Charging operation method and device based on vehicle identification code and storage medium

Abstract

The invention relates to the field of new energy automobile power supply, and provides a charging operation method based on a vehicle identification code, and the method comprises the steps: obtaining a vehicle identification code VIN and a license plate number inputted by a user, building a binding relation between a vehicle corresponding to the VIN and an operation platform, taking the bound VIN as a user pre-stored VIN, and storing the VIN in a database of the operation platform; the operation platform generates a dynamic charging control instruction and issues the dynamic charging control instruction to the target charging pile based on the real-time power grid load data, the user charging demand and the vehicle battery parameter corresponding to the user pre-stored VIN; when the target charging pile executes the control instruction, battery state parameters and charging pile operation data of a vehicle BMS are collected in real time; the battery state parameters and the charging pile operation data are associated with a user pre-stored VIN, and charging parameters are dynamically adjusted through multi-dimensional data fusion analysis; after charging is completed, generating an encrypted settlement message based on a charging record associated with the VIN pre-stored by the user; and carrying out on-chain evidence storage on the encrypted settlement message through a block chain technology to complete expense settlement.

Description

Technical Field

[0001] This application relates to the field of power supply for new energy vehicles, and particularly to a charging operation method, device, and storage medium based on vehicle identification numbers. Background Art

[0002] With the rapid development of the new energy vehicle industry, the intelligent operation of charging infrastructure has become the core demand of the industry. The Vehicle Identification Number (VIN), as the unique identity identifier of a vehicle, plays key roles in vehicle identity verification, data association, and service matching in the charging scenario. The current mainstream charging operation systems usually achieve services based on the simple interaction between user accounts and charging piles. However, there are still significant bottlenecks in grid coordination, dynamic regulation, and data security.

[0003] In the prior art, most charging pile operation systems adopt the following solutions: the identity authentication link relies on single-factor verification of mobile terminals; the generation of charging instructions is mainly based on fixed strategies; the data collection during the charging process is stored separately from the user identity information; the settlement process relies on a centralized platform for processing.

[0004] The above technical defects lead to the following problems: the single authentication method is easily counterfeited and attacked, threatening charging security; the static instruction strategy is difficult to balance grid load and charging efficiency; the decentralized data storage structure hinders real-time regulation and optimization; the centralized settlement system is vulnerable to single-point failures. Therefore, there is an urgent need for an intelligent charging operation method that deeply integrates vehicle identity, dynamic regulation, and trusted settlement. Summary of the Invention

[0005] This application provides a charging operation method, device, and storage medium based on vehicle identification numbers, which can significantly improve charging security, optimize efficiency, and ensure the credibility of fees.

[0006] On the one hand, this application provides a charging operation method based on vehicle identification numbers, and the method includes: Establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identity identification number VIN and license plate number input by the user, and store the bound VIN as the user-prestored VIN in the database of the operation platform; The operation platform generates a dynamic charging control instruction based on real-time grid load data, user charging requirements, and the vehicle battery parameters corresponding to the user-prestored VIN, and sends it to the target charging pile; When the target charging pile executes the control instruction, it real-time collects the battery state parameters of the vehicle battery management system BMS and the operation data of the charging pile; Associate the battery status parameters and the charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; After charging is completed, generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN; Use blockchain technology to perform on-chain storage of the encrypted settlement message, and notify the user after the fee settlement is completed.

[0007] On the other hand, the present application provides a charging operation device based on a vehicle identification code, and the device includes: A binding module, configured to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform; A first generation module, configured to generate a dynamic charging control instruction based on real-time grid load data, user charging requirements, and the vehicle battery parameters corresponding to the user's pre-stored VIN by the operation platform, and send it to the target charging pile; An acquisition module, configured to collect the battery status parameters of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instruction; An association module, configured to associate the battery status parameters and the charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; A second generation module, configured to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; An on-chain storage module, configured to perform on-chain storage of the encrypted settlement message through blockchain technology, and notify the user after the fee settlement is completed.

[0008] In a third aspect, the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the technical solution of the above-mentioned charging operation method based on a vehicle identification code.

[0009] In a fourth aspect, the present application provides a storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the technical solution of the above-mentioned charging operation method based on a vehicle identification code.

[0010] As can be seen from the technical solutions provided by the present application described above, on the one hand, by performing two-way binding verification on the VIN input by the user and the vehicle hardware information obtained in real time by the charging pile, a dual-channel authentication mechanism is constructed, effectively preventing illegal users from accessing the charging system by forging account information, and improving the security of charging operations from the root cause. And based on the real-time power grid load data, user needs and vehicle battery parameters associated with the pre-stored VIN, control instructions are dynamically generated, enabling the charging strategy to synchronously respond to changes in the power grid state and vehicle characteristics, breaking through the limitations of traditional fixed strategies, and enhancing the power grid stability while ensuring the charging efficiency; on the other hand, by performing correlation analysis on the real-time operation data collected by the charging pile and the pre-stored VIN, a dynamic mapping relationship of identity-status-regulation is established, realizing the closed-loop optimization adjustment of charging parameters, and providing data support for solving safety hazards such as battery overheating and voltage anomalies; thirdly, blockchain technology is used to store the charging records associated with the VIN on the chain, and by utilizing its characteristics of decentralization and immutability, the integrity and auditability of the settlement data are ensured, effectively avoiding the risks of data leakage and single-point failure of traditional centralized settlement systems. In summary, the technical solutions of the present application can significantly improve the charging safety, optimization efficiency of the charging pile and ensure the credibility of the fees. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0012] Figure 1 is a flowchart of a charging operation method based on a vehicle identification code provided by an embodiment of the present application; Figure 2 is a schematic structural diagram of a charging operation device based on a vehicle identification code provided by an embodiment of the present application; Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0014] In this specification, adjectives such as first and second are only used to distinguish one element or action from another element or action, and do not necessarily require or imply any actual such relationship or order. Where circumstances permit, reference to an element or component or step (etc.) should not be construed as being limited to only one of the elements, components, or steps, but may be one or more of the elements, components, or steps, etc.

[0015] In this specification, for ease of description, the dimensions of the various parts shown in the drawings are not drawn in accordance with actual proportional relationships.

[0016] The Vehicle Identification Number (VIN) serves as the unique identity identifier for a vehicle and plays key roles such as vehicle identity verification, data association, and service matching in the charging scenario. Currently, the mainstream charging operation systems usually achieve services based on the simple interaction between the user account and the charging pile. However, there are still significant bottlenecks in aspects such as grid coordination, dynamic regulation, and data security. In the prior art, the charging pile operation systems mostly adopt the following solutions: (1) The identity authentication link relies on single-factor verification of the mobile terminal, lacking a two-way verification mechanism at the vehicle hardware level; (2) The generation of charging instructions is mainly based on fixed strategies, making it difficult to respond in a timely manner to the dynamic changes in grid load and user demands; (3) The data collection during the charging process and the user identity information are stored separately, resulting in the lack of multi-dimensional correlation analysis support for regulation decisions; (4) The settlement process relies on the centralized platform for processing, having problems such as the risk of data tampering and insufficient fault recovery ability. The above-mentioned defects in the prior art lead to the following problems: The single authentication method is easily counterfeited and attacked, threatening the charging security; The static instruction strategy is difficult to balance the grid load and the charging efficiency; The decentralized data storage structure hinders real-time regulation and optimization; The centralized settlement system is vulnerable to single-point failures. Therefore, there is an urgent need for an intelligent charging operation method that deeply integrates vehicle identity, dynamic regulation, and trusted settlement.

[0017] In view of the above problems in the prior art, this application proposes a charging operation method based on the vehicle identification number, and its flowchart is as shown in the appendix Figure 1 and mainly includes steps S101 to S106, which are described in detail as follows: Step S101: Establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identity identification code VIN and license plate number input by the user, and store the bound VIN as the user-prestored VIN in the database of the operation platform.

[0018] In the prior art, when implementing the charging operation of electric vehicles, if relying solely on the license plate number, it is vulnerable to attacks by forged license plates; if only using the Vehicle Identification Number (VIN), the actual association between the vehicle and the user cannot be verified; and the VIN is the unique identifier of the vehicle, and the license plate number is auxiliary verification information. When there is no binding relationship between the two, the charging pile cannot verify the legality of the vehicle, which may lead to unauthorized vehicles accessing. Therefore, in order to prevent a single identifier from being tampered with or misused and provide a basis for subsequent charging permission control and data association, in the embodiments of the present application, the binding relationship between the VIN corresponding vehicle and the operation platform can be established by obtaining the vehicle identification code VIN and the license plate number input by the user. Further, considering that if the VIN is not pre-stored, the authenticity of the VIN obtained in real time cannot be verified in the subsequent steps of the charging operation method based on the vehicle identification code, and the identity verification chain is broken. Therefore, the bound VIN can be stored as the user's pre-stored VIN in the database of the operation platform as the reference data for subsequent processes, such as instruction generation, data association, and settlement and evidence storage, etc.

[0019] As an embodiment of the present application, the establishment of the binding relationship between the VIN corresponding vehicle and the operation platform by obtaining the vehicle identification code VIN and the license plate number input by the user can be achieved through steps S1011 to S1013, and the details are as follows: Step S1011: When the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, the VIN is obtained in real time through the interface of the vehicle Battery Management System (BMS).

[0020] The vehicle's Battery Management System (BMS) is the core controller of the vehicle battery. The commercial vehicle communication protocol requires the BMS to support the VIN query function. Therefore, when the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, a communication link between the target charging pile and the vehicle BMS is established through a physical interface (such as CC / CP pins), and a standardized VIN request instruction (such as the $22 service in the UDS protocol) is sent. After the BMS obtains the VIN from the VCU, it returns.

[0021] Step S1012: When the BMS communication is abnormal, activate the Radio Frequency Identification (RFID) reader to scan the in-vehicle electronic tag to obtain the backup VIN.

[0022] If only relying on the BMS interface, the system robustness is insufficient. For example, the vehicle BMS versions are incompatible, etc. The radio frequency identification (RFID) backup mechanism is a technical means to obtain a trusted VIN when the hardware interface fails. This means that when the BMS communication is abnormal, the RFID reader can be activated to scan the vehicle electronic tag to obtain the backup VIN. It can be seen from step S1011 and step S1012 that this dual-channel verification mechanism of dual-channel BMS + RFID can not only ensure service continuity in extreme scenarios, but also prevent obtaining charging permissions by forging BMS data, that is, making the system have the anti-fraud ability.

[0023] Step S1013: Match and verify the VIN obtained in real time or the backup VIN with the VIN pre-stored by the user.

[0024] Specifically, the matching and verification of the VIN obtained in real time or the backup VIN with the VIN pre-stored by the user can be as follows: The operation platform generates a dynamic verification key and divides it into a first key segment and a second key segment; sends the first key segment to the user's mobile terminal for biometric verification; transmits the second key segment to the target charging pile to control its display screen to generate a dynamic two-dimensional code containing the second key segment; after the user scans the dynamic two-dimensional code, the scanning result is associated and verified with the result of the biometric verification; when the verification passes and the VIN obtained in real time or the backup VIN is consistent with the VIN pre-stored by the user, the matching verification of the VIN obtained in real time or the backup VIN with the VIN pre-stored by the user passes. Considering that the keys of traditional encryption algorithms are easily cracked by quantum computing, this means that if fixed keys or simple hashes are used, the high security requirements in the vehicle networking scenario cannot be met. However, the initial value sensitivity and pseudo-randomness of the chaos algorithm can resist brute force cracking. Therefore, in the above embodiments, the operation platform generates a dynamic verification key by: generating an initial key seed according to the hash value of the VIN pre-stored by the user; combining the geographical location of the target charging pile and the real-time timestamp to generate a dynamic perturbation factor; and finally generating a dynamic verification key by fusing the initial key seed and the dynamic perturbation factor through the chaos algorithm.

[0025] In the above embodiments, generating a dynamic disturbance factor by combining the geographical location of the target charging pile and the real-time timestamp may be as follows: encoding and normalizing the geographical location of the target charging pile into a geographical location normalization value; segmenting the real-time timestamp according to a preset rule, intercepting several bits at the end as the dynamic component, and intercepting the current number of seconds as the periodic component. Then, dividing the sum of the dynamic component and the periodic component by a certain number, such as 10,000, to obtain the timestamp disturbance component; finally, performing weighted summation on the geographical location normalization value and the timestamp disturbance component to obtain the disturbance factor and recalculating the above disturbance factor at each preset interval to dynamically update the disturbance factor. In the above embodiments, the technical solution of finally generating a dynamic verification key by fusing the initial key seed and the dynamic disturbance factor through a chaotic algorithm mainly includes initializing the chaotic system, iterating and extracting keys for the chaotic sequence, and finally generating the dynamic verification key through an obfuscation means. Among them, initializing the chaotic system may be to select the Logistic chaotic map as the chaotic model , where r is the fractal parameter (usually taken as 3.99 - 4.0), is the current state value (the initial value is determined by the key seed and the disturbance factor). Then, input the initial key seed into the chaotic model, convert the key seed to decimal, combine the disturbance factor with the decimal value of the initial key seed to generate the chaotic initial value; iterating and extracting keys for the chaotic sequence includes performing a preset number of warm-up iterations (such as 500 times) under the established fractal parameter and chaotic initial value to eliminate the transient effect, and then continuing to iterate to generate an effective sequence, converting these effective sequences to binary and splicing these binary segments into a 256-bit original key sequence; as for finally generating the dynamic verification key through an obfuscation means, it may be to inject the dynamic disturbance factor twice, that is, convert the disturbance factor (0.835) to 8-bit binary, and then perform XOR obfuscation on the original key sequence. Finally, intercept the first several bits (such as 128 bits) from the obfuscated sequence as the dynamic verification key.

[0026] Through the above dynamic key generation mechanism, not only is the cracking difficulty increased, but also by combining the geographical location of the target charging pile with the real-time timestamp, the reuse of keys is avoided, fully reflecting the environmental adaptability of the solution.

[0027] It should be noted that the parameters of the above chaotic algorithm can be pre-configured in the following manner: According to the parity bit distribution characteristics of the VIN pre-stored by the user, the calculation rule of the number of iterations is dynamically selected, that is: if the sum of the odd-bit numbers of the VIN pre-stored by the user is greater than the even-bit, the number of iterations N = the sum of odd bits × 2; otherwise, N = the sum of even bits + a preset base number; Based on the model code of the target charging pile to analyze the hardware performance level, the perturbation amplitude threshold R is set according to the following rules: High-performance pile (the first letter of the code is A / B): R = 0.5 × (rated power of the charging pile / 100); Standard pile (the first letter of the code is C / D): R = 0.3 × (rated power of the charging pile / 100); According to the number of iterations N and the perturbation amplitude threshold R, the key generation time consumption T is calculated through the formula T = K × N × log(R), and the calculation accuracy of the chaotic algorithm is dynamically adjusted to ensure that the key generation time consumption T does not exceed the preset threshold duration, such as 200ms. Among them, in the calculation formula of the key generation time consumption T, K is the hardware performance compensation coefficient.

[0028] Step S102: The operation platform generates a dynamic charging control instruction based on the real-time grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the VIN pre-stored by the user, and sends it to the target charging pile.

[0029] Considering that if only relying on single-dimensional data (such as only user demand), it will lead to grid imbalance or battery damage. This means that in order to ensure the coordination of charging behavior and grid stability, avoid overload risks, meet personalized charging needs (such as fast charging / slow charging selection), and optimize the charging strategy based on vehicle battery characteristics (such as capacity, charging curve), in the embodiment of the present application, the operation platform can generate a dynamic charging control instruction based on the real-time grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the VIN pre-stored by the user. As an embodiment of the present application, the operation platform generates a dynamic charging control instruction based on the real-time grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the VIN pre-stored by the user, which can be implemented through steps S1021 to S1024, and the detailed description is as follows: Step S1021: Obtain the historical charging data and battery health status of the vehicle corresponding to the VIN pre-stored by the user.

[0030] Step S1022: Combine the real-time grid load data and predict the optimal charging power curve through a reinforcement learning model.

[0031] Specifically, combining the real-time grid load data and predicting the optimal charging power curve through a reinforcement learning model can be achieved through steps S10221 to S10224, and the detailed description is as follows: Step S10221: Collect the real-time grid load data and perform preprocessing.

[0032] Specifically, real-time grid load data can be obtained from the grid dispatching center interface, including: the current total grid load (unit: MW), the real-time load rate (percentage) of the transformer in the area where the target charging station is located, the predicted grid load value within the next 1 hour, and the time-of-use electricity price (such as peak-valley-flat electricity price). After collecting this data, it can be standardized, that is, the grid load data is normalized to the range of 0 to 1. For example, the ratio of the current load to the maximum capacity of the transformer.

[0033] Step S10222: Construct the core elements of the reinforcement learning model. In the implementation of this application, the core elements of constructing the reinforcement learning model include the definition of the state space and the action space and the design of the reward function. Among them, the definition of the state space includes input features such as grid-side data (such as real-time load, load rate, future load prediction, current electricity price, etc.), vehicle data (such as the current SOC of the battery, the maximum allowable charging power, the battery health status, etc.), and user requirements (such as the expected charging completion time, the priority of the cost budget, etc.). The action space includes adjusting the charging power (such as increasing from 50 kW to 80 kW, or decreasing to 30 kW), suggesting a delayed charging period (such as "charging 1 hour later can save 20% of the cost"), and switching the charging mode (fast charging / slow charging), etc. The reward function includes grid-side rewards, user-side rewards, and battery health penalties, etc.

[0034] Step S10223: Model training and optimization.

[0035] It mainly includes offline pre-training and online real-time optimization. Among them, offline pre-training can be carried out by inputting a number of (such as 100,000) historical charging records, and then, the policy is iteratively updated through the Q-learning algorithm, that is, the action is randomly selected initially, the obtained reward value is recorded, and the Q-table (state-action value table) is updated through the Bellman equation, so that the model gradually learns to select high-reward actions under specific grid load states; online real-time optimization can be that after the model is deployed to the actual system, the latest grid load data is obtained every preset time period (such as 5 minutes). After each charging task is completed, the model parameters are updated according to the actual results (such as whether a grid overload alarm is triggered, the user satisfaction score), and then, the ε-greedy strategy is used to balance exploration and exploitation. For example: select the current optimal action with a 90% probability and randomly try new actions with a 10% probability.

[0036] Step S10224: Generate the optimal charging power curve Specifically, it includes outputting corresponding candidate strategies according to the current vehicle SOC, user requirements, and grid load rate, etc., then calculating the comprehensive scores of each strategy, and finally, selecting the strategy B with the highest total score to generate the corresponding charging power curve.

[0037] Step S1023: When the predicted power curve conflicts with the user's demand, send an adjustment suggestion to the user's mobile terminal.

[0038] Step S1024: Generate a final control instruction according to the user feedback or the default policy.

[0039] Specifically, if the user selects the priority charging speed, a temporary power increase beyond the grid load threshold is allowed; if the user selects the economy mode, the charging plan is automatically adjusted to match the low-valley electricity price period; the user-selected mode is superimposed on the real-time grid data to generate a segmented charging control instruction. The above segmented charging control instruction can be executed in the following manner: During the power increase stage, the total load on the grid side and the load rate of the transformer at the charging station where the vehicle is located are monitored in real time; when any of the following conditions is met, the economy mode is automatically switched: the total load on the grid side exceeds a preset ratio of the regional power supply capacity threshold, for example, 90%; or, the load rate of the transformer at the charging station continuously exceeds a preset ratio (for example, 5 minutes) higher than the preset ratio, for example, 85%; key parameters such as the switching time, load threshold, and influence range of the mode switching event are generated into a verifiable log and written into the blockchain evidence storage node.

[0040] It can be seen from step S102 of the above embodiment that, based on the real-time grid load data, user demand, and vehicle battery parameters associated with the user's pre-stored VIN, a control instruction is dynamically generated, enabling the charging strategy to synchronously respond to changes in the grid state and vehicle characteristics, breaking through the limitations of traditional fixed strategies, and enhancing the grid stability while ensuring the charging efficiency.

[0041] Step S103: When executing the control instruction at the target charging pile, collect the battery state parameters of the vehicle battery management system BMS and the operation data of the charging pile in real time.

[0042] In the embodiment of the present application, the battery state parameters of the vehicle battery management system BMS may be the state of charge (SOC) of the vehicle battery, health state, temperature parameters, electrical parameters (voltage, current, internal resistance, etc.), and fault codes, etc., while the operation data of the charging pile mainly includes electrical parameters such as the input / output voltage, current, power, and power factor of the target charging pile, state parameters (for example, the working mode of the charging pile, the operation state of the heat dissipation system, and the connection state, etc.), environmental parameters, and fault information, etc. These battery state parameters and the operation data of the charging pile can be obtained through real-time communication between the target charging pile and the vehicle when the target charging pile executes the control instruction.

[0043] Step S104: Associate the battery state parameters and the operation data of the charging pile with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis.

[0044] On the one hand, battery state parameters (such as SOC, temperature, voltage) are the core monitoring indicators for charging safety. If they are not associated with the user's pre-stored VIN, it is impossible to distinguish the charging data of different vehicles, and the control strategy may be incorrectly applied. On the other hand, single-dimensional control, such as only reducing the speed according to temperature, may lead to low charging efficiency or safety hazards. Therefore, in order to ensure clear data attribution, prevent data confusion, and achieve adaptive control of the charging process, in the embodiments of the present application, battery state parameters and charging pile operation data can be associated with the user's pre-stored VIN, and charging parameters can be dynamically adjusted through multi-dimensional data fusion analysis.

[0045] As an embodiment of the present application, dynamically adjusting charging parameters through multi-dimensional data fusion analysis can be: establishing a multi-parameter correlation matrix including battery SOC value, temperature change rate, and voltage fluctuation coefficient; calculating the dynamic weight coefficients of each parameter in the multi-parameter correlation matrix through a sliding time window algorithm; triggering a charging parameter adjustment strategy based on the distribution of each weight coefficient in the multi-parameter correlation matrix. In the above embodiment, triggering a charging parameter adjustment strategy based on the distribution of each weight coefficient in the multi-parameter correlation matrix can be: adjusting the working mode of the heat dissipation system of the target charging pile according to the temperature change rate; correcting the charging curve smoothness parameter based on the voltage fluctuation coefficient; recalculating the optimal charging duration in combination with the battery SOC value. After the above charging parameter adjustment strategy is triggered, the target charging station executes as follows: recording the maximum temperature value and voltage fluctuation amplitude during each charging process, and constructing a time series database; inputting the time series data into a pre-trained LSTM neural network model to output the prediction result of the battery life attenuation curve; when the prediction result shows that the remaining life is lower than a preset ratio of the rated value, generating a customized maintenance recommendation and pushing it to the user's mobile terminal.

[0046] Furthermore, it also includes abnormal handling during the charging process, that is, when the temperature change rate continuously exceeds the safety threshold, the following operations are performed: prompting the user to check the battery state through the display screen of the target charging pile; pushing alternative charging station information to the user's mobile terminal; terminating the current charging and generating a settlement message including temperature anomaly records; where pushing alternative charging station information to the user's mobile terminal can be: calculating the optimal driving path to each alternative charging station based on the user's current location coordinates and real-time road condition data; obtaining the number of available charging piles and estimated charging costs in real time according to the end coordinates of the optimal path; dynamically rendering the comprehensive recommendation index and estimated total time of each alternative station on the map interface of the user's mobile terminal, that is: the comprehensive recommendation index of each alternative charging station calculated by weighting the path duration, electricity price, and number of available charging piles, the navigation guidance and key node prompts of the optimal path, and the estimated total time of each charging station, that is, driving time + charging waiting time + charging time.

[0047] As can be seen from the above embodiments, by associating and analyzing the real-time operation data collected by the target charging pile with the user's pre-stored VIN, a dynamic mapping relationship of identity-status-regulation is established, realizing the closed-loop optimization adjustment of charging parameters and providing data support for solving safety hazards such as battery overheating and abnormal voltage.

[0048] Step S105: After charging is completed, generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN.

[0049] Considering that if the charging record is not associated with the user's pre-stored VIN, the corresponding relationship between the charging behavior and the vehicle cannot be traced, and there is no basis for dispute resolution. Therefore, in order to ensure the accuracy of billing, for example, to prevent billing errors such as "misattribution", in the embodiments of the present application, an encrypted settlement message can be generated based on the charging record associated with the user's pre-stored VIN after charging is completed. Specifically, it can be: extract the user's pre-stored VIN, the start and end times of charging, and the actual charging amount data; use the user's private key bound to the user's pre-stored VIN to digitally sign the actual charging amount data; jointly encrypt the signed actual charging amount data and the charging pile identity information to generate a settlement message.

[0050] The above embodiments are the online settlement mode, that is, the case where the target charging pile and the operation platform can communicate normally. In the actual application scenario of the present application, there is also an offline settlement mode, that is, when the network is interrupted, the target charging pile encrypts the settlement data using a pre-set offline key; generates a temporary certificate containing the hash value of the VIN and the timestamp; after the network is restored, the operation platform verifies the integrity of the temporary certificate and the offline data. If the verification is successful, the charging settlement is completed. In the above embodiments, the operation platform verifying the integrity of the temporary certificate and the offline data can be: comparing the hash value of the VIN in the temporary certificate with the hash value of the user's pre-stored VIN; if the verification passes, verifying whether the timestamp in the temporary certificate is within the validity period of the charging task; if the verification passes, confirming the legitimacy of the offline key through the charging pile digital certificate, including: verifying whether the certificate issuing authority is within the platform white list and checking whether the certificate validity period covers the charging time period; after the legitimacy verification of the offline key through the charging pile digital certificate passes, the integrity verification of the temporary certificate and the offline data is considered to pass.

[0051] Step S106: Use blockchain technology to perform on-chain evidence storage on the encrypted settlement message, and notify the user after the fee settlement is completed.

[0052] As is well known, centralized storage is vulnerable to data tampering attacks, while blockchain evidence storage can avoid the risk of single-point failure. Therefore, in order to solve the problems of "data authenticity" and "settlement traceability", blockchain technology can be used to perform on-chain evidence storage on the encrypted settlement message, and notify the user after the fee settlement is completed.

[0053] As can be seen from steps S105 and S106 of the above embodiments, the blockchain technology is used to store the charging records associated with the VIN on the chain. By leveraging its decentralized and immutable characteristics, the integrity and auditability of the settlement data are ensured, effectively avoiding the risks of data leakage and single-point failure in traditional centralized settlement systems.

[0054] From the above attached Figure 1 As can be seen from the above-described charging operation method based on the vehicle identification number, on the one hand, by performing two-way binding verification on the VIN input by the user and the vehicle hardware information obtained in real time by the charging pile, a dual-channel authentication mechanism is constructed, effectively preventing illegal users from accessing the charging system by forging account information, and improving the security of charging operations at the source. And based on real-time grid load data, user demand, and the vehicle battery parameters associated with the pre-stored VIN, dynamic control instructions are generated, enabling the charging strategy to synchronously respond to changes in the grid state and vehicle characteristics, breaking through the limitations of traditional fixed strategies, enhancing grid stability while ensuring charging efficiency; on the other hand, by performing correlation analysis on the real-time operation data collected by the charging pile and the pre-stored VIN, a dynamic mapping relationship of identity-status-regulation is established, realizing closed-loop optimization adjustment of charging parameters, providing data support for solving safety hazards such as battery overheating and voltage anomalies; thirdly, the blockchain technology is used to store the charging records associated with the VIN on the chain. By leveraging its decentralized and immutable characteristics, the integrity and auditability of the settlement data are ensured, effectively avoiding the risks of data leakage and single-point failure in traditional centralized settlement systems. In summary, the technical solution of the present application can significantly improve the charging safety, optimization efficiency, and cost credibility of the charging pile.

[0055] Please refer to the attached Figure 2 , which is a charging operation device based on the vehicle identification number provided by the embodiment of the present application. The device may include a binding module 201, a first generation module 202, a collection module 203, an association module 204, a second generation module 205, and a deposit proof module 206, which are described in detail as follows: The binding module 201 is configured to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification number VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform; The first generation module 202 is configured to generate dynamic charging control instructions based on real-time grid load data, user charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN by the operation platform and send them to the target charging pile; The collection module 203 is configured to collect the battery state parameters of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instruction; An association module 204, configured to associate battery state parameters and charging pile operation data with the user's pre-stored VIN, and dynamically adjust charging parameters through multi-dimensional data fusion analysis; A second generation module 205, configured to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; An evidence storage module 206, configured to perform on-chain evidence storage on the encrypted settlement message through blockchain technology, and notify the user after the fee settlement is completed.

[0056] From the above-attached Figure 2 It can be seen from the example of the charging operation device based on the vehicle identification number that, on the one hand, through the dynamic scheduling engine, the grid time-sharing load data and the charging pile group status data are integrated in real time, and the charging queue sorting is generated by combining the multi-objective optimization algorithm, so that the charging task allocation can dynamically adapt to the grid carrying capacity and the device operation status, effectively balancing the grid load, avoiding the risk of local overload, and at the same time significantly improving the utilization rate of charging piles by optimizing the spatio-temporal resource allocation of charging piles; on the other hand, during the charging process, through the real-time collection of multi-dimensional operation data and abnormal pattern recognition, the power reallocation strategy can be quickly triggered, the power supply parameters of adjacent charging piles can be dynamically adjusted, the impact of faults can be isolated in time and the continuity of charging services can be maintained, so as to ensure the safety of the charging process and the overall reliability of the system; thirdly, an encrypted communication link is used to realize the secure data transmission between the charging pile monitoring node and the cloud platform, and the key parameters of the charging process are distributed and stored through the blockchain smart contract, which not only prevents the risk of data tampering during the transmission and storage process, but also improves the transparency and credibility of the charging process through the multi-party verification mechanism, reducing user disputes.

[0057] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 3 shown, the electronic device 3 of this embodiment mainly includes: a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30, such as a program for the charging operation method based on the vehicle identification number. When the processor 30 executes the computer program 32, the steps in the embodiment of the above-mentioned charging operation method based on the vehicle identification number are implemented, such as Figure 1 the steps S101 to S106 shown. Alternatively, when the processor 30 executes the computer program 32, the functions of each module / unit in the above-mentioned device embodiments are implemented, such as Figure 2 the functions of the binding module 201, the first generation module 202, the collection module 203, the association module 204, the second generation module 205, and the evidence storage module 206 shown.

[0058] Exemplarily, the computer program 32 for the charging operation method based on the vehicle identification number mainly includes: establishing a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification number VIN and license plate number input by the user, and storing the bound VIN as the user's pre-stored VIN in the database of the operation platform; the operation platform generates a dynamic charging control instruction based on the real-time power grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, and issues it to the target charging pile; when the target charging pile executes the control instruction, the battery state parameters of the vehicle battery management system BMS and the charging pile operation data are collected in real time; the battery state parameters and the charging pile operation data are associated with the user's pre-stored VIN, and the charging parameters are dynamically adjusted through multi-dimensional data fusion analysis; after charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN; the encrypted settlement message is stored on the chain through blockchain technology, and the user is notified after the fee settlement is completed. The computer program 32 can be divided into one or more modules / units, and one or more modules / units are stored in the memory 31 and executed by the processor 30 to complete this application. One or more modules / units can be a series of computer program instruction segments capable of completing specific functions, and these instruction segments are used to describe the execution process of the computer program 32 in the electronic device 3. For example, the computer program 32 can be divided into the functions of a binding module 201, a first generation module 202, a collection module 203, an association module 204, a second generation module 205, and a storage module 206 (modules in the virtual device), and the specific functions of each module are as follows: The binding module 201 is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification number VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform; the first generation module 202 is used for the operation platform to generate a dynamic charging control instruction based on the real-time power grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, and issue it to the target charging pile; the collection module 203 is used to collect the battery state parameters of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instruction; the association module 204 is used to associate the battery state parameters and the charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; the second generation module 205 is used to generate an encrypted settlement message based on the charging record associated with the user's pre-stored VIN after charging is completed; the storage module 206 is used to store the encrypted settlement message on the chain through blockchain technology, and notify the user after the fee settlement is completed.

[0059] The electronic device 3 may include but is not limited to the processor 30 and the memory 31. Those skilled in the art can understand that Figure 3This is only an example of the electronic device 3, which does not constitute a limitation on the electronic device 3. It may include more or fewer components than those shown in the figure, or combine some components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0060] The so-called processor 30 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0061] The memory 31 may be an internal storage unit of the electronic device 3, such as the hard disk or memory of the electronic device 3. The memory 31 may also be an external storage device of the electronic device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 3. Further, the memory 31 may also include both the internal storage unit and the external storage device of the electronic device 3. The memory 31 is used to store computer programs and other programs and data required by the electronic device. The memory 31 may also be used to temporarily store the data that has been output or will be output.

[0062] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into a processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above device may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0063] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0064] Those of ordinary skill in the art will appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0065] In the embodiments provided in this application, it should be understood that the disclosed apparatus / devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0066] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0067] In addition, the functional units in the various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0068] When the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of this application, it can also be completed by a computer program instructing relevant hardware. The computer program of the charging operation method based on the vehicle identification number can be stored in a storage medium. When the computer program is executed by a processor, it can implement the steps of the above-mentioned various method embodiments, that is, by obtaining the vehicle identification number VIN and license plate number input by the user to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform, and storing the bound VIN as the user's pre-stored VIN in the database of the operation platform; the operation platform generates a dynamic charging control instruction based on the real-time grid load data, the user's charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, and sends it to the target charging pile; when the target charging pile executes the control instruction, it collects the battery state parameters of the vehicle battery management system BMS and the operation data of the charging pile in real time; associates the battery state parameters and the operation data of the charging pile with the user's pre-stored VIN, and dynamically adjusts the charging parameters through multi-dimensional data fusion analysis; after the charging is completed, generates an encrypted settlement message based on the charging record associated with the user's pre-stored VIN; performs on-chain storage of the encrypted settlement message through blockchain technology, and notifies the user after the fee settlement is completed. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The storage medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the storage medium does not include electrical carrier signals and telecommunication signals.

[0069] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application. The specific implementation manners described above have further elaborated on the purpose, technical solutions, and beneficial effects of the present application. It should be understood that the above is only the specific implementation manner of the present application, and is not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application should all be included in the protection scope of the present invention.

Claims

1. A charging operation method based on vehicle identification number, characterized in that The method includes: Establishing a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification number (VIN) and license plate number input by the user, and storing the bound VIN as the user's pre-stored VIN in the database of the operation platform; Based on the real-time power grid load data, user charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, the operation platform generates a dynamic charging control instruction and sends it to the target charging pile; When the target charging pile executes the control instruction, the battery state parameters of the vehicle battery management system (BMS) and the charging pile operation data are collected in real time; Associating the battery state parameters and the charging pile operation data with the user's pre-stored VIN, and dynamically adjusting the charging parameters through multi-dimensional data fusion analysis; After charging is completed, an encrypted settlement message is generated based on the charging record associated with the user's pre-stored VIN; Using blockchain technology to perform on-chain storage of the encrypted settlement message, and notifying the user after the fee settlement is completed.

2. The charging operation method based on the vehicle identification number according to claim 1, wherein, The establishment of the binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification number (VIN) and license plate number input by the user includes: When the charging gun of the target charging pile is inserted into the vehicle corresponding to the VIN, the VIN is obtained in real time through the interface of the BMS; When the BMS communication is abnormal, activate the RFID reader to scan the vehicle electronic tag to obtain the backup VIN; Match and verify the real-time obtained VIN or the backup VIN with the user's pre-stored VIN.

3. The charging operation method based on the vehicle identification number according to claim 2, wherein The matching and verification of the real-time obtained VIN or the backup VIN code with the user's pre-stored VIN code includes: The operation platform generates a dynamic verification key and divides it into a first key segment and a second key segment; Sending the first key segment to the user's mobile terminal for biometric verification; Transmitting the second key segment to the target charging pile to control its display screen to generate a dynamic two-dimensional code containing the second key segment; After the user scans the dynamic two-dimensional code, the scan result is associated and verified with the result of the biometric verification; When the verification passes and the real-time obtained VIN or the backup VIN is consistent with the user's pre-stored VIN, the matching verification of the real-time obtained VIN or the backup VIN with the user's pre-stored VIN passes.

4. The charging operation method based on the vehicle identification number according to claim 1, characterized in that The operation platform generates a dynamic charging control instruction based on the real-time power grid load data, user charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, including: Obtaining the historical charging data and battery health status of the vehicle corresponding to the user's pre-stored VIN; Combining the real-time power grid load data, and predicting the optimal charging power curve through a reinforcement learning model; When the predicted power curve conflicts with the user's demand, sending an adjustment suggestion to the user's mobile terminal; Generating a final control instruction according to the user feedback or the default policy.

5. The charging operation method based on the vehicle identification number according to claim 1, characterized in that, The dynamic adjustment of the charging parameters through multi-dimensional data fusion analysis includes: Establishing a multi-parameter correlation matrix including the battery state of charge (SOC) value, temperature change rate, and voltage fluctuation coefficient; Calculating the dynamic weight coefficients of each parameter in the multi-parameter correlation matrix through a sliding time window algorithm; Trigger a charging parameter adjustment strategy based on the weight coefficient distribution.

6. The charging operation method based on the vehicle identification code according to claim 5, wherein, The execution of the charging parameter adjustment strategy includes: Record the maximum temperature value and voltage fluctuation amplitude during each charging process, and construct a time series database; Input the time series data into a pre-trained LSTM neural network model, and output the prediction result of the battery life attenuation curve; When the prediction result shows that the remaining life is lower than a preset proportion of the rated value, generate customized maintenance suggestions and push them to the user's mobile terminal.

7. The charging operation method based on the vehicle identification number according to claim 1, wherein The generation of the encrypted settlement message based on the charging records associated with the user's pre-stored VIN includes: Extract the user's pre-stored VIN, charging start and end times, and actual charging amount data; Use the user's private key bound to the user's pre-stored VIN to digitally sign the actual charging amount data; Encrypt the signed actual charging amount data together with the charging pile identity information to generate a settlement message.

8. A charging operation device based on a vehicle identification number, characterized in that The device includes: A binding module, which is used to establish a binding relationship between the vehicle corresponding to the VIN and the operation platform by obtaining the vehicle identification code VIN and license plate number input by the user, and store the bound VIN as the user's pre-stored VIN in the database of the operation platform; A first generation module, which is used for the operation platform to generate a dynamic charging control instruction based on real-time grid load data, user charging demand, and the vehicle battery parameters corresponding to the user's pre-stored VIN, and send it to the target charging pile; An acquisition module, which is used to collect the battery state parameters of the vehicle battery management system BMS and the charging pile operation data in real time when the target charging pile executes the control instruction; An association module, which is used to associate the battery state parameters and the charging pile operation data with the user's pre-stored VIN, and dynamically adjust the charging parameters through multi-dimensional data fusion analysis; A second generation module, which is used to generate an encrypted settlement message based on the charging records associated with the user's pre-stored VIN after charging is completed; An evidence storage module, which is used to store the encrypted settlement message on the chain through blockchain technology, and notify the user after the fee settlement is completed.

9. An electronic device, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

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

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