Anti-fraud charging pile control method and system, medium and product

Abstract

The invention discloses an anti-fraud charging pile control method and system, a medium and a product, and relates to the field of charging pile control. In the method, an information interaction mechanism among a mobile terminal, a charging platform and a charging pile is established after a two-dimensional code is scanned, and the change of the state of an indicator lamp of the charging pile is used as physical feedback; a user can intuitively judge the authenticity of the scanned two-dimensional code; when a user scans a fraud two-dimensional code, because the charging platform cannot receive a normal request, the charging pile will not receive a code scanning normal signal, and the indicating lamp is kept in the first state, so that the user is reminded in time to prevent the fraud risk; according to the method, a user does not need to install a special APP, the method does not depend on a two-dimensional code encryption mode which is easy to crack, an anti-fraud means is provided from the hardware level of the charging pile, and the safety of the charging process is improved.

Description

Technical Field

[0001] This application belongs to the field of charging pile control, and in particular relates to a fraud prevention charging pile control method, system, medium and product. Background Technology

[0002] With the popularization of new energy vehicles, the number of charging piles is growing rapidly, and charging scenarios are becoming increasingly complex. Currently, mainstream charging piles typically use QR code scanning to initiate charging; users scan the QR code on the charging pile with their mobile phones to access the charging operation interface. However, because QR codes are easily copied, some criminals use copied QR codes from legitimate charging piles or generate fake QR codes to commit fraud. Users who scan fake QR codes may be redirected to phishing websites, resulting in the leakage of account passwords or financial losses.

[0003] Related technologies typically employ methods such as encrypting QR codes or embedding timestamps within them to prevent fraud. However, these solutions are still susceptible to being cracked and require users to download dedicated apps, impacting user experience.

[0004] However, current technology lacks effective means to prevent fraud at the hardware level of charging stations. When users scan fake QR codes, the charging station cannot detect this behavior and cannot promptly alert the user, making it difficult for users to distinguish between genuine and fake QR codes, and making them vulnerable to being deceived. This situation needs further improvement. Summary of the Invention

[0005] This application provides a fraud-prevention charging pile control method to address the technical problem of QR code fraud in charging scenarios. This method establishes a linkage mechanism between the mobile terminal, charging platform, and charging pile during the scanning process. It utilizes changes in the charging pile's indicator light status to help users intuitively determine the authenticity of the QR code. Combined with multiple protective measures such as geolocation verification, user credit scoring, and device status monitoring, it achieves safe and reliable operation during the charging process.

[0006] In a first aspect, this application provides a fraud-prevention method for controlling charging piles, the method comprising: In response to a QR code scanning operation by a mobile terminal browser, the QR code information on the charging pile is obtained, wherein the Uniform Resource Locator corresponding to the QR code contains the charging pile number information. Based on the obtained QR code information, the system automatically accesses the corresponding Uniform Resource Locator and sends a request to the charging platform. The request is parsed, interactive interface information is sent to the mobile terminal, and a normal scanning signal is sent to the charging pile corresponding to the pile number. In response to the normal scanning signal, the indicator light of the charging pile is controlled to switch from the first state to the second state; In response to the second state of the indicator light, the user authentication process is executed through the interactive interface and the charging operation is controlled.

[0007] In the above implementation, by establishing an information interaction mechanism among the mobile terminal, charging platform, and charging pile after scanning the QR code, and using the changes in the charging pile indicator light status as physical feedback, users can intuitively determine the authenticity of the scanned QR code. When a user scans a fraudulent QR code, the charging platform cannot receive a normal request, and the charging pile will not receive a normal scanning signal, with the indicator light remaining in its first state, thus promptly reminding the user to guard against fraud risks. This application does not require users to install a dedicated APP, nor does it rely on easily cracked QR code encryption methods, providing a fraud prevention measure from the charging pile hardware level and improving the security of the charging process. In conjunction with some embodiments of the first aspect, in some embodiments, before the step of controlling the indicator light of the charging pile to switch from the first state to the second state, the method further includes: Obtain the geographical location information of the mobile terminal; The geographical location information is compared with the installation location information of the charging pile; When the distance between the geographical location of the mobile terminal and the installation location of the charging pile exceeds a preset range, it is determined to be an abnormal scan, and the normal scan signal is prohibited from being sent to the charging pile.

[0008] In the above implementation, by obtaining the geographical location information of the mobile terminal and comparing it with the installation location of the charging pile, abnormal behaviors such as remote scanning can be identified. When the actual location of the user is detected to be far away from the location of the charging pile, the system will prohibit the sending of normal scanning signals, thereby preventing criminals from committing fraud by remotely copying and forwarding QR codes, and reducing the risk of users accidentally entering phishing websites when they are far away from the charging pile. In conjunction with some embodiments of the first aspect, in some embodiments, after the step of parsing the request, the method further includes: Obtain real-time load data of each charging pile in the charging station where the charging pile is located; Based on the real-time load data, calculate the historical usage frequency, cumulative usage time and historical rating data of each charging pile; Based on the historical usage frequency, cumulative usage time, and historical rating data, a charging service fee coefficient is dynamically calculated for each charging pile. The higher the historical usage frequency of a charging pile, the higher the corresponding charging service fee coefficient is set. When the historical usage frequency or cumulative usage time of the charging pile corresponding to the specified pile number exceeds a preset threshold, the location information, real-time status, and real-time price discount information calculated based on the charging service fee coefficient of other nearby available charging piles are pushed to the mobile terminal. In response to the user's selection of another charging station, the normal scan signal is sent to the charging station selected by the user.

[0009] In the above embodiments, when multiple charging piles coexist in a large charging station, user waiting times are long, and equipment usage intensity is uneven, without a reasonable scheduling mechanism, some popular charging piles are prone to being under high load for a long time, while charging piles in remote locations have low utilization rates. This not only accelerates equipment wear and tear but also leads to significant differences in user charging experience. This application introduces a dynamic pricing mechanism based on historical data, sets differentiated prices for different charging piles based on real-time load conditions, and proactively pushes price discount information to users. This can guide users to reasonably distribute themselves to different charging piles, balance the usage intensity of each charging pile, extend equipment lifespan, shorten user waiting times, and improve charging efficiency. In conjunction with some embodiments of the first aspect, in some embodiments, prior to the step of dynamically calculating the charging service fee coefficient for each charging pile, the method further includes: Obtain the current timestamp and divide the day into multiple time intervals based on the current timestamp; The timestamps in the historical usage records of the charging piles are statistically analyzed according to the time intervals to obtain time period characteristic data; Based on the time period characteristic data, the average waiting time, average charging time and average idle time of the charging piles in each time interval are calculated. The congestion coefficient is determined based on the ratio of average waiting time, average charging time, and average idle time. When the congestion coefficient exceeds a first preset threshold, the charging service fee coefficient within the time interval is increased by a preset increment step; when the congestion coefficient is lower than a second preset threshold, the charging service fee coefficient within the time interval is decreased by a preset decrement step step.

[0010] In the above embodiments, to address the issue of fluctuating user charging demand at charging stations during different time periods, adjusting service fees solely based on the historical usage frequency of charging piles may not effectively cope with peak-hour congestion. This application introduces a time-based congestion coefficient calculation mechanism, dynamically adjusting the service fee coefficient according to the ratio of average waiting time, charging time, and idle time in different time intervals. This can more accurately reflect the real-time load status of the charging station. When the congestion coefficient is high during a certain period, increasing the service fee can guide some users to avoid peak hours; when the congestion coefficient is low, price discounts can attract users to charge during off-peak hours, thereby achieving time-dispersed charging demand and improving the operational efficiency of the charging station. In some embodiments, in conjunction with the first aspect, after the step of performing the user authentication process and controlling the charging operation through the interactive interface, the method further includes: Obtain the user's historical charging behavior data, which includes charging duration, charging frequency, charging fee settlement records, and charging anomaly records; A credit scoring model is established based on the historical charging behavior data, and the user's credit score is calculated. Differentiated services are provided based on the user's credit score. When the user's credit score reaches a first preset score, the differentiated services include discounts on charging fees; when the user's credit score reaches a second preset score, the differentiated services include priority booking privileges; and when the user's credit score reaches a third preset score, the differentiated services include extended charging time. The user's charging behavior is compared with a preset abnormal behavior feature database, which includes features such as overdue payment of charging fees, repeated scanning without charging, forced disconnection during charging, and malicious occupation. When a user's charging behavior is detected to match a feature in the abnormal behavior feature library, the user's credit score is adjusted and the differentiated service is adjusted accordingly.

[0011] In the above embodiments, addressing the problem that charging stations lack user behavior management mechanisms and struggle to effectively constrain undesirable behaviors such as malicious occupation and overdue payments, this application establishes user profiles that include charging duration, charging frequency, payment settlement, and abnormal records. Combined with a pre-set abnormal behavior feature database, this allows for a comprehensive assessment of users' charging behavior compliance. For users with high credit scores, differentiated services such as charging fee discounts, priority reservations, and extended charging durations are provided as incentives. For users exhibiting abnormal charging behavior, credit scores are adjusted promptly, and corresponding rights are restricted. This constructs a positive user behavior guidance mechanism that improves the utilization efficiency of charging facilities while reducing the operational risks of charging stations. In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: The voltage, current, and temperature parameters of the charging pile are obtained to determine the operating parameters. Establish a charging pile operation status model based on the aforementioned operating parameters; The parameter change trends in the operating state model are compared in real time with a preset fault feature library, wherein the fault feature library includes voltage anomaly features, current anomaly features, and temperature anomaly features. When the trend of any operating parameter deviates from the normal range but does not reach the preset fault standard, a preventive maintenance process is triggered. The preventive maintenance process includes reducing the charging power, adjusting the charging current, activating the heat dissipation device, and sending maintenance reminder information to the operation and maintenance personnel. When any operating parameter exceeds the safe operating threshold, the charging interface will be automatically disconnected and a fault alarm message will be pushed to the maintenance personnel.

[0012] In the above embodiments, to address the problems of insufficient maintenance personnel, low maintenance frequency, and untimely response to equipment failures at charging stations in remote areas, especially at charging stations in some transportation hubs and highway service areas, once a charging pile fails, it not only affects the user's charging experience but may also cause the equipment to operate with defects for a long time, accelerating damage. This application establishes a preventive maintenance mechanism based on multi-parameter monitoring. By collecting key operating parameters such as voltage, current, and temperature in real time and comparing them with a preset fault feature database, equipment anomalies can be detected in a timely manner. When parameters show an abnormal trend but have not yet reached the fault level, the system will automatically take preventive measures such as reducing charging power, adjusting charging current, and starting heat dissipation, while notifying maintenance personnel to check and maintain. When parameters exceed the safety threshold, protective measures such as charging interruption will be immediately implemented, thereby achieving early warning and timely handling of faults, reducing equipment failure rate and safety accident risk, and improving the operational reliability of charging facilities. In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: The probability value of the charging pile malfunctioning is calculated according to a preset fault prediction model, wherein the fault prediction model calculates the fault probability based on the operating parameters. When the probability value is within the first preset probability range, the charging pile is set to observation mode, and the changing trend of the operating parameters is recorded; when the probability value is within the second preset probability range, the charging pile is set to maintenance mode, and the charging power is limited; when the probability value is within the third preset probability range, the charging pile is set to deactivated mode, and the charging interface is disconnected. Based on the status of the charging pile, a maintenance work order of the corresponding level is generated and assigned to the maintenance personnel of the corresponding maintenance level.

[0013] In the above implementation, by introducing a graded handling mechanism based on a fault prediction model, the equipment status is divided into three levels: observation, maintenance, and shutdown according to different ranges of charging pile fault probability. At the same time, maintenance work orders of the corresponding level are generated according to different statuses, enabling maintenance personnel to prioritize high-risk equipment, achieving optimal allocation of maintenance resources and ensuring the safe and stable operation of the charging station. Secondly, embodiments of this application provide a fraud-proof charging pile control system, comprising: one or more processors and a memory; the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and one or more processors call the computer instructions to cause the system to perform the method described in the first aspect and any possible implementation thereof. Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a system, cause the system to perform the method described in the first aspect and any possible implementation thereof. Fourthly, embodiments of this application provide a computer program product that, when run on a system, causes the system to execute the method described in any possible implementation of the first aspect. One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. This application provides a fraud-proof charging pile control method. By establishing an information interaction mechanism between the mobile terminal, the charging platform, and the charging pile after scanning the QR code, and using the changes in the charging pile indicator light status as physical feedback, users can intuitively judge the authenticity of the scanned QR code. When a user scans a fraudulent QR code, the charging platform cannot receive a normal request, and the charging pile will not receive a normal scanning signal. The indicator light remains in the first state, thus promptly reminding the user to guard against fraud risks. This application does not require users to install a dedicated APP, nor does it rely on easily cracked QR code encryption methods. It provides a fraud prevention measure from the charging pile hardware level, improving the security of the charging process.

[0014] 2. Due to the coexistence of multiple charging piles in large charging stations, long user waiting times, and uneven equipment usage, the lack of a reasonable scheduling mechanism can easily lead to situations where charging piles in popular locations are under high load for extended periods, while those in less popular locations have low utilization rates. This not only accelerates equipment wear and tear but also results in significant differences in user charging experience. This application introduces a dynamic pricing mechanism based on historical data, sets differentiated prices for different charging piles based on real-time load conditions, and proactively pushes price discount information to users. This not only guides users to reasonably distribute themselves to different charging piles, balances the usage intensity of each charging pile, extends equipment lifespan, but also shortens user waiting times and improves charging efficiency.

[0015] 3. Addressing the issue of charging stations lacking user behavior management mechanisms and struggling to effectively curb malicious occupation and overdue payments, this application establishes user profiles that include charging duration, charging frequency, payment settlement, and abnormal records. Combined with a pre-set abnormal behavior feature database, this allows for a comprehensive assessment of users' charging behavior compliance. For users with high credit scores, differentiated services such as charging fee discounts, priority reservations, and extended charging durations are provided as incentives. For users exhibiting abnormal charging behavior, credit scores are adjusted promptly, and corresponding rights are restricted. This constructs a positive user behavior guidance mechanism that improves the utilization efficiency of charging facilities while reducing the operational risks of charging stations. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a fraud prevention method for charging pile control in an embodiment of this application.

[0017] Figure 2 This is another flowchart illustrating a fraud prevention charging pile control method in the embodiments of this application.

[0018] Figure 3 This is a schematic diagram of the physical device structure of a fraud-proof charging pile control system provided in an embodiment of this application. Detailed Implementation

[0019] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0020] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more. In the field of new energy vehicle charging, charging piles are an important infrastructure, and their safety and reliability directly affect the user's charging experience and the service quality of charging operators.

[0021] In related technologies, anti-fraud measures for charging piles mainly rely on QR code encryption and dedicated APP verification. The maintenance method is mainly passive response, lacking an effective preventive maintenance mechanism. At the same time, there is also a lack of flexible management methods in terms of user diversion and equipment scheduling.

[0022] This application is mainly applied to scenarios such as large charging stations, highway service areas, and charging stations in remote areas. These scenarios generally feature large fluctuations in user charging demand, uneven equipment usage, and limited maintenance resources. In these application scenarios, preventing QR code fraud, optimizing charging resource allocation, and implementing preventative equipment maintenance are urgent problems to be solved. To address the above technical problems, this application provides a fraud-proof charging pile control method. An embodiment is described below in conjunction with… Figure 1 The following describes a fraud prevention method for charging piles in an embodiment of this application: Please see Figure 1 This is a flowchart illustrating a fraud prevention method for charging pile control in an embodiment of this application.

[0023] S101. In response to the QR code scanning operation of the mobile terminal browser, obtain the QR code information on the charging pile, wherein the Uniform Resource Locator corresponding to the QR code contains the charging pile number information.

[0024] The QR code information contains an encoded Uniform Resource Locator (URL), which embeds the charging pile number as a unique identifier to distinguish different charging pile devices.

[0025] Specifically, when a user points their mobile browser at the QR code on the surface of the charging station, the browser automatically activates its camera to scan it. After a successful scan, the system decodes the QR code to obtain a complete URL string. The system then extracts the charging station number information from the URL to prepare for subsequent charging operations.

[0026] In some implementations, the QR code may include not only the charging station number but also parameters such as the charging station ID, charging station model, and rated power. These parameters can be encoded in different fields of the URL. Optionally, the QR code can be dynamically generated and its content updated periodically to further enhance security.

[0027] S102. Based on the obtained QR code information, automatically access the corresponding Uniform Resource Locator and send a request to the charging platform.

[0028] Specifically, the mobile browser sends an HTTP request to the charging platform, using either a GET or POST method. The request parameters include information such as the charging pile number and charging station ID obtained from the QR code, as well as environmental parameters such as the mobile device type and operating system version. Upon receiving the request, the charging platform records this information in the corresponding session.

[0029] In some implementations, to enhance communication security, data transmission between the mobile terminal and the charging platform can be encrypted using the HTTPS protocol. Optionally, parameters such as timestamps and random strings can be added when sending requests to prevent interception and replay.

[0030] S103. Parse the request, send interactive interface information to the mobile terminal, and simultaneously send a normal scan signal to the charging pile corresponding to the charging pile number.

[0031] Upon receiving a request from a mobile terminal, the charging platform first verifies the validity of all parameters carried in the request. If the verification is successful, it generates an interactive interface and returns it to the mobile terminal, while simultaneously sending a successful scan signal to the corresponding charging station.

[0032] S104. In response to the normal scanning signal, control the indicator light of the charging pile to switch from the first state to the second state.

[0033] Specifically, after receiving a normal QR code scan signal, the charging pile first verifies the legality and validity of the signal. After successful verification, the charging pile's control module drives the indicator light circuit to switch the indicator light's display status from the first state (e.g., solid green, indicating standby mode) to the second state (e.g., flashing green, indicating charging can begin).

[0034] The indicator light status switching process of a charging pile includes: first, detecting the current working status of the indicator light; then, controlling the indicator light drive circuit to change its output according to preset status transition rules. When a user scans a fake QR code, because the charging platform cannot send a signal to the genuine charging pile, the indicator light will remain in the first state, thus reminding the user to guard against fraud risks.

[0035] Furthermore, to prevent abnormal behaviors such as remote scanning, this application adds a geolocation-based security verification mechanism before the indicator light state changes. Specifically, the system obtains the user's mobile terminal's GPS location information or base station location information and compares it in real time with the charging pile's registered installation location information on the charging platform. When the system detects that the distance between the user's actual location and the charging pile's location exceeds a preset reasonable range, it determines that the scanning behavior is abnormal, does not send a normal scanning signal to the charging pile, and the indicator light will remain in its first state.

[0036] In some implementations, the system can optionally adjust the preset distance range based on the specific layout and characteristics of the charging station. For example, in open highway service area charging stations, the distance restriction can be appropriately relaxed; in densely populated urban charging stations, a stricter distance threshold can be set. Optionally, the system can also combine the location change trend of the mobile terminal to identify whether the user is approaching the charging pile, further improving the accuracy of location verification.

[0037] S105, in response to the second state of the indicator light, executes the user authentication process and controls the charging operation through the interactive interface.

[0038] Once users observe that the charging station's indicator light has switched to the second state, they can verify the authenticity of the QR code and then begin the user authentication process through the mobile terminal's interface. The user authentication process includes two main steps: identity verification and payment authorization, ensuring the security of the charging service and the reliability of payment settlement.

[0039] Specifically, users first need to complete real-name authentication on the interactive interface. This can be done by entering a mobile phone number and verifying via SMS, or by linking an existing charging platform account. After successful authentication, users need to select a payment method and authorize payment, such as binding a bank card or setting a payment password. Once the authentication process is complete, the charging platform sends a start signal to the charging station, and the charging station begins charging.

[0040] In some embodiments, the problem of some charging piles being used excessively while others are idle, especially when users habitually choose fixed charging piles or prioritize charging piles near the entrance, can easily lead to uneven equipment wear, increased maintenance costs, and excessively long waiting times for users. Furthermore, the concentrated charging demand during peak hours exacerbates this uneven equipment usage. To address this, after the charging platform parses user requests, the system performs the following steps: First, it obtains real-time load data for each charging pile within the charging station. Based on the obtained real-time load data, the system calculates the historical usage frequency, cumulative usage time, and historical rating data for each charging pile. Next, the system dynamically calculates the charging service fee coefficient for each charging pile based on the historical usage frequency, cumulative usage time, and historical rating data. Specifically, the higher the historical usage frequency of a charging pile, the higher the corresponding charging service fee coefficient.

[0041] When the system detects that the historical usage frequency or cumulative usage time of the charging station corresponding to the user's scanned station exceeds a preset threshold, it will push information about other available charging stations nearby to the user's mobile terminal, including: location information, real-time status (such as idle, occupied, etc.), and real-time price discount information calculated based on the charging service fee coefficient. If the user chooses to switch to another charging station, the system will send a normal scan signal to the newly selected charging station accordingly.

[0042] Specifically, historical usage frequency is calculated by statistically analyzing the average daily usage over the past 30 days; cumulative usage time refers to the total charging time since the charging station was put into use, in hours; historical rating data is the weighted average of user ratings (1-5 points) for the charging experience. The system has preset thresholds including: a historical usage frequency threshold of 15 times per day and a cumulative usage time threshold of 3000 hours. When either indicator exceeds the corresponding threshold, the system classifies the charging station as being in a high-load state.

[0043] Furthermore, before dynamically calculating the charging service fee coefficient, the system first obtains the current timestamp and divides the day into multiple time intervals accordingly. Then, it statistically analyzes the timestamps from the historical usage records of the charging piles according to these time intervals to obtain time-period characteristic data. Based on this data, the system calculates the average waiting time, average charging time, and average idle time for each time interval. According to the ratio of these three durations, the system determines the congestion coefficient. When the congestion coefficient exceeds a first preset threshold, the system increases the charging service fee coefficient for that time interval by a preset increment; when the congestion coefficient is below a second preset threshold, the system decreases the charging service fee coefficient for that time interval by a preset decrement.

[0044] Specifically, the system divides a day into five time intervals: early morning, morning peak, daytime, evening peak, and nighttime. The congestion coefficient is calculated as: average waiting time / (average charging time + average idle time). The first preset threshold is set to 0.3, the second preset threshold is set to 0.1, and both the increment and decrement steps are set to 0.05.

[0045] In some embodiments, to address the problem of charging stations lacking user behavior management mechanisms and finding it difficult to effectively constrain malicious occupation, overdue payments, and other undesirable behaviors, the system first obtains the user's historical charging behavior data after the user completes authentication and begins charging. This data includes charging duration, charging frequency, charging fee settlement records, and charging anomaly records. Based on this historical data, the system establishes a credit scoring model and calculates the user's credit score. According to the user's credit score, the system provides differentiated services at different levels: when the user's credit score reaches a first preset value, they can enjoy a charging fee discount; when it reaches a second preset value, they gain priority access to reserve charging stations; and when it reaches a third preset value, the duration limit for a single charging session can be extended.

[0046] To promptly detect and handle abnormal behavior, the system compares users' real-time charging behavior with a pre-defined database of abnormal behavior characteristics. This database includes several typical patterns of undesirable behavior: overdue payment of charging fees (e.g., exceeding the payment deadline three times consecutively), repeated scanning without charging (e.g., scanning multiple times within 30 minutes without actually using the device), forced disconnection during charging (e.g., failing to end charging through the proper process), and malicious occupancy (e.g., failing to leave the vehicle after charging is completed within a preset time). When the system detects that a user's charging behavior matches these abnormal characteristics, it lowers the user's credit score accordingly and reduces or cancels their differentiated service level.

[0047] In the above embodiments, a convenient and safe charging start-up process is achieved by setting dynamically updatable QR codes on charging piles and combining this with a three-way linkage mechanism involving mobile terminal browsers, charging platforms, and charging pile indicator lights. Simultaneously, by introducing multiple protection mechanisms such as location-based security verification, load balancing based on device usage frequency, and credit rating based on user behavior, abnormal situations such as remote scanning, excessive device use, and malicious occupation are effectively prevented, improving the efficiency and safety of charging facilities. Furthermore, the system implements differentiated pricing and service strategies based on time-of-day characteristics and user credit scores, optimizing the allocation of charging resources and creating a favorable charging environment.

[0048] In the above embodiments, the system mainly improves the utilization efficiency of charging facilities by managing user behavior and charging demand. However, charging pile equipment may experience performance degradation and safety hazards during long-term operation, especially in charging stations in remote areas. Due to limited maintenance personnel and low maintenance frequency, equipment failure not only affects the user's charging experience but may also cause equipment damage. To further ensure the safe and stable operation of charging facilities, this application also provides another anti-fraud charging pile control method. The following is in conjunction with... Figure 2 Another anti-fraud charging pile control method in the embodiments of this application is described below: Please see Figure 2 This is another flowchart illustrating a fraud prevention charging pile control method in this application embodiment.

[0049] S201. Obtain the voltage, current, and temperature parameters of the charging pile to obtain the operating parameters.

[0050] Specifically, the system collects operational data in real time through the sensor network built into the charging pile. This includes voltage parameters such as input voltage, output voltage, and voltage fluctuation; current parameters such as charging current, leakage current, and current harmonic content; and temperature parameters such as charging interface temperature, power module temperature, and ambient temperature.

[0051] S202. Establish a charging pile operation status model based on the operating parameters.

[0052] The operational state model employs a multidimensional state-space representation, treating various operational parameters and their rates of change as state variables. The model assesses the correlation between parameters and the overall stability of the system by calculating the covariance matrix of these state variables in real time.

[0053] S203. Compare the parameter change trends in the operating status model with the preset fault feature library in real time.

[0054] The fault feature database includes abnormal voltage, abnormal current, and abnormal temperature features. The system uses a pattern recognition algorithm to match these features in real time.

[0055] S204. When the trend of any operating parameter deviates from the normal range but does not reach the preset fault standard, the preventive maintenance process is triggered.

[0056] The preventative maintenance process includes reducing charging power, adjusting charging current, activating cooling devices, and sending maintenance reminders to maintenance personnel.

[0057] S205. When any operating parameter exceeds the safe operating threshold, the charging interface will be automatically disconnected and a fault alarm message will be pushed to the maintenance personnel.

[0058] S206. Calculate the probability value of charging pile failure based on the preset fault prediction model, wherein the fault prediction model calculates the fault probability based on the operating parameters.

[0059] Specifically, when the probability value is within the first preset probability range, the charging pile is set to observation mode, and the changing trend of operating parameters is recorded. When the probability value is within the second preset probability range, the charging pile is set to maintenance mode, and charging power is limited. When the probability value is within the third preset probability range, the charging pile is set to disabled mode, and the charging interface is disconnected.

[0060] S207. Generate maintenance work orders of the corresponding level based on the status of the charging pile and assign them to maintenance personnel of the corresponding maintenance level.

[0061] Specifically, maintenance work orders are assigned to qualified maintenance personnel based on the status level, and include information such as fault prediction details, recommended maintenance measures, and processing time limits.

[0062] In the above embodiments, a multi-dimensional sensor network is deployed in the charging pile to collect key operating parameters such as voltage, current, and temperature in real time, and an operating status model is established based on these parameters. The system compares the operating status with a preset fault feature database in real time, and combines this with probability calculations from a fault prediction model to achieve early warning and tiered handling of equipment anomalies. Simultaneously, by setting different warning thresholds and response measures, a complete protection system from observation and maintenance to shutdown is established, ensuring the safe and stable operation of the charging facilities while improving the efficiency of maintenance resource utilization.

[0063] The system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of a fraud-proof charging pile control system provided in an embodiment of this application.

[0064] It should be noted that, Figure 3 The structure of the system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0065] like Figure 3As shown, the system includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 302 or a program loaded from storage portion 308 into Random Access Memory (RAM) 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0066] The following components are connected to I / O interface 305: input section 306 including a camera, infrared sensor, etc.; output section 307 including a liquid crystal display (LCD) and speakers, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card and a modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0067] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the various functions defined in the present invention.

[0068] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0070] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the system described in the above embodiments; or it may exist independently and not assembled into the system. The storage medium carries one or more computer programs that, when executed by a processor of a system, cause the system to implement the methods provided in the above embodiments.

[0071] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0072] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0073] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0074] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A fraud-prevention method for controlling charging piles, characterized in that, The method includes: In response to a QR code scanning operation by a mobile terminal browser, the QR code information on the charging pile is obtained, wherein the Uniform Resource Locator corresponding to the QR code contains the charging pile number information. Based on the obtained QR code information, the system automatically accesses the corresponding Uniform Resource Locator and sends a request to the charging platform. The request is parsed, interactive interface information is sent to the mobile terminal, and a normal scanning signal is sent to the charging pile corresponding to the pile number. In response to the normal scanning signal, the indicator light of the charging pile is controlled to switch from the first state to the second state; In response to the second state of the indicator light, the user authentication process is executed through the interactive interface and the charging operation is controlled.

2. The method according to claim 1, characterized in that, Before the step of switching the indicator light of the charging pile from the first state to the second state, the method further includes: Obtain the geographical location information of the mobile terminal; The geographical location information is compared with the installation location information of the charging pile; When the distance between the geographical location of the mobile terminal and the installation location of the charging pile exceeds a preset range, it is determined to be an abnormal scan, and the normal scan signal is prohibited from being sent to the charging pile.

3. The method according to claim 1, characterized in that, After the step of parsing the request, the method further includes: Obtain real-time load data of each charging pile in the charging station where the charging pile is located; Based on the real-time load data, calculate the historical usage frequency, cumulative usage time and historical rating data of each charging pile; Based on the historical usage frequency, cumulative usage time, and historical rating data, a charging service fee coefficient is dynamically calculated for each charging pile. The higher the historical usage frequency of a charging pile, the higher the corresponding charging service fee coefficient is set. When the historical usage frequency or cumulative usage time of the charging pile corresponding to the specified pile number exceeds a preset threshold, the location information, real-time status, and real-time price discount information calculated based on the charging service fee coefficient of other nearby available charging piles are pushed to the mobile terminal. In response to the user's selection of another charging station, the normal scan signal is sent to the charging station selected by the user.

4. The method according to claim 3, characterized in that, Prior to the step of dynamically calculating the charging service fee coefficient for each charging pile, the method further includes: Obtain the current timestamp and divide the day into multiple time intervals based on the current timestamp; The timestamps in the historical usage records of the charging piles are statistically analyzed according to the time intervals to obtain time period characteristic data; Based on the time period characteristic data, the average waiting time, average charging time and average idle time of the charging piles in each time interval are calculated. The congestion coefficient is determined based on the ratio of average waiting time, average charging time, and average idle time. When the congestion coefficient exceeds a first preset threshold, the charging service fee coefficient within the time interval is increased by a preset increment step; when the congestion coefficient is lower than a second preset threshold, the charging service fee coefficient within the time interval is decreased by a preset decrement step step.

5. The method according to claim 1, characterized in that, After the step of performing the user authentication process and controlling the charging operation through the interactive interface, the method further includes: Obtain the user's historical charging behavior data, which includes charging duration, charging frequency, charging fee settlement records, and charging anomaly records; A credit scoring model is established based on the historical charging behavior data, and the user's credit score is calculated. Differentiated services are provided based on the user's credit score. When the user's credit score reaches a first preset score, the differentiated services include discounts on charging fees; when the user's credit score reaches a second preset score, the differentiated services include priority booking privileges; and when the user's credit score reaches a third preset score, the differentiated services include extended charging time. The user's charging behavior is compared with a preset abnormal behavior feature database, which includes features such as overdue payment of charging fees, repeated scanning without charging, forced disconnection during charging, and malicious occupation. When a user's charging behavior is detected to match a feature in the abnormal behavior feature library, the user's credit score is adjusted and the differentiated service is adjusted accordingly.

6. The method according to claim 1, characterized in that, The method further includes: The voltage, current, and temperature parameters of the charging pile are obtained to determine the operating parameters. Establish a charging pile operation status model based on the aforementioned operating parameters; The parameter change trends in the operating state model are compared in real time with a preset fault feature library, wherein the fault feature library includes voltage anomaly features, current anomaly features, and temperature anomaly features. When the trend of any operating parameter deviates from the normal range but does not reach the preset fault standard, a preventive maintenance process is triggered. The preventive maintenance process includes reducing the charging power, adjusting the charging current, activating the heat dissipation device, and sending maintenance reminder information to the operation and maintenance personnel. When any operating parameter exceeds the safe operating threshold, the charging interface will be automatically disconnected and a fault alarm message will be pushed to the maintenance personnel.

7. The method according to claim 6, characterized in that, The method further includes: The probability value of the charging pile malfunctioning is calculated according to a preset fault prediction model, wherein the fault prediction model calculates the fault probability based on the operating parameters. When the probability value is within the first preset probability range, the charging pile is set to observation mode, and the changing trend of the operating parameters is recorded; when the probability value is within the second preset probability range, the charging pile is set to maintenance mode, and the charging power is limited; when the probability value is within the third preset probability range, the charging pile is set to deactivated mode, and the charging interface is disconnected. Based on the status of the charging pile, a maintenance work order of the corresponding level is generated and assigned to the maintenance personnel of the corresponding maintenance level.

8. A fraud-proof charging pile control system, characterized in that, The system includes: One or more processors and a memory; the memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are executed on the system, the system performs the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the system, the system performs the method as described in any one of claims 1-7.

Images