A charging pile control method and system based on fingerprint recognition

Abstract

The present invention discloses a charging pile control method and system based on fingerprint recognition, which relates to the technical field of charging piles. By using an ultrasonic fingerprint sensor for identity authentication in step S1, fast and accurate user identity recognition can be achieved, effectively preventing illegal users from using charging piles. At the same time, the comparison mechanism of the matching degree Ppd and the pre-set threshold P can ensure the robustness and flexibility of authentication, further reduce the authentication misidentification rate and rejection rate, and improve the security of the system and user experience. In step S3, the comprehensive stability score Wpz constructed based on the monitoring data set can quantitatively evaluate the operating stability of the charging pile and provide a decision-making basis for optimizing the charging plan. When the stability of the charging pile is poor, the charging plan can be adjusted or the optimization mechanism can be started to extend the life of the equipment and avoid charging interruptions.

Description

Technical Field

[0001] The present invention relates to the technical field of charging piles, and in particular to a charging pile control method and system based on fingerprint recognition. Background Art

[0002] Charging pile control technology belongs to the large field of intelligent management of power equipment, involving multiple technical directions such as power transmission, intelligent power consumption and new energy utilization. With the popularization of new energy vehicles and the development of charging infrastructure, charging pile technology is gradually developing in a more efficient, convenient and safe direction. As part of the intelligent charging system, charging pile control technology based on biometric recognition (such as fingerprint recognition) combines the functions of identity authentication and power management, which can effectively improve the safety of charging equipment and user experience. Fingerprint recognition technology has received widespread attention in the authentication link of charging piles due to its accuracy and strong anti-counterfeiting ability, providing users with a more convenient and reliable authentication method.

[0003] Although the application of fingerprint recognition technology in charging piles has certain advantages, the existing fingerprint authentication mechanism still faces many challenges. For example, the existing system lacks dynamic optimization of the authentication threshold. Specifically, the selection of the authentication threshold usually depends on the system's requirements for security and convenience. If the system tends to be high security, a higher authentication threshold is set to reduce the false recognition rate. If the system tends to be high convenience, a lower authentication threshold is set to reduce the rejection rate. Then how to find the balance between the rejection rate and the false recognition rate? At this time, the authentication threshold needs to be dynamically optimized. In addition, although it is popular to have one charging pile per household, which can bring convenience to users and reduce the unstable power supply, if private charging piles and other charging piles share the same distribution network but have independent meters, they may still be indirectly affected by grid stability problems (such as three-phase imbalance, harmonics and local voltage drops, etc.), so real-time monitoring of the power supply network, equipment operation and external interference is very necessary.

[0004] The above problems arise mainly because the traditional charging pile design fails to combine advanced biometric technology and intelligent data analysis methods, and lacks the ability to dynamically perceive and optimize user behavior and equipment operating status. This deficiency not only increases the inconvenience of user use, but may also cause a series of abnormal phenomena: for example, in the authentication process, illegal users often use charging piles in an unauthorized manner; in the operation process, due to the failure to detect and respond in time to problems such as voltage fluctuations and harmonic interference, the equipment may become unstable or even damaged. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a charging pile control method and system based on fingerprint recognition, which solves the problems in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A charging pile control method based on fingerprint recognition, comprising the following steps:

[0007] S1. Use an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified, and match the fingerprint image of the user to be verified with the registration data in the database to obtain a matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P;

[0008] S2. When the authentication pass signal is generated, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference situation of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, and after data preprocessing, a monitoring data set is generated;

[0009] S3. Analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz;

[0010] S4. Use historical data and combine it with the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, regularly send charging reminders to users to enter the charging mode.

[0011] Preferably, the specific steps of S1 include:

[0012] S11, using an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified in advance, and performing image region segmentation on the fingerprint image of the user to be verified to identify and extract several groups of feature values, and generate a fingerprint feature vector of the user to be verified after statistics. The registration data in the database includes the fingerprint feature vector of the authorized user ; Among them, the fingerprint feature vector of the user to be verified is It includes the feature value at each feature point and the feature value of each image area;

[0013] S12, by the fingerprint feature vector of the user to be verified Match with the registration data in the database to obtain the matching degree Ppd, which is obtained by the following formula:

[0014] ;

[0015] In the formula, It is represented as the matching degree corresponding to the jth user to be verified, n is represented as the dimension of the feature vector, i=1, 2, 3, ..., n, Represented as the i-th eigenvalue in the fingerprint feature vector of the user to be verified, Represented as the i-th eigenvalue in the fingerprint feature vector of the authorized user, Expressed as and The dot product of It is represented as the modulus of the fingerprint feature vector of the user to be verified. It is expressed as the modulus of the authorized user's fingerprint feature vector.

[0016] Preferably, the specific step S1 also includes:

[0017] S13, presetting a matching threshold P, the steps for setting the matching threshold P are as follows:

[0018] S131. Collecting fingerprint feature vectors of several groups of authorized users in advance , by performing fingerprint recognition on each authorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as matching degrees No. , according to the matching degree of No. , construct the matching probability density function of authorized users ;

[0019] S132: Collect fingerprint feature vectors of several groups of unauthorized users in advance , by performing fingerprint recognition on each unauthorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as the second matching degree , according to the matching degree of No. , construct the matching probability density function of unauthorized users ;

[0020] S133, matching probability density function based on unauthorized users And the matching probability density function of authorized users , draw the ROC curve, based on the ROC curve, analyze the relationship between the true positive rate and the false positive rate under different thresholds x, and extract the matching threshold P from it. The specific expression is as follows:

[0021] ;

[0022] In the formula, represents the objective function; It means finding the x value that maximizes the objective function value. Indicates the matching degree of authorized users under threshold x The probability of threshold x; represents the probability that the matching value of an unauthorized user is less than the threshold value x under the threshold value x; ;

[0023] ;

[0024] S14, by comparing and analyzing the extracted matching threshold value P with the matching degree Ppd, to determine whether the current user to be verified is an authorized user, the specific determination content is as follows:

[0025] If the matching degree Ppd exceeds the matching threshold P, it means that the user to be verified is an authorized user, and an authentication pass signal will be generated;

[0026] If the matching degree Ppd does not exceed the matching threshold P, it means that the user to be verified is not an authorized user, and an authentication failure signal will be generated.

[0027] Preferably, the specific steps of S2 include:

[0028] S21. After receiving the authentication signal sent in S14, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference status of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, wherein the relevant power supply quality data includes the actual value of the R phase current in the three-phase AC circuit at the input end of the charging pile. , Actual value of S phase current , Actual value of T phase current , R phase relative to the neutral point voltage value , S phase relative to neutral point voltage value And the voltage value of phase T relative to the neutral point ; The relevant operating data includes line impedance And the equivalent current of the three-phase total current ; The relevant interference data includes the effective value of the fundamental current , the effective value of the corresponding harmonic current, the transmission power of the interference source , Antenna gain and the distance between the charging pile and the adjacent charging piles ;

[0029] S22, fill missing values, remove abnormal values, delete duplicate values ​​and remove noise for the relevant power supply quality data, relevant operation data and relevant interference data obtained in S21, and use dimensionless processing technology to standardize the pre-processed data to generate a monitoring data set;

[0030] S23. After receiving the authentication failure signal sent in S14, the charging pile continues to remain in the standby state and stores the authentication failure in the monitoring data set.

[0031] Preferably, the specific steps of S3 include:

[0032] S31. Analyze the distribution of three-phase current and three-phase voltage between the power supply interface from the power distribution network to the charging pile according to the relevant power supply quality data in the monitoring data set to obtain the three-phase current unbalance coefficient. And three-phase voltage unbalance coefficient , the three-phase current unbalance coefficient And the three-phase voltage unbalance coefficient The specific formula is as follows:

[0033] ;

[0034] In the formula, , and They represent the actual current values ​​of the R phase, S phase and T phase in the three-phase AC circuit respectively. Expressed as the average value of three-phase current;

[0035] ;

[0036] In the formula, , and It is expressed as the voltage value of each phase relative to the neutral point; Expressed as the average value of three-phase voltage.

[0037] Preferably, the specific step S3 also includes:

[0038] S32. Analyze the impact of energy loss of the power transmission system on the charging pile according to the relevant operating data in the monitoring data set to obtain the voltage drop value , the voltage drop value Obtained by the following formula:

[0039] ;

[0040] In the formula, represents the line impedance, Indicates the equivalent current of the three-phase total current;

[0041] S33. At the same time, according to the relevant interference data in the monitoring data set, the harmonic superposition status generated by the charging pile during operation and the communication interference caused by the electromagnetic radiation superposition of the adjacent charging piles around the charging pile are analyzed to obtain the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq. The total harmonic distortion rate Zxb is obtained by the following formula:

[0042] ;

[0043] In the formula, Expressed as the effective value of the mth harmonic current, It is expressed as the effective value of the fundamental current, and m is the harmonic number; It represents the distortion rate of all higher harmonics starting from the second harmonic, and M represents the cutoff frequency;

[0044] The total electromagnetic interference field strength Cq is obtained by the following formula:

[0045] ;

[0046] In the formula, Expressed as the transmission power of the interference source, Expressed as antenna gain, Expressed as the distance between the charging pile and the adjacent charging pile; Represents the field strength generated by the corresponding charging pile, k=1, 2, 3, ..., K, K represents the number of adjacent charging piles.

[0047] Preferably, the specific step S3 also includes:

[0048] S34: the three-phase current unbalance coefficient obtained based on S31, S32 and S33 , the three-phase voltage unbalance coefficient , the voltage drop value , the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq are associated, and after dimensionless processing, the comprehensive stability score Wpz of the current charging pile in the corresponding period is obtained by fitting, which is specifically obtained by the following formula:

[0049] ;

[0050] In the formula, , 2. 3. 4 and 5 represent the three-phase current unbalance coefficient , three-phase voltage unbalance coefficient , voltage drop value , the weight values ​​of total harmonic distortion rate Zxb and total electromagnetic interference field strength Cq, the specific values ​​are set by the user according to the situation;

[0051] S35, pre-set the safety threshold Q, and compare and analyze the comprehensive stability score Wpz of the current charging pile in the corresponding period with the safety threshold Q to comprehensively judge the stability performance of the current charging pile during operation. The specific judgment content is as follows:

[0052] If the comprehensive stability score Wpz exceeds the safety threshold Q, it is judged that the current charging pile is in an unstable state during operation. At this time, the optimization instruction will be triggered to start the optimization mechanism;

[0053] If the comprehensive stability score Wpz does not exceed the safety threshold Q, it is judged that the current charging pile is in a stable state during operation, and the monitoring operation will continue.

[0054] Preferably, the specific steps of S4 include:

[0055] S41, after receiving the optimization instruction sent from S35, start the optimization mechanism, the specific steps of starting the optimization mechanism are as follows:

[0056] S411. Using historical data, determine the time period during which the user charges via the charging pile in the historical period, record it as the working period, and analyze and calculate the minimum fee to be paid during the working period in combination with the regional time-of-use electricity price mechanism. , which can be obtained by:

[0057] ;

[0058] ;

[0059] In the formula, Indicates the fees required to apply for the unified electricity price model. Indicates the fees to be paid when applying for the time-of-use electricity price model. represents the average charging power, Indicates the total charging time. represents a fixed electricity price, represents the charging power of the fth charging period, represents the duration of the fth charging period, represents the electricity price of the fth charging period, and F represents the number of charging periods that the user crosses when charging when applying for the time-of-use electricity price mode; f=1, 2, 3, ..., F;

[0060] S412. Fees to be paid when applying for the unified electricity price model Fees required to apply for time-of-use electricity price model Compare the size to find the minimum fee and mark the minimum fee .

[0061] Preferably, the specific step S4 also includes:

[0062] S42. The minimum fee obtained in S41 , initially recommends users to apply for the minimum fee The corresponding electricity price model is used to complete the No. 1 optimization mechanism. Combined with the comprehensive stability score Wpz in the historical period, based on the No. 1 optimization mechanism, the user is recommended a time period for charging, and the vehicle to be charged is reminded through SMS reminders to complete the No. 2 optimization mechanism.

[0063] Among them, the electricity price model includes the unified electricity price model and the time-of-use electricity price model;

[0064] Among them, the optimization mechanism includes optimization mechanism No. 1 and optimization mechanism No. 2.

[0065] A charging pile control system based on fingerprint recognition, including an authentication module, a data acquisition module, a stability performance analysis module and an optimization control module;

[0066] The authentication module is used to collect the fingerprint image of the user to be authenticated by using the ultrasonic fingerprint sensor, and match the fingerprint image of the user to be authenticated with the registration data in the database to obtain the matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P;

[0067] The data acquisition module is used to start the charging mechanism when the authentication pass signal is generated, and to monitor the quality status, operation status and external environmental interference situation of the power supply network in real time during the operation of the charging pile, so as to obtain relevant power supply quality data, relevant operation data and relevant interference data, and generate a monitoring data set after data preprocessing;

[0068] The stability performance analysis module is used to analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz;

[0069] The optimization control module is used to utilize historical data and combine the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, a charging reminder is regularly issued to the user to enter the charging mode.

[0070] The present invention provides a charging pile control method and system based on fingerprint recognition, which has the following beneficial effects:

[0071] (1) Through the use of ultrasonic fingerprint sensors for identity authentication in step S1, fast and accurate user identity recognition can be achieved, effectively preventing illegal users from using charging piles. At the same time, the comparison mechanism of the matching degree Ppd and the pre-set threshold P can ensure the robustness and flexibility of authentication, further reduce the authentication misidentification rate and rejection rate, and improve the security of the system and user experience. In step S3, the comprehensive stability score Wpz constructed based on the monitoring data set can quantitatively evaluate the operating stability of the charging pile and provide a decision-making basis for optimizing the charging plan. When the stability of the charging pile is poor, the charging plan can be adjusted or the optimization mechanism can be started to extend the life of the equipment and avoid charging interruptions. At the same time, combined with the historical data in step S4 and the regional time-of-use electricity price mechanism, the electricity consumption plan can be intelligently matched. Users can choose the charging time based on relatively low electricity prices and relatively good stability scores to reduce charging costs as much as possible. The present invention utilizes the synergistic effect of the comprehensive stability score Wpz and the time-of-use electricity price mechanism, and combines historical electricity consumption data to regularly send charging reminders to users. This mechanism not only facilitates users to reasonably arrange charging plans and avoid additional costs caused by peak electricity consumption, but also effectively alleviates the load pressure on the power grid and achieves the purpose of peak shaving and valley filling, thereby improving the operating efficiency of the power grid and the overall user experience.

[0072] (2) The present invention collects the fingerprint image of the user to be verified through an ultrasonic fingerprint sensor, and uses image region segmentation technology to identify and extract key feature values ​​such as bifurcation points, intersection points, ridge density and ridge spacing from the fingerprint image to generate a high-precision fingerprint feature vector. By combining coordinate and angular information to characterize the position and direction of the feature points, the expression ability and discrimination of the feature vector are improved. This multi-dimensional feature extraction method can not only more accurately reflect the local characteristics and overall distribution of the fingerprint, but also effectively deal with the recognition difficulties caused by fingerprint blur and damage. Furthermore, a mathematical model is used to match the fingerprint feature vector of the user to be verified with the fingerprint feature vector of the registered user in the database, and the matching degree Ppd is calculated by a formula to quantify the similarity between the user to be verified and the registered user in the feature space in multiple dimensions.

[0073] (3) The present invention can significantly improve the accuracy and robustness of fingerprint recognition authentication by setting the matching threshold P based on statistical and probability analysis methods. By constructing matching probability density functions for the fingerprint feature vectors of authorized users and unauthorized users respectively, and comprehensively analyzing the distribution characteristics of the two types of users in terms of matching, the accuracy and efficiency of charging pile user authentication are further improved, so as to find a balance between the false recognition rate and the rejection rate. In addition, by comparing the extracted matching threshold P with the matching degree Ppd of the user to be verified in real time, the user identity can be quickly determined and the corresponding authentication signal can be generated. The authentication pass signal can quickly start subsequent operations, while the authentication fail signal ensures that unauthorized users cannot access the charging pile, further enhancing the security of the system.

[0074] (4) This method effectively improves the safety and stability of charging pile operation through a comprehensive analysis of energy loss, voltage drop, harmonic superposition and electromagnetic interference in the power transmission system. Based on the analysis of these phenomena, a comprehensive stability score Wpz is constructed, which provides a scientific and quantitative basis for the comprehensive evaluation of the operating status of the charging pile, and automatically determines whether the charging pile is in a stable operating state. When it is unstable, the system issues an optimization instruction to start the optimization mechanism. By constructing a dual optimization analysis model of unified electricity price and time-of-use electricity price, as well as a dynamic adjustment strategy combined with the charging pile operation stability score, it not only saves charging costs for users, but also ensures the safety and reliability of the charging process. At the same time, this mechanism helps the power grid to achieve peak shaving and valley filling, optimize regional power resource allocation, and provide more intelligent and efficient charging support for the popularization of new energy vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is a schematic flow chart of a charging pile control method based on fingerprint recognition according to the present invention;

[0076] Figure 2 This is a block diagram of a charging pile control system based on fingerprint recognition in the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] Example 1

[0079] See also Figure 1 The present invention provides a charging pile control method based on fingerprint recognition, comprising the following steps:

[0080] S1. Use an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified, and match the fingerprint image of the user to be verified with the registration data in the database to obtain a matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P;

[0081] S2. When the authentication pass signal is generated, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference situation of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, and after data preprocessing, a monitoring data set is generated;

[0082] S3. Analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz;

[0083] S4. Use historical data and combine it with the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, regularly send charging reminders to users to enter the charging mode.

[0084] In this embodiment, the method realizes efficient and secure user identification by using an ultrasonic fingerprint sensor to collect and match the user's fingerprint, which can effectively prevent unauthorized illegal users from using the charging pile, thereby improving the safety and reliability of the charging pile. The preset matching threshold P combined with the matching degree Ppd is used to automatically generate an authentication signal, which not only simplifies the user operation process, but also improves the authentication efficiency and optimizes the user experience. During the operation of the charging pile, the system monitors the quality of the power supply network, the operating status and the external interference in real time, and generates a monitoring data set through data preprocessing, which can dynamically reflect the power supply status and external environment changes during the charging process. By constructing a comprehensive stability score Wpz, the system can accurately evaluate the operating stability of the charging pile, provide users with stable and reliable charging services, and can timely identify potential abnormal conditions, initiate optimization measures, and avoid equipment damage or reduced operating efficiency. In addition, the present invention combines user historical data and regional time-of-use electricity price mechanism to match users with relatively better electricity consumption plans and reduce users' charging costs. In particular, under the time-of-use electricity price mechanism, the system can intelligently generate charging reminders based on the dynamic adjustment function of the comprehensive stability score Wpz to ensure that users charge during periods of low electricity prices and stable power supply, further improving electricity efficiency and economy. Through the above comprehensive design, the present invention realizes the intelligent and personalized control of charging piles, significantly improving the operating efficiency, safety and user satisfaction of charging piles.

[0085] Example 2

[0086] Please refer to Figure 1 , specifically: S1 specific steps include:

[0087] S11, using an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified in advance, and performing image region segmentation on the fingerprint image of the user to be verified to identify and extract several groups of feature values, and generate a fingerprint feature vector of the user to be verified after statistics. The registration data in the database includes the fingerprint feature vector of the authorized user ; Among them, the fingerprint feature vector of the user to be verified is It includes the feature values ​​at each feature point and the feature values ​​of each image area.

[0088] Among them, each feature point is represented by coordinates and direction angles, that is, ; The characteristic values ​​include but are not limited to the bifurcation points and intersection points on the corresponding characteristic points, the grain line density and ridge line spacing in the corresponding image area;

[0089] S12, by the fingerprint feature vector of the user to be verified Match with the registration data in the database to obtain the matching degree Ppd, which is obtained by the following formula:

[0090] ;

[0091] In the formula, It is represented as the matching degree corresponding to the jth user to be verified, n is represented as the dimension of the feature vector, that is, the total number of fingerprint feature points, i=1, 2, 3, ..., n, Represented as the i-th eigenvalue in the fingerprint feature vector of the user to be verified, Represented as the i-th eigenvalue in the fingerprint feature vector of the authorized user, Expressed as and The dot product of and Common features in each dimension; It is represented as the modulus of the fingerprint feature vector of the user to be verified. It is expressed as the modulus of the authorized user's fingerprint feature vector.

[0092] In this embodiment, the method realizes high-precision extraction and matching of fingerprint features through step S1, effectively improving the accuracy and security of user authentication. Specifically, the ultrasonic fingerprint sensor is used to collect the fingerprint image of the user to be verified, and the image is segmented and feature value extracted to generate a fingerprint feature vector containing multi-dimensional features such as bifurcation points, intersection points, ridge density and ridge spacing, so that the feature description of the fingerprint is more comprehensive and detailed, and the reliability and anti-counterfeiting ability of the matching are improved. The calculation formula of the matching degree Ppd adopts the vector dot product method to compare the fingerprint feature vector of the user to be verified with the feature vector in the registered user database in multiple dimensions. By calculating the angle and amplitude difference between the two feature vectors, the formula can measure the similarity of the fingerprint in each feature dimension from multiple aspects, and can accurately reflect the matching of the fingerprint. Through the above design, the method further improves the accuracy and efficiency of the user authentication of the charging pile, so as to find a balance between the false recognition rate and the rejection rate. At the same time, based on the extracted multi-dimensional feature values ​​and matching algorithms, the system can flexibly respond to the complex distribution of user fingerprint features, further enhancing the security of the authentication process. Combined with the high resolution of ultrasonic sensors and the diversity of feature extraction, the reliability of the authentication results is ensured, laying a solid technical foundation for the safe operation of charging piles.

[0093] Example 3

[0094] Please refer to Figure 1 Specifically: S1 includes the following steps:

[0095] S13, presetting a matching threshold P, the steps for setting the matching threshold P are as follows:

[0096] S131. Collecting fingerprint feature vectors of several groups of authorized users in advance , by performing fingerprint recognition on each authorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as matching degrees No. , according to the matching degree of No. , construct the matching probability density function of authorized users ;

[0097] S132: Collect fingerprint feature vectors of several groups of unauthorized users in advance , by performing fingerprint recognition on each unauthorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as the second matching degree , according to the matching degree of No. , construct the matching probability density function of unauthorized users ;

[0098] S133, matching probability density function based on unauthorized users And the matching probability density function of authorized users , draw the ROC curve, based on the ROC curve, analyze the relationship between the true positive rate (rejection rate) and the false positive rate (error recognition rate) under different thresholds x, and extract the matching threshold P from it. The specific expression is as follows:

[0099] ;

[0100] This formula is based on probability statistics and finds a relatively good dividing point by measuring the overlapping areas of the two parts of the matching degree distribution; where: represents the objective function; It means finding the x value that maximizes the objective function value. Indicates the matching degree of authorized users under threshold x The probability of threshold x; represents the probability that the matching value of an unauthorized user is less than the threshold value x under the threshold value x;

[0101] ;

[0102] ;

[0103] in, Indicates the integral of the matching degree, the upper and lower limits of the integral, the lower limit x refers to the currently set matching degree threshold, and the integral starts from x, indicating that only users with a matching degree greater than x are counted; the upper limit 1 refers to the maximum value of the matching degree, indicating the end point of the probability density function of the matching degree.

[0104] Obtained by the following formula: in, It is expressed as the average matching degree, reflecting the central position of the distribution; It is expressed as the standard deviation of the matching degree, which reflects the width of the distribution, that is, the degree of dispersion of the data; represents the exponential function; Expressed as a mathematical parameter, the value is approximately 3.1415927;

[0105] The rejection rate mentioned above refers to the probability that a registered user is misidentified as an illegal user; the false recognition rate refers to the probability that an unregistered user is misidentified as a legitimate user;

[0106] S14, by comparing and analyzing the extracted matching threshold value P with the matching degree Ppd, to determine whether the current user to be verified is an authorized user, the specific determination content is as follows:

[0107] If the matching degree Ppd exceeds the matching threshold P, it means that the user to be verified is an authorized user, and an authentication pass signal will be generated;

[0108] If the matching degree Ppd does not exceed the matching threshold P, it means that the user to be verified is not an authorized user, and an authentication failure signal will be generated.

[0109] In this embodiment, the method accurately analyzes the distribution characteristics of the matching degree of authorized users and unauthorized users by constructing the probability density function of the matching degree of the two types of users, thereby ensuring the scientificity and accuracy of the authentication threshold P. Based on the analysis of the ROC curve, the present invention can achieve a relatively good balance between the true positive rate (rejection rate) and the false positive rate (error recognition rate), and dynamically extract the matching threshold P that maximizes the objective function value. The threshold effectively distinguishes between legitimate users and illegal users, and further reduces the phenomenon of false recognition and rejection caused by improper thresholds. By introducing the mathematical model of the probability density function, the mean value and standard deviation of the matching degree are used to accurately reflect the central position and discrete degree of the distribution, and the system has a stronger generalization ability in a diverse user group. In addition, the integral calculation and exponential function fitting method are adopted to make the calculation result of the matching threshold have higher accuracy and robustness, and the authentication performance can be kept stable even in a noisy environment or boundary conditions (such as the matching degree is close to the threshold). Finally, the system accurately determines whether the user is an authorized user by comparing the matching degree Ppd with the threshold P. For users who exceed the threshold, the system generates an authentication pass signal to quickly start the charging mechanism; for users who do not reach the threshold, the system generates an authentication fail signal to effectively prevent illegal users from accessing. This authentication mechanism based on data statistics and intelligent analysis significantly improves the safety of charging piles and the reliability of user identity recognition, while optimizing the user experience.

[0110] Example 4

[0111] Please refer to Figure 1 , specifically: S2 specific steps include:

[0112] S21. After receiving the authentication signal sent in S14, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference status of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, wherein the relevant power supply quality data includes the actual value of the R phase current in the three-phase AC circuit at the input end of the charging pile. , Actual value of S phase current , Actual value of T phase current , R phase relative to the neutral point voltage value , S phase relative to neutral point voltage value And the voltage value of phase T relative to the neutral point ; The relevant operating data includes line impedance And the equivalent current of the three-phase total current ; The relevant interference data includes the effective value of the fundamental current , the effective value of the corresponding harmonic current, the transmission power of the interference source , Antenna gain and the distance between the charging pile and the adjacent charging piles ;

[0113] S22, fill missing values, remove abnormal values, delete duplicate values ​​and remove noise for the relevant power supply quality data, relevant operation data and relevant interference data obtained in S21, and use dimensionless processing technology to standardize the pre-processed data to generate a monitoring data set;

[0114] S23. After receiving the authentication failure signal sent in S14, the charging pile continues to remain in the standby state and stores the authentication failure in the monitoring data set.

[0115] The specific steps of S3 include:

[0116] S31. Analyze the distribution of three-phase current and three-phase voltage between the power supply interface from the power distribution network to the charging pile (i.e., the three-phase AC power access point or the input end of the charging pile) according to the relevant power supply quality data in the monitoring data set to obtain the three-phase current unbalance coefficient And three-phase voltage unbalance coefficient , the three-phase current unbalance coefficient And the three-phase voltage unbalance coefficient The specific formula is as follows:

[0117] ;

[0118] In the formula, , and They represent the actual current values ​​of the R phase, S phase and T phase in the three-phase AC circuit respectively. Expressed as the average value of three-phase current;

[0119] The actual current values ​​of the R phase, S phase and T phase in the above three-phase AC circuit can be monitored and obtained by a current transformer or a Hall effect current sensor;

[0120] Three-phase current unbalance coefficient Used to measure whether the three-phase load is evenly distributed. Current imbalance may cause equipment overheating and increased power loss;

[0121] ;

[0122] In the formula, , and It is expressed as the voltage value of each phase relative to the neutral point (usually the zero line), that is, the voltage value of the R phase relative to the neutral point, the voltage value of the S phase relative to the neutral point, and the voltage value of the T phase relative to the neutral point; Expressed as the average value of three-phase voltage;

[0123] The voltage value of each phase relative to the neutral point (usually the neutral line) can be monitored and obtained through a voltage transformer or a voltage divider;

[0124] Three-phase voltage unbalance coefficient Used to measure the symmetry of three-phase voltage. Voltage imbalance may cause abnormal operation of equipment and reduced efficiency.

[0125] It should be noted that three-phase electricity is the most common power supply method in the power system. It consists of three phase lines (R, S, and T phases) and a neutral line. Ideally, the voltage (or current) amplitudes of these three-phase electricity are equal, and the phases differ by 120° from each other, forming a symmetrical three-phase power supply; the three-phase imbalance of the regional distribution network will be transmitted to the low-voltage side of the distribution transformer. If the transformer outputs asymmetric three-phase voltage amplitude and phase, the private charging piles connected to this transformer for power supply will also receive unbalanced voltage.

[0126] The above-mentioned real-time monitoring of the power supply network quality, operating status and external environmental interference during the operation of the charging pile effectively improves the safety, stability and intelligent level of the operation of the charging pile. The monitoring system comprehensively collects the power supply quality data such as the current, voltage, line impedance and total current of the three-phase circuit at the input end of the charging pile, as well as the fundamental current, harmonic current and environmental electromagnetic interference data. By filling missing values, removing abnormal values ​​and standardizing these data, a high-quality monitoring data set is generated, which provides reliable data support for subsequent operation status evaluation. By performing distribution analysis on the three-phase current and three-phase voltage in the monitoring data set, the present invention constructs the three-phase current imbalance coefficient and the three-phase voltage imbalance coefficient, which can accurately reflect whether the three-phase load distribution is uniform and whether the voltage symmetry is normal. In addition, real-time monitoring of line impedance and equivalent total current, combined with comprehensive analysis of harmonic current and interference data, can further ensure the stability of the operating environment of the charging pile. Under the premise of passing the certification, the present invention starts the monitoring and evaluation mechanism, which can dynamically evaluate the health status of the power supply network and the operating stability of the charging pile, thereby realizing intelligent control and optimization during the charging process. Even if the authentication fails, the system can still store the authentication failure record in the monitoring data set, providing a basis for subsequent user behavior analysis. Through the above design, this method further improves the power supply quality monitoring capability of the charging pile, effectively reduces the operation risk caused by power supply abnormalities or environmental interference, and provides users with more reliable, safe and efficient charging services.

[0127] The specific steps of S3 also include:

[0128] S32. Analyze the impact of energy loss of the power transmission system on the charging pile according to the relevant operating data in the monitoring data set to obtain the voltage drop value , the voltage drop value Obtained by the following formula:

[0129] ;

[0130] In the formula, represents the line impedance, Indicates the equivalent current of the three-phase total current, that is, the average value of the three-phase current ;

[0131] Line impedance Obtained by the following formula: ;in, Indicates line resistance, which determines power loss; Represents the line reactance, which is mainly determined by the inductance effect;

[0132] The above line resistance Indicates the resistance value of the conductor in the power supply line, which affects the power loss of the line. It can be monitored and obtained through a DC resistance tester or a line impedance analyzer.

[0133] Line Reactance It can be monitored and obtained through an impedance analyzer or reactance tester;

[0134] Voltage drop value It reflects the difference between the voltage at the supply point (upstream voltage) and the voltage at the load end (downstream voltage), which is usually caused by the impedance of the wire and the load current.

[0135] S33. At the same time, according to the relevant interference data in the monitoring data set, the harmonic superposition status generated by the charging pile during operation and the communication interference caused by the electromagnetic radiation superposition of the adjacent charging piles around the charging pile are analyzed to obtain the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq. The total harmonic distortion rate Zxb is obtained by the following formula:

[0136] ;

[0137] In the formula, Expressed as the effective value of the mth harmonic current, It is expressed as the effective value of the fundamental current, reflecting the amplitude of the basic frequency component in the signal. m is the serial number of the harmonic, indicating that the frequency of the harmonic is an integer multiple of the fundamental frequency. It represents the distortion rate of all higher harmonics (m=3, m=4, …, m=M) accumulated starting from the second harmonic (m=2). It starts from m=2 because the fundamental wave (m=1) is not a harmonic and the harmonic is an integer multiple of the fundamental wave frequency. M represents the cutoff frequency. In practical applications, it is impossible to calculate all harmonics (especially very high-order harmonics). Therefore, a reasonable cutoff frequency M is usually selected. The cutoff frequency M is usually in the range of 40~50, depending on the accuracy requirements of the analysis and the frequency range of the measurement equipment.

[0138] The effective value of the corresponding harmonic current mentioned above represents the current amplitude at a specific harmonic frequency, which is used to analyze the harmonic pollution in the power grid and can be monitored and obtained by a harmonic analyzer;

[0139] The effective value of fundamental current It is the current effective value of the fundamental component in the signal (i.e. the frequency is the grid frequency, such as 50Hz or 60Hz), which can also be monitored and obtained by a harmonic analyzer;

[0140] The total electromagnetic interference field strength Cq is obtained by the following formula:

[0141] ;

[0142] In the formula, Expressed as the transmission power of the interference source, Expressed as antenna gain, Expressed as the distance between the charging pile and the adjacent charging pile; Represents the field strength generated by the corresponding charging pile, k=1, 2, 3, ..., K, K represents the number of adjacent charging piles (interference sources).

[0143] The transmission power of the above interference sources Refers to the electromagnetic interference source power generated by the nearby charging piles or other electrical equipment during operation, which can be monitored and obtained through a spectrum analyzer or electromagnetic interference (EMI) probe;

[0144] Antenna gain Indicates the ability of an antenna to radiate electromagnetic waves in a certain direction. The gain value compared with a non-directional antenna can be monitored by a network analyzer.

[0145] The distance between the charging pile and the adjacent charging pile It can be monitored and acquired through ultrasonic ranging sensors or laser rangefinders.

[0146] In this embodiment, the method provides a basis for improving the stability and anti-interference ability of the charging pile during operation by comprehensively analyzing the energy loss and external interference conditions of the power transmission system. By real-time monitoring and calculating the equivalent current of the line impedance and the three-phase total current, the method can accurately obtain the voltage drop value and effectively reflect the voltage loss between the power supply point and the load end. Through the careful analysis of the resistance and reactance in the line impedance, the method can deeply evaluate the influence of power loss and inductive load characteristics on the power supply quality, thereby providing a scientific basis for power grid optimization and equipment protection. In terms of external interference, the method comprehensively quantifies the harmonic content in the charging pile power supply signal by monitoring the harmonic current condition of the charging pile during operation and calculating the total harmonic distortion rate Zxb. By accumulating the high-order harmonic distortion rate starting from the second harmonic, the present invention can effectively identify the distortion caused by nonlinear loads in the signal, and provide accurate data support for power grid quality assessment and harmonic governance. In addition, by calculating the electromagnetic radiation superposition field strength Cq of the charging pile near the charging pile around the charging pile, the present invention can evaluate the potential impact of electromagnetic interference on communication and charging equipment in real time, and prevent signal interruption or equipment failure caused by excessive interference. In summary, the present invention can not only dynamically monitor the voltage stability of the power supply network, but also timely identify the impact of external interference sources on the operation of the charging pile, providing strong data support for optimized control and abnormal warning during the charging process.

[0147] Example 5

[0148] Please refer to Figure 1 , specifically: S3 specific steps also include:

[0149] S34: the three-phase current unbalance coefficient obtained based on S31, S32 and S33 , the three-phase voltage unbalance coefficient , the voltage drop value , the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq are associated, and after dimensionless processing, the comprehensive stability score Wpz of the current charging pile in the corresponding period is obtained by fitting, which is specifically obtained by the following formula:

[0150] ;

[0151] In the formula, , 2. 3. 4 and 5 represent the three-phase current unbalance coefficient , three-phase voltage unbalance coefficient , voltage drop value , the weight value of total harmonic distortion rate Zxb and total electromagnetic interference field strength Cq, where 0< <1,0< <1,0< <1,0< <1,0< <1, the specific value is set by the user according to the situation;

[0152] S35, pre-set the safety threshold Q, and compare and analyze the comprehensive stability score Wpz of the current charging pile in the corresponding period with the safety threshold Q to comprehensively judge the stability performance of the current charging pile during operation. The specific judgment content is as follows:

[0153] If the comprehensive stability score Wpz exceeds the safety threshold Q, it is judged that the current charging pile is in an unstable state during operation. At this time, the optimization instruction will be triggered to start the optimization mechanism;

[0154] If the comprehensive stability score Wpz does not exceed the safety threshold Q, it is judged that the current charging pile is in a stable state during operation, and the monitoring operation will continue.

[0155] The setting method of the safety threshold Q is as follows: According to the method of obtaining the comprehensive stability score Wpz in S34, the comprehensive stability scores Wpz in different time periods are obtained in sequence, and the average comprehensive stability score Wpz is obtained through statistics. and the standard deviation of the comprehensive stability score , based on the average overall stability score and the standard deviation of the comprehensive stability score , set the safety threshold Among them, Y is a constant, usually with a value of 1-3, corresponding to different confidence levels, and the specific value is set by the user (based on actual conditions).

[0156] In this embodiment, the method constructs an accurate and efficient stability evaluation model by comprehensively analyzing a variety of important indicators that affect the stability of the charging pile, and quantifies it into a comprehensive stability score Wpz. By introducing multi-dimensional indicators such as three-phase current imbalance coefficient, three-phase voltage imbalance coefficient, voltage drop value, total harmonic distortion rate and total electromagnetic interference field strength, the system can evaluate the power supply quality problems, abnormal equipment status and external interference that may be faced during the operation of the charging pile in multiple dimensions. In order to ensure the comparability of data and the robustness of the calculation model, the present invention standardizes each indicator through dimensionless processing technology. By setting the safety threshold Q, the method can dynamically judge the operating status of the charging pile according to the comprehensive stability score Wpz. This mechanism realizes real-time monitoring, dynamic judgment and optimized response to the operating stability of the charging pile.

[0157] Example 6

[0158] Please refer to Figure 1, specifically: S4 specific steps include:

[0159] S41, after receiving the optimization instruction sent from S35, start the optimization mechanism, the specific steps of starting the optimization mechanism are as follows:

[0160] S411. Using historical data, determine the time period during which the user charges via the charging pile in the historical period, record it as the working period, and analyze and calculate the minimum fee to be paid during the working period in combination with the regional time-of-use electricity price mechanism. , which can be obtained by:

[0161] ;

[0162] ;

[0163] In the formula, Indicates the fees required to apply for the unified electricity price model. Indicates the fees to be paid when applying for the time-of-use electricity price model. represents the average charging power, Indicates the total charging time. represents a fixed electricity price, represents the charging power of the fth charging period, represents the duration of the fth charging period, represents the electricity price of the fth charging period, and F represents the number of charging periods that the user crosses when charging when applying for the time-of-use electricity price mode; f=1, 2, 3, ..., F;

[0164] S412. Fees to be paid when applying for the unified electricity price model Fees required to apply for time-of-use electricity price model Compare the size to find the minimum fee and mark the minimum fee .

[0165] The total charging time mentioned above The duration t of the corresponding charging period can be monitored and obtained by a timer;

[0166] Average charging power And the charging power of the corresponding charging period It can be monitored and obtained through a power meter or smart meter;

[0167] The specific steps of S4 also include:

[0168] S42. The minimum fee obtained in S41 , initially recommends users to apply for the minimum fee The corresponding electricity price model is used to complete the No. 1 optimization mechanism. Combined with the comprehensive stability score Wpz in the historical period, based on the No. 1 optimization mechanism, the user is recommended a time period for charging, and the vehicle to be charged is reminded through SMS reminders to complete the No. 2 optimization mechanism.

[0169] The above historical data is used to determine the time period when the user charges through the charging pile during the historical period;

[0170] The comprehensive stability score Wpz in the historical period can be calculated and obtained according to step S34, which serves as the basis for later recommendations on charging time periods for users;

[0171] Among them, the electricity price model includes the unified electricity price model and the time-of-use electricity price model;

[0172] Among them, the optimization mechanism includes optimization mechanism No. 1 and optimization mechanism No. 2.

[0173] In this embodiment, the method effectively reduces the user's charging costs by constructing an optimization mechanism for the user's charging costs, while improving the efficiency of the charging pile and the user experience. After receiving the optimization instruction from the comprehensive stability score Wpz, the system uses the user's historical charging data and combines the regional time-of-use electricity price mechanism to intelligently analyze and calculate the user's charging costs during the working hours. By calculating the charging costs under the unified electricity price mode and the time-of-use electricity price mode respectively, the system can quickly and accurately compare the costs of the two modes, mark the minimum cost, and provide a clear cost reference for the user. In the first stage of the optimization mechanism, the system preliminarily recommends the user to select the electricity price mode corresponding to the minimum cost based on the calculation results, ensuring that the user can complete the charging operation at a relatively low cost. In the second stage, the system further combines the comprehensive stability score Wpz in the historical period to recommend a relatively good charging time period, thereby helping users avoid unstable power supply or peak hours and improve charging efficiency and safety as much as possible. In addition, the user is notified of the charging plan of the vehicle to be charged by SMS reminder, which enhances the convenience and intelligence of the user experience. Overall, through the joint implementation of the No. 1 and No. 2 optimization mechanisms, this method achieves a comprehensive balance between economy and stability, providing users with an intelligent and personalized charging service experience, while also providing strong support for the load management of the power grid and the improvement of the operating efficiency of charging piles.

[0174] Example 7

[0175] Please refer to Figure 2 ,Specifically: A charging pile control system based on fingerprint recognition, including an authentication module, a data acquisition module, a stability performance analysis module and an optimization control module;

[0176] The authentication module is used to collect the fingerprint image of the user to be authenticated by using the ultrasonic fingerprint sensor, and match the fingerprint image of the user to be authenticated with the registration data in the database to obtain the matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P;

[0177] The data acquisition module is used to start the charging mechanism when the authentication pass signal is generated, and to monitor the quality status, operation status and external environmental interference situation of the power supply network in real time during the operation of the charging pile, so as to obtain relevant power supply quality data, relevant operation data and relevant interference data, and generate a monitoring data set after data preprocessing;

[0178] The stability performance analysis module is used to analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz;

[0179] The optimization control module is used to utilize historical data and combine the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, a charging reminder is regularly issued to the user to enter the charging mode.

[0180] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A charging pile control method based on fingerprint recognition, characterized in that: The following steps are included: S1. Use an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified, and match the fingerprint image of the user to be verified with the registration data in the database to obtain a matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P; The specific steps of S1 include: S11, using an ultrasonic fingerprint sensor to collect the fingerprint image of the user to be verified in advance, and performing image region segmentation on the fingerprint image of the user to be verified to identify and extract several groups of feature values, and generate a fingerprint feature vector of the user to be verified after statistics. The registration data in the database includes the fingerprint feature vector of the authorized user ; Among them, the fingerprint feature vector of the user to be verified is It includes the feature value at each feature point and the feature value of each image area; S12, by the fingerprint feature vector of the user to be verified Match with the registration data in the database to obtain the matching degree Ppd, which is obtained by the following formula: ； In the formula, It is represented as the matching degree corresponding to the jth user to be verified, n is represented as the dimension of the feature vector, i=1, 2, 3, ..., n, Represented as the i-th eigenvalue in the fingerprint feature vector of the user to be verified, Represented as the i-th eigenvalue in the authorized user’s fingerprint feature vector, Expressed as and The dot product of It is represented as the modulus of the fingerprint feature vector of the user to be verified. It is represented as the modulus of the fingerprint feature vector of the authorized user; The specific steps of S1 also include: S13, presetting a matching threshold P, the steps for setting the matching threshold P are as follows: S131. Collecting fingerprint feature vectors of several groups of authorized users in advance , by performing fingerprint recognition on each authorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as matching degrees No. , according to the matching degree of No. , construct the matching probability density function of authorized users ; S132: Collect fingerprint feature vectors of several groups of unauthorized users in advance , by performing fingerprint recognition on each unauthorized user to calculate the corresponding matching degree Ppd, and after statistics, obtain several groups of matching degrees Ppd and mark them as the second matching degree , according to the matching degree of No. , construct the matching probability density function of unauthorized users ; S133, matching probability density function based on unauthorized users And the matching probability density function of authorized users , draw the ROC curve, based on the ROC curve, analyze the relationship between the true positive rate and the false positive rate under different thresholds x, and extract the matching threshold P from it. The specific expression is as follows: ； In the formula, represents the objective function; It means finding the x value that maximizes the objective function value. Indicates the matching degree of authorized users under threshold x The probability of threshold x; represents the probability that the matching degree of unauthorized users is less than the threshold value x under the threshold value x; ; S14, by comparing and analyzing the extracted matching threshold value P with the matching degree Ppd, to determine whether the current user to be verified is an authorized user, the specific determination content is as follows: If the matching degree Ppd exceeds the matching threshold P, it means that the user to be verified is an authorized user, and an authentication pass signal will be generated; If the matching degree Ppd does not exceed the matching threshold P, it means that the user to be verified is not an authorized user, and an authentication failure signal will be generated; S2. When the authentication pass signal is generated, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference situation of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, and after data preprocessing, a monitoring data set is generated; S3. Analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz; S4. Use historical data and combine it with the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, regularly send charging reminders to users to enter the charging mode.

2. According to a charging pile control method based on fingerprint recognition according to claim 1, it is characterized in that: The specific steps of S2 include: S21. After receiving the authentication signal sent in S14, the charging mechanism is started, and during the operation of the charging pile, the quality status, operation status and external environmental interference status of the power supply network are monitored in real time to obtain relevant power supply quality data, relevant operation data and relevant interference data, wherein the relevant power supply quality data includes the actual value of the R phase current in the three-phase AC circuit at the input end of the charging pile. , Actual value of S phase current , Actual value of T phase current , R phase relative to the neutral point voltage value , S phase relative to neutral point voltage value And the voltage value of phase T relative to the neutral point ; The relevant operating data includes line impedance And the equivalent current of the three-phase total current ; The relevant interference data includes the effective value of the fundamental current , the effective value of the corresponding harmonic current, the transmission power of the interference source , Antenna gain and the distance between the charging pile and the adjacent charging piles ; S22, fill missing values, remove abnormal values, delete duplicate values ​​and remove noise for the relevant power supply quality data, relevant operation data and relevant interference data obtained in S21, and use dimensionless processing technology to standardize the pre-processed data to generate a monitoring data set; S23. After receiving the authentication failure signal sent in S14, the charging pile continues to remain in the standby state and stores the authentication failure in the monitoring data set.

3. A charging pile control method based on fingerprint recognition according to claim 2, characterized in that: The specific steps of S3 include: S31. Analyze the distribution of three-phase current and three-phase voltage between the power supply interface from the power distribution network to the charging pile according to the relevant power supply quality data in the monitoring data set to obtain the three-phase current unbalance coefficient. And three-phase voltage unbalance coefficient , the three-phase current unbalance coefficient And the three-phase voltage unbalance coefficient The specific formula is as follows: ； In the formula, , and They represent the actual current values ​​of the R phase, S phase and T phase in the three-phase AC circuit respectively. Expressed as the average value of three-phase current; ； In the formula, , and It is expressed as the voltage value of each phase relative to the neutral point; Expressed as the average value of three-phase voltage.

4. The charging pile control method based on fingerprint recognition according to claim 3 is characterized in that: The specific steps of S3 also include: S32. Analyze the impact of energy loss of the power transmission system on the charging pile according to the relevant operating data in the monitoring data set to obtain the voltage drop value , the voltage drop value Obtained by the following formula: ； In the formula, represents the line impedance, Indicates the equivalent current of the three-phase total current; S33. At the same time, according to the relevant interference data in the monitoring data set, the harmonic superposition status generated by the charging pile during operation and the communication interference caused by the electromagnetic radiation superposition of the adjacent charging piles around the charging pile are analyzed to obtain the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq. The total harmonic distortion rate Zxb is obtained by the following formula: ； In the formula, Expressed as the effective value of the mth harmonic current, It is expressed as the effective value of the fundamental current, and m is the harmonic number; It represents the distortion rate of all higher harmonics starting from the second harmonic, and M represents the cutoff frequency; The total electromagnetic interference field strength Cq is obtained by the following formula: ； In the formula, Expressed as the transmission power of the interference source, Expressed as antenna gain, Expressed as the distance between the charging pile and the adjacent charging pile; Represents the field strength generated by the corresponding charging pile, k=1, 2, 3, ..., K, K represents the number of adjacent charging piles.

5. The charging pile control method based on fingerprint recognition according to claim 4 is characterized in that: The specific steps of S3 also include: S34: the three-phase current unbalance coefficient obtained based on S31, S32 and S33 , the three-phase voltage unbalance coefficient , the voltage drop value , the total harmonic distortion rate Zxb and the total electromagnetic interference field strength Cq are associated, and after dimensionless processing, the comprehensive stability score Wpz of the current charging pile in the corresponding period is obtained by fitting, which is specifically obtained by the following formula: ； In the formula, , 2.

3. 4 and 5 represent the three-phase current unbalance coefficient , three-phase voltage unbalance coefficient , voltage drop value , the weight values ​​of total harmonic distortion rate Zxb and total electromagnetic interference field strength Cq, the specific values ​​are set by the user according to the situation; S35, pre-set the safety threshold Q, and compare and analyze the comprehensive stability score Wpz of the current charging pile in the corresponding period with the safety threshold Q to comprehensively judge the stability performance of the current charging pile during operation. The specific judgment content is as follows: If the comprehensive stability score Wpz exceeds the safety threshold Q, it is judged that the current charging pile is in an unstable state during operation. At this time, the optimization instruction will be triggered to start the optimization mechanism; If the comprehensive stability score Wpz does not exceed the safety threshold Q, it is judged that the current charging pile is in a stable state during operation, and the monitoring operation will continue.

6. The charging pile control method based on fingerprint recognition according to claim 5 is characterized in that: The specific steps of S4 include: S41, after receiving the optimization instruction sent from S35, start the optimization mechanism, the specific steps of starting the optimization mechanism are as follows: S411. Using historical data, determine the time period during which the user charges via the charging pile in the historical period, record it as the working period, and analyze and calculate the minimum fee to be paid during the working period in combination with the regional time-of-use electricity price mechanism. , which can be obtained by: ； ； In the formula, Indicates the fees required to apply for the unified electricity price model. Indicates the fees to be paid when applying for the time-of-use electricity price model. represents the average charging power, Indicates the total charging time. represents a fixed electricity price, represents the charging power of the fth charging period, represents the duration of the fth charging period, represents the electricity price of the fth charging period, and F represents the number of charging periods that the user crosses when charging when applying for the time-of-use electricity price mode; f=1, 2, 3, ..., F; S412. Fees to be paid when applying for the unified electricity price model Fees required to apply for time-of-use electricity price model Compare the size to find the minimum fee and mark the minimum fee .

7. A charging pile control method based on fingerprint recognition according to claim 6, characterized in that: The specific steps of S4 also include: S42. The minimum fee obtained in S41 , initially recommends users to apply for the minimum fee The corresponding electricity price model is used to complete the No. 1 optimization mechanism. Combined with the comprehensive stability score Wpz in the historical period, based on the No. 1 optimization mechanism, the user is recommended a time period for charging, and the vehicle to be charged is reminded through SMS reminders to complete the No. 2 optimization mechanism. Among them, the electricity price model includes the unified electricity price model and the time-of-use electricity price model; Among them, the optimization mechanism includes optimization mechanism No. 1 and optimization mechanism No.

2.

8. A charging pile control system based on fingerprint recognition, used to implement a charging pile control method based on fingerprint recognition as described in any one of claims 1 to 7, characterized in that: It includes authentication module, data acquisition module, stability performance analysis module and optimization control module; The authentication module is used to collect the fingerprint image of the user to be authenticated by using the ultrasonic fingerprint sensor, and match the fingerprint image of the user to be authenticated with the registration data in the database to obtain the matching degree Ppd, and generate a corresponding authentication signal in combination with a preset matching threshold P; The data acquisition module is used to start the charging mechanism when the authentication pass signal is generated, and to monitor the quality status, operation status and external environmental interference situation of the power supply network in real time during the operation of the charging pile, so as to obtain relevant power supply quality data, relevant operation data and relevant interference data, and generate a monitoring data set after data preprocessing; The stability performance analysis module is used to analyze the stability of the charging pile during operation based on the monitoring data set to construct a comprehensive stability score Wpz, and optimize the user's charging plan according to the value of the comprehensive stability score Wpz; The optimization control module is used to utilize historical data and combine the regional time-of-use electricity price mechanism to match the electricity consumption plan. When the matched electricity consumption plan adopts the time-of-use electricity price mechanism, combined with the comprehensive stability score Wpz, a charging reminder is regularly issued to the user to enter the charging mode.

Images