New energy automobile charging interface adaptation method and system based on multi-protocol conversion

Abstract

The invention discloses a new energy automobile charging interface adaptation method and system based on multi-protocol conversion, and relates to the related field of new energy automobile charging, and the method comprises the steps: collecting multi-protocol interaction data in a charging connection building process; executing protocol behavior level disassembly, and establishing an interaction behavior segment; constructing a charging interaction semantic unit by utilizing the interaction behavior fragments, and combining according to a charging process stage and a time sequence to form a charging interaction semantic intermediate state model; dynamically updating the charging interaction semantic intermediate state model in the charging process, and executing semantic continuity verification; and carrying out progressive adjustment on the interaction parameters of the target charging protocol based on the reversible mapping chain according to the verification result. According to the method and the device, the technical problems of insufficient adaptation flexibility and lack of dynamic interaction adjustment in the existing new energy automobile charging interface adaptation are solved, and the technical effects of improving the multi-protocol adaptation flexibility and realizing dynamic and accurate adjustment in the charging interaction process to guarantee the charging stability are achieved.

Description

Technical Field

[0001] This application relates to the field of new energy vehicle charging, and in particular to a method and system for adapting new energy vehicle charging interfaces based on multi-protocol conversion. Background Technology

[0002] The reliability of charging interface adaptation for new energy vehicles directly determines charging efficiency and safety, and is crucial for promoting the large-scale development of the new energy vehicle industry. It is also of great significance for ensuring charging network compatibility and improving the user charging experience. Currently, the mainstream technology for solving charging interface adaptation problems mainly adopts a fixed protocol conversion module approach. This involves pre-setting mapping rules for mainstream charging protocols to convert the format of the interaction data between the vehicle and the charging station to achieve adaptation. However, this method relies excessively on pre-configured protocol rules, making it difficult to cover new charging protocols and protocol version updates. This results in insufficient adaptation flexibility and a lack of real-time perception and adjustment of the dynamic interaction status during the charging process, easily leading to safety and efficiency risks such as protocol interaction stuttering and charging parameter mismatches.

[0003] Currently, the technology for adapting charging interfaces for new energy vehicles suffers from technical problems such as insufficient adaptability and lack of dynamic interactive adjustment. Summary of the Invention

[0004] This application provides a method and system for adapting new energy vehicle charging interfaces based on multi-protocol conversion. During the process of establishing a charging connection between a new energy vehicle and a charging device, multi-protocol interaction data containing charging protocol interaction messages, electrical interface status parameters, and status feedback information is collected. This data is then decomposed at the protocol behavior level to obtain energy request, safety constraint, and control response interaction behavior fragments. Based on these fragments, charging interaction semantic units are constructed and combined according to the charging process stages and time sequence to form a dynamically updated charging interaction semantic intermediate state model. This model is dynamically updated during the charging process, and the continuity of adjacent semantic state evolution is verified based on a reversible mapping chain. Based on the verification results, the interaction parameters of the target charging protocol are progressively adjusted through the reversible mapping chain. These technical means solve the technical problems of insufficient adaptation flexibility and lack of dynamic interaction adjustment in existing new energy vehicle charging interface adaptations, achieving the technical effect of improving multi-protocol adaptation flexibility and realizing dynamic and precise adjustment of the charging interaction process to ensure charging stability.

[0005] This application provides a method for adapting charging interfaces for new energy vehicles based on multi-protocol conversion, comprising: during the process of establishing a charging connection between a new energy vehicle and a charging device, collecting multi-protocol interaction data to characterize the charging interaction process, wherein the multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and status feedback information of the charging process; performing protocol behavior-level decomposition of the multi-protocol interaction data to establish interaction behavior segments characterizing energy requests, safety constraints, and control responses; constructing corresponding charging interaction semantic units using the interaction behavior segments, and combining the charging interaction semantic units according to the charging process stages and time sequence to form a charging interaction semantic intermediate state model characterizing the joint charging behavior state of the current charging stage, wherein the charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process; dynamically updating the charging interaction semantic intermediate state model during the charging process, and performing semantic continuity verification of the evolution relationship between adjacent semantic states based on a reversible mapping chain; and progressively adjusting the interaction parameters of the target charging protocol based on the reversible mapping chain according to the semantic continuity verification results.

[0006] In a possible implementation, the reversible mapping chain is a hierarchical bidirectional semantic evolution constraint structure constructed for the charging interaction semantic intermediate state model. It performs the following processing: The joint semantic states in the charging interaction semantic intermediate state model are structurally decomposed to obtain a multidimensional semantic sub-state set including energy request sub-states, safety constraint sub-states, and control rhythm sub-states. Each semantic sub-state corresponds to a protocol field set of different granularities under different charging protocols. Based on the multidimensional semantic sub-state set, multiple sets of forward semantic projection operators are constructed to project different semantic sub-states into candidate protocol control states according to the field organization rules of the target charging protocol. Different forward semantic projection operators correspond to different protocol understanding assumptions and field combination logics. During the execution of the target charging protocol, electrical responses, status confirmations, and anomaly feedback information triggered by the candidate protocol control states are collected in real time. The real-time collection results are re-embedded into the charging interaction semantic intermediate state model to form a semantic-execution coupled evolution state. Based on the semantic-execution coupled evolution state, a reverse semantic backtracking operator is constructed. The constraint optimization of the forward semantic projection operator is performed using the reverse semantic backtracking operator to establish the reversible mapping chain.

[0007] In a possible implementation, the inverse semantic backtracking operator is used to optimize the constraints of the forward semantic projection operator, establishing a reversible mapping chain. The following processes are performed: the inverse semantic backtracking operator is used to reverse-parse the candidate protocol control state and its corresponding execution feedback to recover the updated semantic sub-state set corresponding to the semantic level after protocol execution; within the same mapping period, semantic closed-loop consistency analysis is performed on the semantic sub-state set before forward semantic projection and the updated semantic sub-state set recovered by the inverse semantic backtracking operator to generate a semantic consistency constraint index characterizing the semantic maintenance capability of the reversible mapping chain in the current charging stage; the semantic consistency constraint index is used to jointly constrain the selection of the forward semantic projection operator, the activation order of the mapping path, and the adjustment range of the protocol interaction parameters to construct the reversible mapping chain.

[0008] In a possible implementation, semantic continuity verification of the evolutionary relationship between adjacent semantic states is performed based on a reversible mapping chain, and the following processing is performed: During the charging process, using the charging interaction semantic intermediate state model as a unified semantic carrier, a first joint semantic state and a second joint semantic state are generated in two adjacent charging interaction cycles, respectively. The first joint semantic state and the second joint semantic state are both obtained by mapping the interaction behavior fragments through a forward semantic projection operator and correcting them through a reverse semantic backtracking operator; based on the reversible mapping chain, semantic forward prediction is performed on the first joint semantic state along the forward semantic projection path to construct the expected evolutionary semantic state; the expected evolutionary semantic state and the second joint semantic state are compared for consistency to generate a semantic continuity verification result.

[0009] In possible implementations, the following processing is performed: consistency comparison includes energy semantic continuity dimension comparison, security semantic preservation dimension comparison, forward-backward semantic closed loop consistency dimension comparison, semantic evolution path consistency dimension comparison, and semantic evolution rate consistency dimension comparison.

[0010] In a possible implementation, the interaction parameters of the target charging protocol are progressively adjusted based on the semantic continuity verification result and a reversible mapping chain. The following processing is performed: using the semantic continuity verification result as the closed-loop control input of the reversible mapping chain, the adjustability of the protocol interaction parameter set corresponding to the current forward semantic projection operator is determined, wherein the protocol interaction parameter set includes at least power request parameters, voltage and current limit parameters, and interaction timing parameters; when the semantic continuity verification result indicates that there is a trend of deviation from the expected semantic evolution path between adjacent semantic states, the semantic sub-state category causing the deviation is determined based on the reversible mapping chain, and an adjustable subset of protocol interaction parameters is configured; in the adjustable subset of protocol interaction parameters, the single adjustment step size and adjustment direction of the protocol interaction parameters are determined according to the degree of semantic deviation corresponding to the semantic continuity verification result, and progressive adjustment is performed.

[0011] In a possible implementation, the following process is performed: after reading the current charging process stage, stage constraints are established, including the priority and adjustment range limits of protocol interaction parameters, and progressive adjustment constraint compensation is performed according to the stage constraints.

[0012] In a possible implementation, based on the semantic continuity verification result, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain, and the following processing is also performed: continuous charging interaction cycle monitoring is performed for progressive adjustment, and cycle feedback is established; if the semantic continuity verification result of the cycle feedback does not meet the verification threshold within the preset continuous cycle, a rollback safety protection mechanism is triggered; and the interaction parameters are rolled back according to the rollback safety protection mechanism.

[0013] In a possible implementation, the following processing is performed: performing early warning trigger analysis based on the semantic continuity verification result, configuring an early warning signal, and managing anomaly reporting based on the early warning signal.

[0014] This application also provides a new energy vehicle charging interface adaptation system based on multi-protocol conversion, including: a multi-protocol interaction data acquisition module, used to acquire multi-protocol interaction data characterizing the charging interaction process during the establishment of a charging connection between the new energy vehicle and the charging equipment, wherein the multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and charging process status feedback information; a protocol behavior-level decomposition module, used to perform protocol behavior-level decomposition of the multi-protocol interaction data and establish interaction behavior fragments characterizing energy requests, safety constraints, and control responses; and a charging interaction semantic intermediate state model generation module, used to construct corresponding charging interaction models using the interaction behavior fragments. The system comprises: a semantic unit and a semantic unit for charging interaction, which are combined according to the charging process stages and time sequence to form a charging interaction semantic intermediate state model representing the joint charging behavior state of the current charging stage. The charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process; a semantic continuity verification module, which is used to dynamically update the charging interaction semantic intermediate state model during the charging process and perform semantic continuity verification of the evolution relationship between adjacent semantic states based on a reversible mapping chain; and an interaction parameter progressive adjustment module, which is used to progressively adjust the interaction parameters of the target charging protocol based on the reversible mapping chain according to the semantic continuity verification results.

[0015] The proposed method and system for adapting new energy vehicle charging interfaces based on multi-protocol conversion, as described in this application, firstly collects multi-protocol interaction data to characterize the charging interaction process during the establishment of a charging connection between the new energy vehicle and the charging equipment. This multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and charging process status feedback information. Next, the protocol behavior level of the multi-protocol interaction data is decomposed to establish interaction behavior segments characterizing energy requests, safety constraints, and control responses. Then, corresponding charging interaction semantic units are constructed using these interaction behavior segments. These units are combined according to the charging process stages and time sequence to form a charging interaction semantic intermediate state model characterizing the joint charging behavior state of the current charging stage. This intermediate state model is a joint semantic state representation that is dynamically updated during the charging process. The intermediate state model is then dynamically updated during the charging process, and semantic continuity verification of the evolutionary relationship between adjacent semantic states is performed based on a reversible mapping chain. Finally, based on the semantic continuity verification results, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain. Through the above process, the method and system proposed in this application achieve the technical effect of improving the flexibility of multi-protocol adaptation and realizing dynamic and precise adjustment of the charging interaction process to ensure charging stability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating the new energy vehicle charging interface adaptation method based on multi-protocol conversion provided in the embodiments of this application.

[0018] Figure 2 This is a schematic diagram of the structure of a new energy vehicle charging interface adaptation system based on multi-protocol conversion provided in an embodiment of this application.

[0019] Figure labeling: 10 Multi-protocol interaction data acquisition module, 20 Protocol behavior level decomposition module, 30 Charging interaction semantic intermediate state model generation module, 40 Semantic continuity verification module, 50 Interaction parameter progressive adjustment module. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] This application provides a method for adapting new energy vehicle charging interfaces based on multi-protocol conversion, such as... Figure 1 As shown, the method includes: Step S100: During the process of establishing a charging connection between the new energy vehicle and the charging equipment, multi-protocol interaction data is collected to characterize the charging interaction process. The multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and status feedback information of the charging process.

[0022] Specifically, after the physical layer of the charging connection is established, the embedded data acquisition module is activated. This module integrates a CAN bus data acquisition unit, an electrical parameter sensing unit, and a status feedback information receiving unit. The CAN bus data acquisition unit collects charging protocol interaction messages at preset intervals, including protocol handshake frames, power negotiation frames, and safety status frames. The electrical parameter sensing unit collects electrical interface status parameters such as voltage, current, and temperature in real time. The status feedback information receiving unit receives status feedback information from the vehicle's battery management system (BMS) and the charging pile's main control unit, including charging preparation completion signals and fault alarm signals. All collected data is stored in a local cache database in a timestamp-data type-data content format.

[0023] For example, during the connection establishment process between a new energy vehicle and a national standard charging pile, the data acquisition module collects the handshake request frame sent by the charging pile at 0ms and the handshake response frame from the vehicle at 10ms. Simultaneously, the electrical parameter sensing unit collects the interface voltage as 220V and the current as 0A at 5ms, and the interface temperature as 25℃ at 20ms. The status feedback information receiving unit receives the charging preparation completion signal sent by the vehicle's BMS at 30ms. All data, along with their corresponding timestamps, is stored in a cache database.

[0024] Step S200: Perform protocol behavior-level decomposition of the multi-protocol interaction data to establish interaction behavior segments representing energy requests, security constraints, and control responses.

[0025] Specifically, the protocol behavior decomposition employs a two-layer decomposition logic based on rule matching of protocol function codes and time window association. The tool is an embedded data processing module with a built-in standard charging protocol function code dictionary. Parameters include time window thresholds and function code matching confidence thresholds. Specifically, the protocol function code dictionary is initialized, pre-stored with mapping relationships between function codes and behavior types of mainstream charging protocols such as GB / T27930, CCS, and CHAdeMO. For example, function code 0x01 maps to energy request behavior, 0x02 to safety constraint behavior, and 0x03 to control response behavior. Time window thresholds and function code matching confidence thresholds are set. The data processing module extracts and matches function codes from protocol interaction messages in the cache database. When the function code matching confidence is greater than or equal to the confidence threshold, the behavior type corresponding to the message is determined. Using the timestamp of a successfully matched protocol message as a benchmark, a time window is defined according to the time window threshold. For example, if the time window threshold is 100ms, a ±50ms time window is defined. The electrical interface status parameters and status feedback information collected within this window are associated and bound with the protocol message. The bound data sets are classified according to behavior type, and behavior type identifier, time window range, and associated data index are added to each data set. Finally, three types of interactive behavior fragments are generated: energy request, security constraint, and control response.

[0026] Step S300: Construct corresponding charging interaction semantic units using the interactive behavior fragments, and combine the charging interaction semantic units according to the charging process stages and time sequence to form a charging interaction semantic intermediate state model that represents the joint charging behavior state of the current charging stage. The charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process.

[0027] Specifically, a behavior-semantic mapping rule base is constructed to clarify the mapping relationship between three types of interactive behavior fragments and semantic units. Specifically, energy request behavior fragments are mapped to energy demand semantic units, including three semantic attributes: demand power, demand duration, and power change rate. Safety constraint behavior fragments are mapped to safety threshold semantic units, including four semantic attributes: voltage upper limit, current upper limit, temperature upper limit, and insulation resistance threshold. Control response behavior fragments are mapped to control command semantic units, including three semantic attributes: command type, command execution parameters, and command response timeout. The charging process is divided into four stages: charging preparation stage, power increase stage, constant power stage, and power decrease stage, with time interval identifiers set for each stage. Semantic units are layered and combined according to a combination rule: within the same stage, they are arranged chronologically, with safety threshold semantic units as the basic layer, energy demand semantic units as the target layer, and control command semantic units as the execution layer. A doubly linked list structure is used to construct the intermediate semantic model of charging interaction. Each node of the linked list corresponds to a combination of semantic units of a charging process stage. The dynamic update trigger condition of the model is set as follows: when a new interactive behavior fragment is received and the stage to which the fragment belongs is consistent with the current stage of the model node, when the update is triggered, the old data of the corresponding node in the linked list is replaced with the new semantic unit.

[0028] Step S400: During the charging process, the charging interaction semantic intermediate state model is dynamically updated, and the semantic continuity of the evolution relationship between adjacent semantic states is verified based on the reversible mapping chain.

[0029] Specifically, the model update cycle is set to be consistent with the charging interaction cycle, for example, both being 200ms. At the beginning of each cycle, newly collected interaction behavior fragments are read and converted into semantic units. The corresponding nodes in the model linked list are matched using the stage identifier of the semantic unit, and the node data is updated using an overwrite method to complete the dynamic model update. A reversible mapping chain is initialized, which contains a set of forward semantic projection operators and a set of backward semantic backtracking operators, and has a built-in semantic state evolution rule library. The joint semantic state of two adjacent cycles in the updated model is extracted, denoted as the previous semantic state and the current semantic state. The semantic continuity verification module of the reversible mapping chain is called to calculate the evolution distance between the two states in the three dimensions of energy, safety, and control. The evolution distance calculation formula is: Where D = {energy, security, control} are three evolutionary dimensions. It is the attribute value of dimension d in the current semantic state. It is the attribute value of dimension d in the preceding semantic state. These are the weighting coefficients for dimension d. An evolutionary distance threshold is set; if the calculated evolutionary distance is less than or equal to the threshold, the expression is considered semantically continuous; otherwise, it is considered semantically discontinuous.

[0030] In one possible implementation, the reversible mapping chain is a hierarchical bidirectional semantic evolution constraint structure constructed for the charging interaction semantic intermediate state model. Step S400 further includes step S410, which involves structurally decomposing the joint semantic state in the charging interaction semantic intermediate state model to obtain a multi-dimensional semantic sub-state set including energy request sub-state, safety constraint sub-state, and control rhythm sub-state. Each semantic sub-state corresponds to a set of protocol fields of different granularities under different charging protocols. Specifically, a tree-structure decomposition method is used, with the joint semantic state as the root node, divided into three first-level sub-nodes according to the energy-safety-control dimension, corresponding to the energy request sub-state, safety constraint sub-state, and control rhythm sub-state, respectively. Each first-level sub-node is further subdivided: the energy request sub-state is subdivided into three second-level sub-nodes: demand power, demand duration, and power change rate; the safety constraint sub-state is subdivided into four second-level sub-nodes: voltage limit, current limit, temperature limit, and insulation resistance threshold; and the control rhythm sub-state is subdivided into three second-level sub-nodes: command sending cycle, command response timeout time, and command retry count. A protocol field mapping table is constructed, storing the correspondence between secondary semantic sub-states and protocol frame fields under different charging protocols. For example, in the national standard protocol, the required power corresponds to bytes 0x03-0x06 of the protocol frame, and the voltage limit corresponds to bytes 0x07-0x0A. A protocol field identifier is added to each secondary child node, ultimately forming a multi-dimensional semantic sub-state set with a three-level structure.

[0031] Step S420: Based on the multidimensional semantic sub-state set, multiple sets of forward semantic projection operators are constructed to project different semantic sub-states into candidate protocol control states according to the field organization rules of the target charging protocol. Different forward semantic projection operators correspond to different protocol understanding assumptions and field combination logics. Specifically, for target charging protocols, including national standards, CCS, and CHAdeMO, forward semantic projection operators are constructed. Each set of operators includes three core modules: protocol field organization rules, semantic attribute-field mapping relationship, and field value conversion function. The field value conversion function uses a linear mapping formula: Protocol field value = Semantic attribute value × Conversion coefficient + Offset. The conversion coefficient and offset are determined according to the protocol specification. For example, in the national standard protocol, the power conversion coefficient is 1 and the offset is 0, and the voltage conversion coefficient is 0.1 and the offset is 0. The multidimensional semantic sub-state set is input to the forward projection operator of the corresponding protocol. The operator calls the conversion function according to the mapping relationship to convert the attribute value of each secondary semantic sub-state into a protocol frame field value. Following the protocol field organization rules, the converted field values ​​are arranged in a fixed order, and a frame header, function code, checksum, and frame trailer are added to generate a complete protocol control frame. The protocol control frame is then combined with corresponding execution parameters, including transmission period and retries, to form a candidate protocol control state.

[0032] Step S430: During the execution of the target charging protocol, electrical responses, status confirmations, and anomaly feedback information triggered by the candidate protocol control state are collected in real time. The real-time collection results are then re-embedded into the charging interaction semantic intermediate state model to form a semantic-execution coupled evolutionary state. Specifically, the candidate protocol control state is sent to the charging pile and the vehicle's BMS, and the execution feedback collection module is started. This module includes an electrical parameter sensing unit, a protocol confirmation frame receiving unit, and an anomaly monitoring unit. The collection frequency of electrical parameters is set, and parameters such as the output voltage, current, power, and temperature of the charging pile are collected. The protocol confirmation frame reception timeout time is set, and information such as frame reception confirmation and instruction execution success confirmation returned by the charging pile and BMS is received. The anomaly monitoring unit monitors abnormal signals such as overvoltage, overcurrent, and communication timeout in real time. The collected feedback information is standardized and organized according to the format of candidate protocol control state ID-feedback type-feedback content-timestamp. The model embedding interface is called to add an execution feedback attribute field to the corresponding node of the charging interaction semantic intermediate state model, and the organized feedback information is written into this field. The updated model nodes contain semantic attributes and execution feedback attributes, forming a semantic-execution coupled evolutionary state.

[0033] Step S440: Construct a reverse semantic backtracking operator based on the semantic-execution coupling evolution state, and use the reverse semantic backtracking operator to perform constraint optimization of the forward semantic projection operator to establish a reversible mapping chain. Specifically, the reverse semantic backtracking operator is constructed, which includes a protocol field reverse parsing module, a semantic attribute recovery module, and a parameter optimization module. The input is the execution feedback information of the candidate protocol control state, and the output is the recovered semantic sub-state set. The protocol field reverse parsing module converts the electrical parameters in the execution feedback into corresponding semantic attribute candidate values ​​according to the protocol field mapping table. The conversion formula is: semantic attribute candidate value = (feedback parameter - offset) / conversion coefficient. The semantic attribute recovery module calculates the deviation rate between the candidate value and the original semantic attribute value. The deviation rate = |candidate value - original value| / original value × 100%. A deviation rate threshold is set. When the deviation rate ≤ the deviation rate threshold, the candidate value is directly used as the recovered semantic attribute value. When the deviation rate > the deviation rate threshold, a weighted average method is used to correct the candidate value. The parameter optimization module adjusts the transformation coefficients and offsets of the forward semantic projection operator based on the deviation rate. The adjustment formulas are: new transformation coefficient = original transformation coefficient × (1 - deviation rate × 0.1), new offset = original offset × (1 - deviation rate × 0.1). The optimized forward projection operator is then bidirectionally bound to the reverse backtracking operator. The trigger condition is set as follows: after the forward projection generates the control state, the reverse backtracking parsing is automatically triggered. After the reverse backtracking is completed, the forward operator parameters are automatically optimized, ultimately forming a reversible mapping chain.

[0034] In one possible implementation, the inverse semantic backtracking operator is used to perform constraint optimization of the forward semantic projection operator to establish a reversible mapping chain. Step S440 further includes step S441, which uses the inverse semantic backtracking operator to perform reverse parsing of the candidate protocol control state and its corresponding execution feedback to recover the updated semantic sub-state set corresponding to the semantic level after protocol execution. Specifically, the protocol field reverse parsing module of the inverse semantic backtracking operator is called to load the protocol field mapping table and clarify the semantic sub-state type corresponding to each field in the candidate protocol control state. The protocol field values ​​and corresponding execution feedback parameters of the candidate protocol control state are extracted, such as power field values, voltage field values, actual output power, and actual output voltage. The feedback correction coefficient is calculated, where the correction coefficient = actual execution parameter / protocol field value. The updated semantic attribute value is converted into the corresponding semantic attribute value using the formula: updated semantic attribute value = protocol field value × feedback correction coefficient. The converted semantic attribute values ​​are integrated according to the dimensions of energy request, safety constraints, and control rhythm to generate the updated semantic sub-state set.

[0035] Step S442: Within the same mapping period, perform semantic closed-loop consistency analysis on the semantic sub-state set before forward semantic projection and the updated semantic sub-state set after recovery by the reverse semantic backtracking operator, generating a semantic consistency constraint index characterizing the semantic preservation capability of the reversible mapping chain in the current charging phase. Specifically, the time range of the mapping period is determined to be from the moment the forward projection operator generates the candidate protocol control state to the moment the reverse backtracking operator recovers the updated semantic sub-state set. Extract the original semantic sub-state set and the updated semantic sub-state set within this period, and compare the corresponding second-level semantic attribute values ​​in the two sets one by one. Calculate the single-attribute consistency score using the formula: Single-attribute score = 1 - |Updated value - Original value| / Original value, and set a single-attribute score threshold. Calculate the overall consistency score using the weighted summation formula: Overall score = Σ(Single-attribute score × Attribute weight). The overall consistency score is used as a semantic consistency constraint indicator. For example, when the overall score is ≥0.9, it is judged as good consistency; when 0.8≤overall score<0.9, it is judged as average consistency; and when the overall score<0.8, it is judged as poor consistency.

[0036] Step S443: The semantic consistency constraint index is used to jointly constrain the selection of the forward semantic projection operator, the activation order of the mapping path, and the adjustment range of the protocol interaction parameters to construct a reversible mapping chain. Specifically, a mapping table between the semantic consistency constraint index and the operator optimization strategy is established, clarifying the optimization measures corresponding to different score ranges. For example: when the overall score is ≥0.9, the parameters and mapping path of the current forward projection operator remain unchanged; when 0.8≤overall score<0.9, the activation order of the mapping path is adjusted, prioritizing the mapping path with a low deviation rate; when the overall score<0.8, the adjustment range of the protocol interaction parameters is adjusted, increasing the parameter adjustment step size. For the adjustment of the mapping path activation order, a path priority evaluation model is constructed. The model input is the historical consistency score of each mapping path, and the output is the path priority ranking, prioritizing the activation of paths with higher priority. For the adjustment of the parameter adjustment range, a correlation rule between the adjustment step size and the consistency score is set: step size = original step size × [1 - (0.9 - overall score) × 2]. The optimized forward projection operator and the backward backtracking operator are bound in a closed loop, and a cyclic triggering logic of forward projection-execution feedback-backtracking-operator optimization-forward projection is set. The reversibility of the mapping chain is verified. The verification standard is that the deviation rate between the semantic state recovered from the control state generated by forward projection and the original state after backward backtracking is ≤ the deviation rate threshold. After the verification is passed, the construction of the reversible mapping chain is completed.

[0037] In one possible implementation, based on the reversible mapping chain, the semantic continuity verification of the evolutionary relationship between adjacent semantic states is performed. Step S400 further includes step S450, whereby, during the charging process, using the charging interaction semantic intermediate state model as a unified semantic carrier, a first joint semantic state and a second joint semantic state are generated in two adjacent charging interaction cycles, respectively. Both the first and second joint semantic states are obtained by mapping interactive behavior fragments through a forward semantic projection operator and correcting them through a reverse semantic backtracking operator. Specifically, a charging interaction cycle is set, and a cycle number identifier is added to each node of the semantic intermediate state model. After completing the forward projection and reverse backtracking correction of the nth cycle, the joint semantic state of that cycle is extracted. This state contains complete semantic attributes and execution feedback attributes in three dimensions: energy, safety, and control, and is marked as the first joint semantic state. After completing the forward projection and reverse backtracking correction of the (n+1)th cycle, the joint semantic state of that cycle is extracted using the same method and marked as the second joint semantic state. The validity of two joint semantic states is verified. The verification criteria are that the number of semantic attributes contained in the state is complete, the execution feedback attribute is not empty, and the consistency score is greater than or equal to the consistency score threshold. After the verification is passed, the state is stored in the comparison sample database.

[0038] Step S460: Based on the reversible mapping chain, perform semantic forward prediction on the first joint semantic state along the forward semantic projection path to construct the expected evolutionary semantic state. Specifically, call the semantic evolution prediction module of the reversible mapping chain. This module has a built-in semantic state transition probability model based on Markov chains, and the state transition matrix of the model is obtained through training with historical charging data. Input the first joint semantic state into the prediction module. The module calculates the transition probability of each semantic attribute according to the state transition matrix. For example, the probability of energy demand remaining unchanged from 60kW is 0.7, the probability of decreasing to 55kW is 0.2, and the probability of increasing to 65kW is 0.1. Select the attribute value combination with the highest transition probability as the attribute value of the expected evolutionary semantic state. Calculate the confidence of the expected state, which is the product of the transition probabilities of each semantic attribute.

[0039] Step S470: The expected evolutionary semantic state is compared with the second joint semantic state to generate a semantic continuity verification result. The consistency comparison includes energy semantic continuity dimension comparison, safety semantic preservation dimension comparison, forward-backward semantic closed-loop consistency dimension comparison, semantic evolution path consistency dimension comparison, and semantic evolution rate consistency dimension comparison. Specifically, five dimensions for consistency comparison are determined: energy semantic continuity dimension, safety semantic preservation dimension, forward-backward semantic closed-loop consistency dimension, semantic evolution path consistency dimension, and semantic evolution rate consistency dimension. Comparison indicators and thresholds are set for each dimension. Specifically, the energy semantic dimension compares the deviation rate between actual power and expected power; the safety semantic dimension compares the deviation rate between actual voltage / current and expected values; the semantic closed-loop dimension compares the deviation value between forward projection and backward backtracking; the evolution path dimension compares the overlap between the actual evolution path and the expected path; and the evolution rate dimension compares the deviation between the actual power change rate and the expected rate. The comparison results of the five dimensions are comprehensively judged. When all dimensions meet the threshold requirements, a semantically continuous verification result is generated; when any dimension does not meet the threshold, a semantically discontinuous verification result is generated, and the dimension that does not meet the threshold is marked.

[0040] Step S500: Based on the semantic continuity verification result, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain.

[0041] Specifically, a mapping relationship is established between semantic continuity verification results and parameter adjustment strategies: when the verification result is semantically continuous, the current protocol interaction parameters remain unchanged; when the verification result is semantically discontinuous, the corresponding adjustment parameters are determined based on the dimension that is not satisfied. A progressive adjustment rule is set, for example, the single adjustment step size does not exceed 5% of the current parameter value to avoid sudden parameter changes that could lead to charging anomalies. The parameter adjustment module of the reversible mapping chain is invoked. This module calculates the adjustment direction and magnitude of the parameters based on the adjustment strategy and step size rules. The adjustment direction is determined by the semantic deviation direction; for example, when the actual power is lower than the expected power, the adjustment direction is to reduce the power request parameter. The adjusted parameters are then sent to the charging pile and the vehicle's BMS to initiate semantic acquisition and verification for the next charging interaction cycle. This verification-adjustment-re-verification process is repeated until the semantic continuity verification result is semantically continuous, ensuring that the execution state of the charging protocol remains consistent with the semantic state, thus achieving adaptation to multi-protocol charging interfaces.

[0042] In one possible implementation, based on the semantic continuity verification result, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain. Step S500 further includes step S510, using the semantic continuity verification result as the closed-loop control input of the reversible mapping chain to determine the adjustability of the protocol interaction parameter set corresponding to the current forward semantic projection operator. The protocol interaction parameter set includes at least power request parameters, voltage and current limit parameters, and interaction timing parameters. Specifically, the protocol interaction parameter set corresponding to the current forward semantic projection operator is extracted, including power request parameters, voltage and current limit parameters, and interaction timing parameters. A parameter adjustability determination rule base is constructed, containing three core constraints: first, the parameter adjustment range must be within the threshold allowed by the device hardware, for example, the adjustment range of the power request parameter is 0 to the rated power of the charging pile; second, the parameter adjustment step size must comply with the protocol specification requirements, for example, the national standard protocol stipulates that the power adjustment step size is not less than 1kW; third, the parameter adjustment will not trigger a safety protection mechanism, for example, the voltage adjustment will not fall below the minimum allowable voltage of the vehicle's BMS. The semantic continuity verification result is input into the adjustability determination module. The module judges the adjustability of each parameter in the parameter set one by one according to the rule base, and generates a parameter adjustability list. The list marks adjustable, non-adjustable and the corresponding constraint reasons.

[0043] Step S520: When the semantic continuity verification result indicates a trend of deviation from the expected semantic evolution path between adjacent semantic states, the semantic sub-state category causing the deviation is determined based on the reversible mapping chain, and an adjustable subset of protocol interaction parameters is configured. Specifically, the semantic state association analysis module of the reversible mapping chain is invoked to associate the dimension of semantic deviation with the semantic sub-state category. For example, deviation in the energy semantic dimension corresponds to the energy request sub-state, and deviation in the safety semantic dimension corresponds to the safety constraint sub-state. A semantic sub-state-protocol parameter mapping table is constructed to clarify the protocol interaction parameters corresponding to each type of semantic sub-state. For example, the energy request sub-state corresponds to the power request parameter and the power change rate parameter, and the safety constraint sub-state corresponds to the voltage and current limit parameter and the temperature threshold parameter. According to the sub-state category corresponding to the semantic deviation, the corresponding parameter subset is selected from the protocol interaction parameter set. Causal verification is performed on the selected parameter subset. By analyzing historical data, it is verified whether there is a direct causal relationship between the value of the parameter subset and the semantic deviation. If the verification is successful, it is determined as the protocol interaction parameter subset to be adjusted.

[0044] Step S530: Within the adjustable subset of protocol interaction parameters, based on the semantic deviation degree corresponding to the semantic continuity verification result, determine the single adjustment step size and adjustment direction of the protocol interaction parameters, and perform gradual adjustment. Specifically, calculate the quantitative index of semantic deviation degree using the formula: Deviation degree = |Actual semantic attribute value - Expected semantic attribute value| / Expected semantic attribute value × 100%. Establish a mapping rule between deviation degree and adjustment step size. For example, when the deviation degree ≤ 5%, the single adjustment step size is 2% of the current parameter value; when 5% < deviation degree ≤ 10%, the single adjustment step size is 5% of the current parameter value; when the deviation degree > 10%, the single adjustment step size is 8% of the current parameter value, and the single adjustment step size does not exceed the maximum allowable step size of the protocol specification. Determine the parameter adjustment direction based on the direction of semantic deviation: when the actual value is less than the expected value, the parameter adjustment direction is to decrease; when the actual value is greater than the expected value, the adjustment direction is to increase. According to the calculated adjustment step size and direction, the parameters in the adjustable protocol interaction parameter subset are adjusted to generate new parameter values, which are then sent to the charging device for execution. This avoids abnormal charging process caused by sudden parameter changes. At the same time, the adjustment time, adjustment range, and parameter values ​​before and after the adjustment are recorded.

[0045] In one possible implementation, step S500 further includes step S540, after reading the current charging process stage, establishing stage constraints, the stage constraints including the priority and adjustment range limit of protocol interaction parameters, and performing progressive adjustment constraint compensation according to the stage constraints.

[0046] Specifically, the current charging process is divided into four stages: charging preparation, power increase, constant power, power decrease, and charging completion. A stage constraint rule base is established for each stage, clearly defining the priority and adjustment range limits for parameter adjustments. For example: in the charging preparation stage, the adjustment priority is interactive timing parameters > safety constraint parameters > energy request parameters, with an adjustment range limit of ≤3%; in the power increase stage, the priority is energy request parameters > safety constraint parameters > interactive timing parameters, with an adjustment range limit of ≤5%; in the constant power stage, the priority is safety constraint parameters > energy request parameters > interactive timing parameters, with an adjustment range limit of ≤2%; in the power decrease stage, the adjustment priority is the same as in the power increase stage, with an adjustment range limit of ≤5%; in the charging completion stage, adjusting energy request parameters is prohibited, only adjusting interactive timing parameters is allowed, with an adjustment range limit of ≤1%. During parameter adjustment, the constraint compensation module is invoked to compensate for the adjustment priority and range according to the constraint rules of the current stage, ensuring that the parameter adjustments meet the operational requirements of different charging stages. For example, if the originally planned adjustment range exceeds the stage limit, the range is reduced to the limit value. The compensated adjustment strategy is executed, and the adjusted parameters are verified to meet the stage's operational requirements.

[0047] In one possible implementation, step S500 further includes step S550, performing early warning trigger analysis based on the semantic continuity verification result, configuring an early warning signal, and managing anomaly reporting based on the early warning signal.

[0048] Specifically, a mapping relationship is established between semantic continuity scores and warning levels. For example, a score ≥ 0.9 indicates no warning; 0.8 ≤ score < 0.9 indicates a Level 1 warning; 0.7 ≤ score < 0.8 indicates a Level 2 warning; and a score < 0.7 indicates a Level 3 warning. Based on the warning level of the verification results, warning signals are configured with the following format: Warning Level - Anomaly Dimension - Occurrence Time - Device Identifier. An anomaly reporting management module is constructed to classify, store, and push warning signals, promptly reminding the system to take countermeasures to ensure charging safety. For example, Level 1 warning signals are stored in the general log; Level 2 warning signals are pushed to the system monitoring interface; and Level 3 warning signals trigger an audible and visual alarm and record anomaly details. Statistical analysis of anomaly reporting data is performed regularly to optimize the threshold and parameter adjustment strategies for semantic continuity verification. For example, the trigger threshold for Level 2 warnings is adjusted from 0.8 to 0.78 to reduce the false alarm rate.

[0049] In one possible implementation, the interaction parameters of the target charging protocol are progressively adjusted based on a reversible mapping chain according to the semantic continuity verification results. The method further includes step S600: performing continuous charging interaction cycle monitoring with progressive adjustment to establish cycle feedback. Specifically, the number of continuous monitoring cycles is set, the cycle monitoring module is started, and semantic continuity verification results, protocol execution parameters, and device status information are collected in each monitoring cycle. The collected data is organized according to the format of cycle number-verification result-execution parameter-device status-timestamp to establish a cycle feedback data set. Update rules for the data set are set; after each monitoring cycle is completed, the earliest cycle data is automatically removed to ensure that the data set always contains the latest cycle data. The cycle feedback data set is analyzed in real time to calculate the number and proportion of semantic discontinuities within continuous cycles.

[0050] Step S700: If the semantic continuity verification results of the periodic feedback within a preset continuous period do not meet the verification threshold, a rollback safety protection mechanism is triggered. Specifically, a rollback trigger threshold condition is set, for example, the number of semantic discontinuities occurring ≥ 4 times in 5 consecutive charging interaction cycles. The periodic feedback data set is monitored in real time to determine whether the threshold condition is met. When the condition is met, the rollback safety protection mechanism is immediately triggered to terminate the current parameter adjustment strategy in a timely manner, preventing the abnormal aggravation of the charging process. Specifically, the following operations are performed: pausing the current protocol interaction parameter adjustment process; recording the charging status parameters when the rollback is triggered; sending a rollback command to the charging pile and the vehicle BMS, with the command content being: stop parameter adjustment and restore the parameter values ​​to the previous stable state. The reason for triggering the rollback, the time, the status parameters, and other information are stored in the safety log database.

[0051] Step S800: Perform interactive parameter rollback processing according to the rollback safety protection mechanism. Specifically, extract the parameter values ​​of the previous stable state from the safety log library. The criteria for determining a stable state are semantic continuity for three consecutive charging cycles and no abnormalities in the device status. Call the parameter rollback execution module to send the extracted stable parameter values ​​to the charging pile and the vehicle's BMS. The sent parameters include power request parameters, voltage and current limit parameters, and interactive timing parameters. Initiate the rollback verification process. In the next few charging interaction cycles, collect the semantic continuity verification results and device status information. If the semantic continuity verification results are both continuous and the device has no abnormal signals, the criteria are met, and the rollback is considered successful. If the criteria are not met, rollback is performed again to an earlier stable state parameter value until the charging state is stable. By restoring the stable operation of the charging process, charging safety is ensured. Record the entire process information of parameter rollback, including parameter values ​​before and after rollback, rollback time, and verification results.

[0052] This application employs a multi-protocol interaction data collection process during the establishment of a charging connection between a new energy vehicle and a charging device. This data includes charging protocol interaction messages, electrical interface status parameters, and status feedback information. The data is then decomposed at the protocol behavior level to obtain energy request, safety constraint, and control response interaction behavior fragments. Based on these fragments, charging interaction semantic units are constructed and combined according to the charging process stages and time sequence to form a dynamically updated charging interaction semantic intermediate state model. This model is dynamically updated during the charging process, and the continuity of adjacent semantic state evolution is verified based on a reversible mapping chain. Based on the verification results, the interaction parameters of the target charging protocol are progressively adjusted through the reversible mapping chain. This approach solves the technical problems of insufficient adaptation flexibility and lack of dynamic interaction adjustment in existing new energy vehicle charging interface adaptations. It achieves the technical effect of improving the flexibility of multi-protocol adaptation and realizing dynamic and precise adjustment of the charging interaction process to ensure charging stability.

[0053] In the above text, refer to Figure 1 This paper describes in detail a new energy vehicle charging interface adaptation method based on multi-protocol conversion according to embodiments of the present invention. Next, reference will be made to... Figure 2 This invention describes a new energy vehicle charging interface adaptation system based on multi-protocol conversion according to an embodiment of the present invention.

[0054] The new energy vehicle charging interface adaptation system based on multi-protocol conversion according to embodiments of the present invention addresses the technical problems of insufficient adaptation flexibility and lack of dynamic interactive adjustment in existing new energy vehicle charging interface adaptations, achieving the technical effect of improving multi-protocol adaptation flexibility and realizing dynamic and precise adjustment of the charging interaction process to ensure charging stability. The new energy vehicle charging interface adaptation system based on multi-protocol conversion includes: a multi-protocol interaction data acquisition module 10, a protocol behavior-level decomposition module 20, a charging interaction semantic intermediate state model generation module 30, a semantic continuity verification module 40, and a progressive adjustment module for interaction parameters 50.

[0055] The multi-protocol interaction data acquisition module 10 is used to collect multi-protocol interaction data to characterize the charging interaction process during the establishment of a charging connection between the new energy vehicle and the charging equipment. The multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and charging process status feedback information. The protocol behavior-level decomposition module 20 is used to perform protocol behavior-level decomposition of the multi-protocol interaction data and establish interaction behavior fragments characterizing energy requests, safety constraints, and control responses. The charging interaction semantic intermediate state model generation module 30 is used to construct corresponding charging interaction semantic units using the interaction behavior fragments and according to the charging process stages. The charging interaction semantic units are combined with the time sequence to form a charging interaction semantic intermediate state model that represents the joint charging behavior state of the current charging stage. The charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process. The semantic continuity verification module 40 is used to dynamically update the charging interaction semantic intermediate state model during the charging process and perform semantic continuity verification of the evolution relationship between adjacent semantic states based on the reversible mapping chain. The interaction parameter progressive adjustment module 50 is used to progressively adjust the interaction parameters of the target charging protocol based on the reversible mapping chain according to the semantic continuity verification results.

[0056] The detailed description of the specific configuration of the semantic continuity verification module 40 is explained as follows: As mentioned above, the reversible mapping chain is a hierarchical bidirectional semantic evolution constraint structure for constructing a charging interaction semantic intermediate state model. The semantic continuity verification module 40 may further include: a structured decomposition unit for structurally decomposing the joint semantic states in the charging interaction semantic intermediate state model to obtain a multidimensional semantic sub-state set including energy request sub-states, safety constraint sub-states, and control rhythm sub-states, wherein each semantic sub-state corresponds to a protocol field set of different granularities under different charging protocols; and a forward semantic projection operator construction unit for constructing multiple sets of forward semantic projections based on the multidimensional semantic sub-state set. The operator projects different semantic sub-states into candidate protocol control states according to the field organization rules of the target charging protocol. Different forward semantic projection operators correspond to different protocol understanding assumptions and field combination logic. The real-time information acquisition unit is used to collect electrical response, status confirmation and abnormal feedback information triggered by the candidate protocol control state in real time during the execution of the target charging protocol. The real-time acquisition results are re-embedded into the charging interaction semantic intermediate state model to form a semantic-execution coupled evolution state. The reversible mapping chain establishment unit is used to construct a reverse semantic backtracking operator based on the semantic-execution coupled evolution state, and use the reverse semantic backtracking operator to perform constraint optimization of the forward semantic projection operator to establish a reversible mapping chain.

[0057] Specifically, the reverse semantic backtracking operator is used to optimize the constraints of the forward semantic projection operator to establish a reversible mapping chain. The reversible mapping chain establishment unit may further include: a reverse parsing subunit used to perform reverse parsing on the candidate protocol control state and its corresponding execution feedback using the reverse semantic backtracking operator to recover the updated semantic sub-state set corresponding to the semantic level after protocol execution; a semantic closed-loop consistency analysis subunit used to perform semantic closed-loop consistency analysis on the semantic sub-state set before forward semantic projection and the updated semantic sub-state set recovered by the reverse semantic backtracking operator within the same mapping cycle to generate a semantic consistency constraint index characterizing the semantic maintenance capability of the reversible mapping chain in the current charging stage; and a joint constraint subunit used to use the semantic consistency constraint index to jointly constrain the selection of the forward semantic projection operator, the activation order of the mapping path, and the adjustment range of the protocol interaction parameters to construct the reversible mapping chain.

[0058] The semantic continuity verification module 40, which performs semantic continuity verification based on the reversible mapping chain to perform evolutionary relationship verification between adjacent semantic states, may further include: a joint semantic state generation unit, which generates a first joint semantic state and a second joint semantic state respectively in two adjacent charging interaction cycles during the charging process, using the charging interaction semantic intermediate state model as a unified semantic carrier; the first joint semantic state and the second joint semantic state are both obtained by mapping the interaction behavior fragment through a forward semantic projection operator and correcting it through a reverse semantic backtracking operator; a semantic forward prediction unit, which performs semantic forward prediction on the first joint semantic state along the forward semantic projection path based on the reversible mapping chain to construct the expected evolutionary semantic state; and a consistency comparison unit, which performs a consistency comparison between the expected evolutionary semantic state and the second joint semantic state to generate a semantic continuity verification result.

[0059] The consistency comparison unit may further include: consistency comparison includes energy semantic continuity dimension comparison, security semantic preservation dimension comparison, forward-backward semantic closed loop consistency dimension comparison, semantic evolution path consistency dimension comparison, and semantic evolution rate consistency dimension comparison.

[0060] The detailed description of the specific configuration of the progressive adjustment module 50 for interaction parameters is explained as follows: As mentioned above, the progressive adjustment of the interaction parameters of the target charging protocol is performed based on the semantic continuity verification result and the reversible mapping chain. The progressive adjustment module 50 for interaction parameters may further include: an adjustability determination unit used to use the semantic continuity verification result as the closed-loop control input of the reversible mapping chain to determine the adjustability of the protocol interaction parameter set corresponding to the current forward semantic projection operator, wherein the protocol interaction parameter set includes at least power request parameters, voltage and current limit parameters, and interaction timing parameters; a protocol interaction parameter subset configuration unit used to determine the semantic sub-state category causing the deviation based on the reversible mapping chain when the semantic continuity verification result indicates that there is a trend of deviation from the expected semantic evolution path between adjacent semantic states, and configure an adjustable protocol interaction parameter subset; and a progressive adjustment unit used to determine the single adjustment step size and adjustment direction of the protocol interaction parameters in the adjustable protocol interaction parameter subset according to the degree of semantic deviation corresponding to the semantic continuity verification result, and perform progressive adjustment.

[0061] The progressive adjustment module 50 for interactive parameters may further include: a constraint compensation unit for establishing stage constraints after reading the current charging process stage, wherein the stage constraints include the priority and adjustment range limit of the protocol interactive parameters, and progressive adjustment constraint compensation is performed according to the stage constraints.

[0062] The system, which progressively adjusts the interaction parameters of the target charging protocol based on a reversible mapping chain according to the semantic continuity verification results, may further include: a periodic feedback establishment module for performing continuous charging interaction period monitoring for progressive adjustment and establishing periodic feedback; a fallback safety protection mechanism triggering module for triggering a fallback safety protection mechanism if the semantic continuity verification results of the periodic feedback within a preset continuous period do not meet the verification threshold; and an interaction parameter fallback processing module for performing interaction parameter fallback processing according to the fallback safety protection mechanism.

[0063] The interactive parameter progressive adjustment module 50 may further include: performing early warning trigger analysis based on the semantic continuity verification result, configuring an early warning signal, and managing abnormal reporting based on the early warning signal.

[0064] The new energy vehicle charging interface adaptation system based on multi-protocol conversion provided in the embodiments of the present invention can execute the new energy vehicle charging interface adaptation method based on multi-protocol conversion provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0065] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0066] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for adapting charging interfaces for new energy vehicles based on multi-protocol conversion, characterized in that, The method includes: During the process of establishing a charging connection between a new energy vehicle and a charging device, multi-protocol interaction data is collected to characterize the charging interaction process. The multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and status feedback information of the charging process. The protocol behavior level of the multi-protocol interaction data is decomposed to establish interactive behavior fragments representing energy requests, security constraints, and control responses; The corresponding charging interaction semantic units are constructed using the interactive behavior fragments, and the charging interaction semantic units are combined according to the charging process stages and time sequence to form a charging interaction semantic intermediate state model that represents the joint charging behavior state of the current charging stage. The charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process. During the charging process, the charging interaction semantic intermediate state model is dynamically updated, and the semantic continuity of the evolution relationship between adjacent semantic states is verified based on the reversible mapping chain. Based on the semantic continuity verification results, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain.

2. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 1, characterized in that, The reversible mapping chain is a hierarchical bidirectional semantic evolution constraint structure constructed for a semantic intermediate state model oriented towards charging interaction, including: The joint semantic state in the charging interaction semantic intermediate state model is decomposed in a structured manner to obtain a multi-dimensional semantic sub-state set including energy request sub-state, safety constraint sub-state, and control rhythm sub-state. Each semantic sub-state corresponds to a set of protocol fields of different granularities under different charging protocols. Based on the multidimensional semantic sub-state set, multiple sets of forward semantic projection operators are constructed to project different semantic sub-states into candidate protocol control states according to the field organization rules of the target charging protocol. Different forward semantic projection operators correspond to different protocol understanding assumptions and field combination logic. During the execution of the target charging protocol, electrical response, status confirmation and abnormal feedback information triggered by the control state of the candidate protocol are collected in real time. The real-time collection results are then re-embedded into the charging interaction semantic intermediate state model to form a semantic-execution coupled evolution state. Based on the semantic-execution coupled evolution state, a reverse semantic backtracking operator is constructed. The reverse semantic backtracking operator is used to perform constraint optimization of the forward semantic projection operator to establish a reversible mapping chain.

3. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 2, characterized in that, Constraint optimization of the forward semantic projection operator using the inverse semantic backtracking operator to establish an invertible mapping chain includes: The reverse semantic backtracking operator is used to reverse-parse the candidate protocol control state and its corresponding execution feedback to recover the set of updated semantic sub-states at the semantic level after the protocol is executed; Within the same mapping cycle, semantic closed-loop consistency analysis is performed on the set of semantic sub-states before forward semantic projection and the set of updated semantic sub-states after recovery by the reverse semantic backtracking operator, generating a semantic consistency constraint index that characterizes the semantic preservation capability of the reversible mapping chain in the current charging stage. The semantic consistency constraint index is used to jointly constrain the selection of the forward semantic projection operator, the activation order of the mapping path, and the adjustment range of the protocol interaction parameters to construct a reversible mapping chain.

4. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 1, characterized in that, Semantic continuity verification based on the evolutionary relationship between adjacent semantic states, performed using an invertible mapping chain, includes: During the charging process, the charging interaction semantic intermediate state model is used as a unified semantic carrier. A first joint semantic state and a second joint semantic state are generated in two adjacent charging interaction cycles, respectively. The first joint semantic state and the second joint semantic state are obtained by mapping the interaction behavior fragments through the forward semantic projection operator and correcting them through the reverse semantic backtracking operator. Based on the reversible mapping chain, semantic forward prediction is performed on the first joint semantic state along the forward semantic projection path to construct the expected evolutionary semantic state; The expected evolutionary semantic state is compared with the second joint semantic state to generate a semantic continuity verification result.

5. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 4, characterized in that, Consistency comparison includes energy semantic continuity dimension comparison, security semantic preservation dimension comparison, forward-backward semantic closed loop consistency dimension comparison, semantic evolution path consistency dimension comparison, and semantic evolution rate consistency dimension comparison.

6. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 1, characterized in that, Based on the semantic continuity verification results, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain, including: Using the semantic continuity verification result as the closed-loop control input of the reversible mapping chain, the adjustability of the protocol interaction parameter set corresponding to the current forward semantic projection operator is determined, wherein the protocol interaction parameter set includes at least power request parameters, voltage and current limit parameters and interaction timing parameters. When the semantic continuity verification result indicates that there is a trend of deviation from the expected semantic evolution path between adjacent semantic states, the semantic sub-state category causing the deviation is determined based on the reversible mapping chain, and an adjustable subset of protocol interaction parameters is configured. Within the adjustable subset of protocol interaction parameters, based on the degree of semantic deviation corresponding to the semantic continuity verification result, the single adjustment step size and adjustment direction of the protocol interaction parameters are determined, and a gradual adjustment is performed.

7. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 6, characterized in that, After reading the current charging process stage, stage constraints are established, including the priority and adjustment range limit of protocol interaction parameters. Gradual adjustment constraint compensation is then performed based on the stage constraints.

8. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 1, characterized in that, Based on the semantic continuity verification results, the interaction parameters of the target charging protocol are progressively adjusted according to the reversible mapping chain, which also includes: Perform progressively adjusted continuous charging interaction cycle monitoring and establish cycle feedback; If the semantic continuity verification results of the periodic feedback within the preset continuous period do not meet the verification threshold, the fallback security protection mechanism is triggered. The interaction parameters are rolled back according to the rollback security protection mechanism.

9. The new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in claim 1, characterized in that, Based on the semantic continuity verification results, an early warning trigger analysis is performed, an early warning signal is configured, and anomaly reporting management is performed based on the early warning signal.

10. A new energy vehicle charging interface adaptation system based on multi-protocol conversion, characterized in that, The system is used to implement the new energy vehicle charging interface adaptation method based on multi-protocol conversion as described in any one of claims 1-9, and the system includes: The multi-protocol interaction data acquisition module is used to collect multi-protocol interaction data to characterize the charging interaction process during the process of establishing a charging connection between a new energy vehicle and a charging device. The multi-protocol interaction data includes charging protocol interaction messages, electrical interface status parameters, and status feedback information of the charging process. The protocol behavior-level decomposition module is used to perform protocol behavior-level decomposition of the multi-protocol interaction data and establish interaction behavior fragments that characterize energy requests, security constraints, and control responses. The charging interaction semantic intermediate state model generation module is used to construct corresponding charging interaction semantic units using the interaction behavior fragments, and to combine the charging interaction semantic units according to the charging process stage and time sequence to form a charging interaction semantic intermediate state model that represents the joint charging behavior state of the current charging stage. The charging interaction semantic intermediate state model is a joint semantic state representation that is dynamically updated with the charging process. The semantic continuity verification module is used to dynamically update the intermediate state model of the charging interaction semantics during the charging process, and to perform semantic continuity verification of the evolution relationship between adjacent semantic states based on the reversible mapping chain. The interaction parameter progressive adjustment module is used to progressively adjust the interaction parameters of the target charging protocol based on the semantic continuity verification results and the reversible mapping chain.

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