresponding to the fixed mapping allocation strategy, wherein the target mapping relationship includes the mapping matching relationship between the charging gun and the charging module; determining the charging gun identifier corresponding to the plug-in signal; and determining the fixed charging module matching the charging gun identifier as the target charging module based on the target mapping relationship.

[0091] This embodiment illustrates the specific process of determining the target charging module using a fixed mapping allocation strategy under an integrated topology.

[0092] This involves a fixed mapping allocation strategy, which is a resource allocation strategy designed for integrated topologies. Its core feature is that there is a predefined and unchangeable static binding relationship between the charging gun and the charging module, and the system directly allocates resources based on this fixed relationship.

[0093] This involves target mapping relationships, which are a specific manifestation of the fixed mapping allocation strategy. It is a predefined data structure that records the correspondence between each charging gun identifier and one or more fixed charging module identifiers that are uniquely bound to it.

[0094] This involves the mapping and matching relationship between the charging gun and the charging module. The mapping and matching relationship between the charging gun and the charging module is the specific associated entry recorded in the target mapping relationship. It defines that in the integrated topology, a specific charging gun controls a specific charging module in a fixed and exclusive manner, which is usually a one-to-one or one-to-many fixed mapping.

[0095] This involves the charging gun identifier, which is a code or code used to uniquely identify a specific charging gun in the system. It can be determined by the hardware design and carried in the gun insertion signal, and is used to find the corresponding fixed charging module in the target mapping relationship.

[0096] This includes fixed charging modules, which are one or more charging modules that are pre-bound to a specific charging gun identifier according to a target mapping relationship in an integrated topology and are exclusively used by that charging gun. The mapping relationship remains unchanged during system operation.

[0097] In this step, firstly, after the system identifies the target charging structure as an integrated topology, it invokes a preset fixed mapping allocation strategy and retrieves the target mapping relationship corresponding to that strategy. Then, the system parses the specific charging gun identifier from the triggered plug-in signal. Finally, based on the retrieved target mapping relationship, the system uses a query operation to find the fixed charging module that precisely matches the charging gun identifier and directly identifies that module as the target charging module.

[0098] This approach fixes the mapping relationship during the system design phase, requiring only simple query operations at runtime. It avoids the computational uncertainties and resource contention risks associated with dynamic allocation, making it suitable for fixed-configuration scenarios such as all-in-one machines where stability and predictability are paramount. This achieves extremely high determinism and reliability in resource allocation. The allocation mechanism eliminates complex arbitration, optimization calculations, and resource locking verification processes, resulting in a very short decision path. It can determine the target charging module with minimal latency, significantly improving the system's response speed when ready to charge after plugging in the charging gun. For simple topologies like integrated systems, the fixed mapping strategy achieves adaptation with minimal system overhead, demonstrating the architecture's flexibility and practicality, ensuring that it covers multiple topologies without sacrificing execution efficiency in simple scenarios.

[0099] As an optional embodiment, sending a charging command to the corresponding control unit includes: when there are multiple target charging modules, controlling the corresponding control unit to send a parallel control command to the multiple target charging modules so that the multiple target charging modules form a parallel structure; receiving parallel feedback information corresponding to the parallel control command; and when the parallel feedback information indicates that the multiple target charging modules have formed a parallel structure, sending a charging command to the corresponding control unit.

[0100] This embodiment illustrates the specific process of sending a charging command only after the modules are ready through a pre-parallel connection mechanism when multiple charging modules need to work together.

[0101] This involves parallel control commands, which are preliminary commands sent by the system to the control unit before issuing formal charging commands. They can be used to instruct the control unit to drive multiple target charging modules under its management to form a parallel operation structure in physical or logical order, in preparation for subsequent joint power output.

[0102] This involves a parallel structure, which refers to the parallel relationship formed by multiple charging modules in electrical connection or control logic, enabling them to jointly output current to the same load (electric vehicle), and its total output capacity is the sum of the outputs of each module.

[0103] This involves parallel feedback information, which is a status report returned by the control unit to the upper layer of the system after executing the parallel control command. It can be used to indicate whether the multiple target charging modules under its jurisdiction have successfully established the required parallel structure.

[0104] This involves multiple target charging modules, which refers to two or more charging modules that need to be simultaneously invoked to jointly complete this charging task, as determined by the aforementioned resource allocation steps.

[0105] In this step, the system first determines that multiple target charging modules need to be used for this charging operation. Then, instead of immediately sending a charging command, the system first sends a parallel control command to the corresponding control unit. The control unit executes this command, driving the multiple target charging modules to establish a parallel structure. The system receives parallel feedback information from the control unit and evaluates its content. Only when the feedback information confirms that the parallel structure has been successfully established does the system finally issue a charging command carrying the specific target charging parameters.

[0106] This approach enables status verification and safety assurance before multi-module collaborative operation. By adding a pre-parallel connection verification step, the system is forced to verify that multiple charging modules are correctly and reliably connected in parallel in terms of physical electrical connections before actually applying power for charging. This mechanism effectively prevents parallel connection failures caused by unreliable engagement of parallel contactors, abnormal synchronization between modules, or communication delays. If parallel connection fails, the system can detect and handle the anomaly before sending the charging command, thereby avoiding serious faults such as single-module overload, circulating current surges, unstable output voltage, or even equipment damage. This improves the system's safety in dynamic allocation and multi-module parallel scenarios, ensures the reliability and stability of the charging process startup, and provides users with a safe and high-quality charging service experience.

[0107] As an optional embodiment, based on the target allocation strategy and target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined. This includes: if the charging request also carries user demand parameters and electric vehicle status parameters, obtaining the user demand parameters and electric vehicle status parameters; and based on the target allocation strategy, target resource parameters, user demand parameters, and electric vehicle status parameters, determining the target charging module to be invoked from the charging modules corresponding to the target charging structure, and determining the target charging parameters corresponding to the target charging module.

[0108] This embodiment illustrates how to optimize the resource allocation and parameter decision-making process by introducing richer contextual information.

[0109] This involves user demand parameters, which are a set of parameters embedded in the charging request or obtained through user interaction that reflect the user's personalized charging preferences. These parameters may include expected charging duration, target charging capacity, charging mode selection, and budget constraints, and are important inputs for personalized service customization.

[0110] This involves electric vehicle status parameters, which are technical parameters describing the current state of the electric vehicle requesting charging. These parameters are obtained through communication between the charging gun and the vehicle's battery management system, including but not limited to the current battery state of charge, battery health status, battery temperature, maximum allowable charging current / voltage, and supported charging protocol versions. They are crucial for ensuring charging safety and compatibility.

[0111] In this step, the system first detects that the charging request, in addition to the basic charging interface identifier, also carries user demand parameters and electric vehicle status parameters, and acquires these parameters. Subsequently, during the resource allocation and parameter determination process based on the target allocation strategy and target resource parameters, the system uses the user demand parameters and electric vehicle status parameters as important decision inputs, participating in the calculation and judgment together, and finally comprehensively determines the target charging modules to be called and the more refined target charging parameters corresponding to these modules.

[0112] This approach achieves personalized and intelligent enhancements to charging services. By introducing user demand parameters, resource allocation and charging parameter settings can better align with users' individual preferences, significantly improving user experience and service satisfaction. Introducing electric vehicle status parameters allows the system to fully consider the actual state and safety boundaries of the vehicle's battery when allocating resources and setting parameters, thus avoiding damage such as overcharging and overloading, ensuring battery safety during charging, and extending battery life. By comprehensively considering user needs and vehicle status, the allocated module combinations and their output parameters can be more rational, avoiding waste caused by over-allocation of resources and preventing insufficient allocation from failing to meet reasonable user needs, thereby achieving more refined resource management and energy efficiency improvements at the system level.

[0113] Based on the above embodiments and optional embodiments, an optional implementation method is provided, which is described in detail below.

[0114] An optional embodiment of the present invention provides a software abstraction method that supports multiple charging pile system topologies. Figure 2 This is a seven-layer hierarchical abstract architecture diagram of an optional embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the adaptation of the software abstraction method of the optional embodiments of the present invention under various topologies, such as... Figure 2-3 As shown, it will be introduced below.

[0115] This invention employs a seven-layer hierarchical abstraction architecture, abstracting layer by layer from the underlying hardware to the upper-level applications. See the diagram of the seven-layer hierarchical abstraction architecture. Figure 2 This architecture features a clear layering: a 7-layer architecture with well-defined responsibilities and low coupling between layers; downward dependency: upper layers depend on services provided by lower layers, while lower layers are unaware of upper layers; unified interface: each layer provides a unified interface to the outside world, shielding internal implementation differences; easy extensibility: adding new topologies only requires adaptation of the lowest layer, without modification of upper layers; and precise requirement input down to the layer level, minimizing changes and impact. The following is a description of some of the layers:

[0116] 1) Charging gun object layer:

[0117] To address the issue that the mapping relationship between the charging gun and the hardware is completely different under different topologies, Table 1 shows the mapping relationship between the charging gun and the hardware under different topologies provided by the optional embodiments of the present invention.

[0118] Table 1

[0119]

[0120] A "charging gun object" is established as the core abstract unit. The charging gun object data structure is defined; resource mapping for the configuration driver is handled by defining resource mapping relationships through a JSON configuration file, which is dynamically loaded at runtime. Upper-layer applications only need to manipulate the "charging gun object" without needing to be aware of topology differences; adding new topologies only requires writing configuration files, without modifying the code, or simply modifying the driver hierarchy; complex resource mapping relationships (fixed / dynamic / shared) are supported; and adaptability to topologies with different numbers of charging guns is achieved.

[0121] 2) Interaction layer:

[0122] To achieve an efficient data transmission mechanism, a dedicated interaction layer was designed, which includes multiple mechanisms.

[0123] Priority-based message queues; double-buffered data synchronization; event publish-subscribe mechanism.

[0124] This ensures that fault messages respond within 10ms (priority queue); the underlying and application layers are completely decoupled (event mechanism); and charging real-time data is generated at a high frequency (10-100Hz).

[0125] 3) Protocol layer:

[0126] The unified adaptation of multiple protocols solves the problem of charging devices involving multiple heterogeneous protocols. Table 2 is a table of multiple heterogeneous protocols for charging devices provided by the optional embodiments of the present invention, as shown in Table 2.

[0127] Table 2

[0128]

[0129] By establishing a unified protocol adapter interface, common functions of various protocols are abstracted: initialization, receiving data, and sending data; protocol routing mechanism; upper layers do not need to be aware of specific protocols; new protocols only need to implement the adapter interface; protocols are automatically routed and flexibly extended.

[0130] 4) Charging service function layer:

[0131] It includes state machines and functional modules.

[0132] The charging process state machine abstracts the common process states of the charging business: plug-in state; initiation state; handshake state; charging state; charging complete state; plug-out idle state; and charging function modules. The charging startup module includes: safety check → resource allocation → BMS handshake → parameter configuration → module startup → billing startup; the charging detection module includes: reading real-time data → safety check → power adjustment → billing and metering → data reporting; the fault alarm handling module includes: overvoltage / overcurrent / overtemperature / BMS timeout / module fault / insulation fault detection; and the metering and billing module includes: processing energy, electricity fees, and charging record data. This ensures a unified charging process, consistent behavior, reusable function modules, and universal functionality across various topologies.

[0133] It includes a configuration driver-based topology adaptation mechanism:

[0134] Configuration file driven. The configuration loading mechanism means that adding topologies only requires writing configuration files; the configuration is clear and easy to maintain.

[0135] Optionally, based on the above embodiments and optional embodiments, an optional implementation method is provided, including:

[0136] Dual-gun all-in-one machine: Configuration: 1 controller + 2 guns + 2 modules (fixed mapping).

[0137] Adaptation method: The gun-module mapping relationship is defined through a JSON configuration file, requiring no code modification. Using the charging gun as an example, this abstract method significantly reduces repetitive work for developers on charging devices with different topologies, improving work efficiency and the stability of development for new charging pile companies' equipment and topologies.

[0138] In short, the system loads the configuration file, reads the dual-gun configuration of the all-in-one machine upon startup, and establishes a fixed mapping between the guns and modules; it creates two charging gun objects dynamically, each bound to one charging module; it initializes hardware resources, protocol adapters, and functional modules, including CAN and RS-485 communication protocol adapters, and loads the charging service functional modules; the system enters a ready state, completing initialization and waiting for the user to plug in the gun for charging. The charging process includes: plugging in state; startup state; handshake state; charging state; charging complete state; and unplugging / idling state. Technical benefits include: concurrent charging with dual guns without interference; fault isolation, allowing the other gun to continue charging even if one fails; adding similar topologies only requires modifying the configuration file, reducing the development cycle to less than one week; business logic reusability is greater than 90%, resulting in high system stability. Using the abstract method described in this document, only configuration file configuration, hardware resource initialization, and protocol adapter setup are required; the entire charging service, including gun status and fault handling, is completely independent and requires no separate development.

[0139] Split-type single gun: Configuration: 1 controller + 1 gun + 4 modules (dynamically allocated).

[0140] Adaptation Method: The configuration file defines a dynamic mapping rule of "1 gun - N modules". Implementation Steps: Load the split-unit configuration: The system reads the configuration file, identifies the topology as "single gun dynamic allocation" mode, and initializes a shared resource pool containing 4 modules. Create a charging gun object: The system creates one charging gun object, which is not bound to a fixed module, but is associated with the entire dynamic resource pool. Initialize the protocol and functional modules: Load the protocol route and, critically, initialize the dynamic power arbitrator. This arbitrator belongs to the charging business function layer and is responsible for allocating and reclaiming modules from the resource pool for the charging gun object based on the charging request and system status. The system enters standby state: waiting for user charging requests. A dynamic power allocation process can be implemented, based on an abstract architecture. Since dynamic power allocation is not a simple business logic, but a collaborative process initiated by the charging gun object layer, passed through the interaction layer, decided by a dedicated module in the charging business function layer, and finally executed in the driver layer.

[0141] The specific process is as follows: Receiving a charging request: The user sets the requested power (e.g., 60kW), and the application layer sends this request. The charging gun object receives the request, its internal state machine switches to the "starting" state, and initiates a "resource allocation" request to the power dynamic arbitrator (located in the charging business function layer). Resource arbitration and allocation: The arbitrator queries the requested power (60kW) reported by the charging gun object and the rated power of each module (e.g., 30kW). Based on a preset strategy (e.g., the minimum number of modules strategy), the arbitrator calculates the optimal allocation scheme from the global resource pool (allocating 2 modules, i.e., module 1 and module 2). The arbitrator sends instructions to the driver layer through the interaction layer to dynamically bind the physical control rights of module 1 and module 2 to the charging gun object. The charging gun object updates its internal resource mapping table, at which point it "holds" module 1 and module 2. Dynamically adjusting power during charging: Scenario: The user increases the charging power to 90kW. The charging gun object again initiates a "resource reallocation" request to the power dynamic arbitrator. The arbitrator receives the 90kW request and calculates that 3 modules are needed. It checks the resource pool and finds that module 3 is idle. The arbitrator performs allocation, adding module 3 to the resource mapping of the charging gun object and activating module 3 in real time through the driver layer. Technical effect: This process is implemented in an architecture where the business layer and driver layer are decoupled. The core charging business process does not need to care about the addition or deletion of underlying modules; dynamic and seamless power adjustment can be completed simply by updating the state of the charging gun object. Charging completion and resource reclamation: When charging ends, the state machine of the charging gun object enters the "charging complete" state. The object automatically initiates a "resource release" request to the arbitrator. The arbitrator releases all modules it holds (module 1, module 2, module 3) back to the global resource pool for subsequent use. Technical effect: Architectural-level dynamic allocation: Power allocation is a mechanism completed collaboratively by various abstract layers defined in this invention, rather than simple business logic, achieving complete decoupling of hardware resources and software business. Maximized module utilization: Through the central arbitrator and shared resource pool, on-demand allocation is achieved, increasing module utilization by >40%. High reliability: The arbitrator can monitor the health status of modules in real time. If module 1 experiences a sudden failure, the system can automatically allocate module 4 from the resource pool as a replacement and complete the switchover within seconds, without the user noticing. The strategy is configurable: arbitration strategies (such as load balancing and priority) can be configured as options, adapting to different operational needs without modifying the core code.

[0142] Multi-gun charging island: To further demonstrate the applicability of the method provided by the optional embodiments of the present invention in more complex and larger topologies, this embodiment describes its application in a "charging island" scenario. Compared with Embodiment 1 (fixed mapping) and Embodiment 2 (dynamic allocation by a single controller), this embodiment needs to handle the problem of global resource sharing and competition across controllers, which is achieved by enhancing the arbitration mechanism in the architecture.

[0143] The configuration can be: 2 controllers + 4 guns + 6 modules (shared mapping).

[0144] Adaptation method: A shared resource pool across controllers is defined via a JSON configuration file, and a global resource arbitrator with a multi-objective decision function is enabled. Specific strategy and logic of shared mapping: The sharing strategy of this invention is not a simple "first-come, first-served" approach, but is executed by a global resource arbitrator located in the charging service function layer. This arbitrator makes decisions based on a comprehensive optimization objective function. The optimization objective function is the core decision-making basis of the arbitrator, a multi-objective optimization function that aims to find the optimal solution for the system in each allocation.

[0145] Maximize:α Efficiency+β Fairness-γ Fragmentation;

[0146] The allocation process includes the following parameters: Efficiency: Prioritizes allocating the fewest possible modules to satisfy power requests, reserving more modules for subsequent requests and improving overall throughput. Its calculation is related to the required number of modules / the number of modules allocated. Fairness: Ensures all charging requests are served, avoiding prolonged waiting times for some charging stations. This is achieved by maintaining a "priority weight" for each charging station, which increases with waiting time. Fragmentation: Assesses whether this allocation will result in the remaining resources being divided into multiple small blocks that cannot satisfy high-power requests. α, β, and γ are corresponding adjustment coefficients that can be adaptively set according to the actual application and scenario. The decision tends to favor allocation schemes that produce larger, contiguous blocks of idle modules.

[0147] It also possesses certain decision-making logic and constraints: Input: Power request of the charging gun object, real-time status of each module (idle / occupied / faulty), system constraints. Constraints: Power constraint: Total output power of the allocated modules ≥ requested power. Module exclusivity constraint: A module can only be allocated to one charging gun at a time. Output: An optimal allocation scheme of [charging gun -> module set].

[0148] Module Sharing and Arbitration Process: Initial Concurrent Requests: Gun 1 (connected to controller A) requests 60kW, and Gun 2 (connected to controller B) simultaneously requests 30kW. Both requests are reported to the global resource arbitrator by their respective controllers. Arbitrator Decision and Allocation: The arbitrator incorporates both requests into the same decision cycle and runs an optimization algorithm. Candidate Solution Evaluation: Solution 1: Allocate [Module 1, Module 2] to Gun 1 and [Module 3] to Gun 2. This solution is efficient and has low fragmentation. Solution 2: Allocate [Module 4, Module 5] to Gun 1 and [Module 6] to Gun 2. This solution may result in subsequent high-power requests not being fulfilled. Resource Preemption and Reallocation: Scenario: Gun 1 completes charging and releases Modules 1 and 2. At this time, Gun 2 wants to increase the power from 30kW to 90kW. Decision: Gun 2 initiates a reallocation request. The arbitrator calculates that 3 modules are needed to meet 90kW. The current idle pool is [Module 1, Module 2], and Gun 2 already holds [Module 3]. Optimal Solution: The arbitrator immediately allocates modules 1 and 2 to gun 2, forming a combination of [module 1, module 2, module 3], perfectly meeting the power requirement. This process is completed automatically by the system without manual intervention. Optimization Decision in Complex Scenarios: Scenario: Gun 3 (high-priority VIP user) requests 120kW, but the system only has 4 idle modules, which are allocated to gun 2 (90kW) and gun 4 (30kW). Decision: The arbitrator initiates secondary scheduling. It calculates that if the allocation of gun 4 is optimized from 2 modules to 1 module (still meeting the 30kW requirement), enough modules can be freed up to meet gun 3's 120kW request. Execution: The arbitrator forcibly adjusts the resource mapping of gun 4, allocating the freed-up modules to gun 3, achieving the optimization goal of tilting system resources towards high-value requests while ensuring basic services. Technical Effects: Global Optimum: Through a multi-objective decision function, cross-controller system-level resource optimization is achieved, rather than local optima, with an average module utilization improvement of >50%. Dynamic and Adaptive: The system can dynamically adjust resource allocation based on real-time load and business strategies (such as priority), exhibiting high intelligence and adaptability. Business Value: This mechanism can directly support operational strategies, such as enabling rapid switching between different operational strategies like power priority and fair operation.

[0149] The above optional implementation methods can achieve at least the following beneficial effects:

[0150] (1) This implementation plan can significantly improve development efficiency, greatly improve system performance, and significantly reduce maintenance costs;

[0151] (2) Reduces R&D costs, increases code reuse rate, and improves development efficiency by 3-10 times;

[0152] (3) Shorten the time to market, and shorten the development of new topologies from monthly to weekly.

[0153] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0154] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0155] Example 2

[0156] According to an embodiment of the present invention, a charging system for an electric vehicle is also provided, comprising: a sensing layer, a communication layer, an application layer, a resource management layer, and a control layer, wherein the sensing layer is used to trigger a charging gun signal based on a target operation, wherein the target operation includes the operation of inserting a charging gun into the charging interface of an electric vehicle; the communication layer is used to receive a charging request corresponding to a charging pile system, wherein the charging request is in response to the generation of the charging gun signal, and the charging request carries a charging interface identifier, the charging interface identifier being used to identify the charging structure of the charging device, the charging structure including one of the following: an integrated topology, a distributed topology, and a shared topology, wherein the integrated topology is used to fix and control multiple first charging modules through a first control unit, the distributed topology is used to dynamically control multiple second charging modules through a second control unit, and the shared topology is used to share and control multiple third charging modules through multiple third control units; the application layer is used, in response to the charging request, to determine a target charging structure corresponding to the charging device based on the charging interface identifier; and to determine a target allocation strategy corresponding to the target charging structure, wherein... The target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology; the resource management layer is used to determine the target resource parameters corresponding to the target charging structure, wherein the target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology; based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined; the communication layer is used to send a charging command to the corresponding control unit, wherein the charging command carries the identifier corresponding to the target charging module and the target charging parameters; the control layer is used to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters.

[0157] Example 3

[0158] According to an embodiment of the present invention, an apparatus for implementing the above-described charging method for an electric vehicle is also provided. Figure 4 This is a structural block diagram of a charging device for an electric vehicle according to an embodiment of the present invention, such as... Figure 4 As shown, the device includes: a receiving module 402, a first determining module 404, a second determining module 406, a third determining module 408, and a transmitting module 410. The device will be described in detail below.

[0159] A receiving module 402 is used to receive a charging request corresponding to the charging pile system. The charging request is responded to by a plug-in signal, which is triggered by a target operation. The target operation includes the insertion of a charging gun into an electric vehicle charging interface. The charging request carries a charging interface identifier, which identifies the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, or a shared topology. The integrated topology is used to fix and control multiple first charging modules through a first control unit. The distributed topology is used to dynamically control multiple second charging modules through a second control unit. The shared topology is used to share and control multiple third charging modules through multiple third control units. A first determining module 404, connected to the receiving module 402, is used to determine, in response to the charging request, a target charging structure corresponding to the charging device based on the charging interface identifier. A second determining module 406, connected to the first determining module 404, is used to determine a target allocation strategy and target resource parameters corresponding to the target charging structure. The strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. A third determining module 408, connected to the second determining module 406, is used to determine the target charging module to be called from the charging modules corresponding to the target charging structure based on the target allocation strategy and the target resource parameters, and to determine the target charging parameters corresponding to the target charging module. A sending module 410, connected to the third determining module 408, is used to send a charging command to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier corresponding to the target charging module and the target charging parameters.

[0160] It should be noted here that the receiving module 402, the first determining module 404, the second determining module 406, the third determining module 408 and the sending module 410 mentioned above correspond to steps S102 to S110 in the method for charging electric vehicles. The multiple modules and the corresponding steps are the same in terms of implementation examples and application scenarios, but are not limited to the content disclosed in the above embodiment 1.

[0161] Example 4

[0162] According to another aspect of the present invention, an electronic device is also provided, comprising: a processor; and a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the electric vehicle charging method of any of the above embodiments.

[0163] Example 5

[0164] According to another aspect of the present invention, a computer-readable storage medium is also provided, which, when the instructions in the computer-readable storage medium are executed by a processor of an electronic device, enables the electronic device to perform any of the above-described electric vehicle charging methods.

[0165] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0166] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0167] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0168] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0169] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0170] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0171] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A charging method for an electric vehicle, characterized in that, include: The system receives a charging request corresponding to a charging pile system. The charging request is responded to by a plug-in signal, which is triggered by a target operation. The target operation includes inserting the charging gun into the electric vehicle's charging interface. The charging request carries a charging interface identifier, which identifies the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, or a shared topology. The integrated topology is used to fix and control multiple first charging modules through a first control unit. The distributed topology is used to dynamically control multiple second charging modules through a second control unit. The shared topology is used to share and control multiple third charging modules through multiple third control units. In response to the charging request, the target charging structure corresponding to the charging device is determined based on the charging interface identifier; Determine the target allocation strategy and target resource parameters corresponding to the target charging structure, wherein the target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology; the target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. Based on the target allocation strategy and the target resource parameters, the target charging module to be called is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined. A charging command is sent to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module and charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier of the target charging module and the target charging parameters.

2. The method according to claim 1, characterized in that, Based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, including: When the target charging structure is the shared topology, the target optimization function corresponding to the global multi-objective optimization strategy is invoked. The target optimization function aims to make the joint target index corresponding to the joint indicator item greater than a predetermined threshold. The joint indicator item includes a charging efficiency indicator item, a charging waiting time indicator item, and a continuous idle degree indicator item of the remaining charging modules after allocation. Based on the target resource parameters in the global resource pool, the target optimization function is solved to obtain multiple global charging module combinations, wherein the multiple global charging module combinations include cross-control unit charging module combinations; Send cross-control unit resource locking requests corresponding to the multiple global charging module combinations to the corresponding control units, and receive locking feedback results corresponding to the multiple global charging module combinations. The target charging module is determined by identifying the combination of global charging modules that can be successfully locked based on the corresponding locking feedback result and has the highest corresponding joint target index.

3. The method according to claim 1, characterized in that, Based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, including: When the target charging structure is the distributed topology, the local arbitration rule set corresponding to the local dynamic arbitration strategy is retrieved. The local arbitration rule set includes power redundancy arbitration rules and comprehensive quantitative index arbitration rules. The power redundancy arbitration rules include filtering out charging module combinations whose total power is greater than the target sum. The target sum is the sum of the requested power and the predetermined redundant power. The comprehensive quantitative index arbitration rules include rules for comprehensive arbitration based on multiple quantitative index items. The multiple quantitative index items include: module health index item, module load balancing index item, module historical scheduling index item, and module response speed index item. Based on the power redundancy arbitration rules and the target resource parameters corresponding to the local resource pool, power redundancy arbitration is performed to obtain multiple combinations of local charging modules, wherein the target resource parameters include power redundancy parameters; Under the comprehensive quantitative index arbitration rule, the comprehensive quantitative index corresponding to each of the multiple local charging module combinations is determined, wherein the corresponding comprehensive quantitative index is obtained based on the sub-quantitative index corresponding to each of the multiple quantitative index items; The target charging module is determined from the multiple combinations of local charging modules based on a number of comprehensive quantitative indices.

4. The method according to claim 1, characterized in that, Based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, including: When the target charging structure is the integrated topology, the target mapping relationship corresponding to the fixed mapping allocation strategy is retrieved, wherein the target mapping relationship includes the mapping matching relationship between the charging gun and the charging module; Determine the charging gun identifier corresponding to the plug-in signal; Based on the target mapping relationship, the fixed charging module that matches the charging gun identifier is determined as the target charging module.

5. The method according to claim 1, characterized in that, Sending charging commands to the corresponding control unit, including: When multiple target charging modules are identified, the corresponding control unit sends parallel control commands to the multiple target charging modules so that the multiple target charging modules form a parallel structure. Receive parallel feedback information corresponding to the parallel control command; When the parallel feedback information indicates that the multiple target charging modules have formed the parallel structure, the charging command is sent to the corresponding control unit.

6. The method according to any one of claims 1 to 5, characterized in that, Based on the target allocation strategy and the target resource parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined, including: If the charging request also carries user demand parameters and electric vehicle status parameters, obtain the user demand parameters and the electric vehicle status parameters. Based on the target allocation strategy, the target resource parameters, the user demand parameters, and the electric vehicle status parameters, the target charging module to be invoked is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined.

7. A charging system for an electric vehicle, characterized in that, include: The layers are: perception layer, communication layer, application layer, resource management layer, and control layer. The sensing layer is used to trigger a charging gun insertion signal based on a target operation, wherein the target operation includes the operation of inserting the charging gun into the charging interface of an electric vehicle; The communication layer is used to receive charging requests corresponding to the charging pile system. The charging request is in response to the generation of the plug-in signal. The charging request carries a charging interface identifier, which is used to identify the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, and a shared topology. The integrated topology is used to fix and control multiple first charging modules through a first control unit. The distributed topology is used to dynamically control multiple second charging modules through a second control unit. The shared topology is used to share and control multiple third charging modules through multiple third control units. The application layer is used to respond to the charging request, determine the target charging structure corresponding to the charging device based on the charging interface identifier, and determine the target allocation strategy corresponding to the target charging structure, wherein the target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The resource management layer is used to determine the target resource parameters corresponding to the target charging structure, wherein the target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology; based on the target allocation strategy and the target resource parameters, the target charging module to be called is determined from the charging modules corresponding to the target charging structure, and the target charging parameters corresponding to the target charging module are determined; The communication layer is used to send charging commands to the corresponding control unit, wherein the charging command carries the identifier corresponding to the target charging module and the target charging parameters; The control layer is used to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters.

8. A charging device for an electric vehicle, characterized in that, include: A receiving module is used to receive a charging request corresponding to the charging pile system. The charging request is in response to the generation of a plug-in signal, which is triggered based on a target operation. The target operation includes the operation of inserting the charging gun into the charging interface of an electric vehicle. The charging request carries a charging interface identifier, which is used to identify the charging structure of the charging device. The charging structure includes one of the following: an integrated topology, a distributed topology, and a shared topology. The integrated topology is used to fix and control multiple first charging modules through a first control unit. The distributed topology is used to dynamically control multiple second charging modules through a second control unit. The shared topology is used to share and control multiple third charging modules through multiple third control units. The first determining module is used to respond to the charging request and determine the target charging structure corresponding to the charging device based on the charging interface identifier; The second determining module is used to determine the target allocation strategy and target resource parameters corresponding to the target charging structure. The target allocation strategy includes one of the following: a fixed mapping allocation strategy corresponding to the integrated topology, a local dynamic arbitration strategy corresponding to the distributed topology, and a global multi-objective optimization strategy corresponding to the shared topology. The target resource parameters include one of the following: resource parameters of the integrated charging module group corresponding to the integrated topology, resource parameters of the local resource pool corresponding to the distributed topology, and resource parameters of the global resource pool corresponding to the shared topology. The third determining module is used to determine the target charging module to be called from the charging modules corresponding to the target charging structure, based on the target allocation strategy and the target resource parameters, and to determine the target charging parameters corresponding to the target charging module. The sending module is used to send a charging command to the corresponding control unit to control the corresponding control unit to use the corresponding target charging module to charge the electric vehicle with the corresponding target charging parameters. The charging command carries the identifier of the target charging module and the target charging parameters.

9. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the charging method for an electric vehicle as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by the processor of the electronic device, the electronic device is able to perform the charging method for an electric vehicle as described in any one of claims 1 to 6.

Images