A charging pile software automatic online upgrade method and system

Abstract

The present invention relates to the field of network communication technology, and in particular to a method and system for automatic online upgrade of charging pile software. The method comprises the following steps: obtaining charging pile usage history data; performing upgrade period planning on the charging pile usage history data, thereby obtaining upgrade period data; performing network periodic monitoring on the charging pile through a charging pile monitoring tool according to the upgrade period data, thereby obtaining charging pile network status data; performing network stability index calculation on the charging pile network status data, thereby obtaining the network stability index; when the network stability index is greater than or equal to a preset minimum network stability index, executing step S4. The present invention analyzes the user's charging pile usage off-peak period to perform upgrade time planning, accurately analyzes network stability, can perform upgrade judgment based on network stability, incrementally upgrade new software version data, reduce data transmission, and improve data transmission efficiency and stability.

Description

Technical Field

[0001] The present invention relates to the field of network communication technology, and in particular to a method and system for automatically upgrading charging pile software online. Background Art

[0002] In the early days, software upgrades for devices usually required manual intervention by users, and the new version of the software might need to be installed on the device through physical media, such as a disc or USB drive. This method is cumbersome and prone to errors. With the development of cloud computing and IoT technologies, the concept of automatic online upgrades has been gradually introduced. The device is able to automatically detect new versions of the software and upgrade without user intervention. This stage improves the convenience and efficiency of the upgrade. However, the existing automatic online upgrade method for charging pile software does not accurately analyze the stability of the network and does not fully consider the user experience. The upgrade causes the interruption of the user's charging service, has poor ability to cope with network fluctuations, and cannot adjust the automatic upgrade process according to data transmission fluctuations; the efficiency of transmission upgrade resources is low, resulting in slow transmission speed and unstable transmission. Summary of the invention

[0003] Based on this, it is necessary to provide a method and system for automatic online upgrading of charging pile software to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for automatically upgrading charging pile software online comprises the following steps:

[0005] Step S1: Obtaining charging pile usage history data; performing upgrade period planning on the charging pile usage history data, thereby obtaining upgrade period data;

[0006] Step S2: Perform network periodic monitoring of the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data;

[0007] Step S3: Calculate the network stability index of the charging pile network status data to obtain the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, execute step S4; when the network stability index is less than the preset minimum network stability index, return to execute step S2;

[0008] Step S4: Obtain charging pile software version data; perform a secure backup of the charging pile software version data, thereby obtaining secure backup data; obtain server software version data; perform version difference encoding and incremental extraction of the server software version data and the charging pile software version data, thereby obtaining version incremental encoding data;

[0009] Step S5: When the version increment coded data is less than or equal to the preset guaranteed version increment threshold, the version increment coded data is incrementally verified and transmitted to the charging pile; when the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version coded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile;

[0010] Step S6: The charging pile decodes the version increment coded data or the complete version coded data and performs version merging to obtain version upgrade data; performs software version upgrade according to the version upgrade data and performs upgrade monitoring and rollback operations to realize automatic online upgrade of the charging pile software.

[0011] By collecting the historical data of charging pile usage, the present invention can deeply understand the user's charging behavior pattern, the usage during peak and trough periods, and provide basic data for subsequent upgrade period planning. By calculating the network stability index, the network connection quality of the charging pile can be quantitatively evaluated; when the network stability index reaches or exceeds the preset minimum stability index, it is ensured that the subsequent upgrade operation is carried out in a stable network environment to reduce the upgrade risk. The software version data of the current charging pile and the server is obtained to provide a basis for subsequent upgrade operations; the security backup ensures that the previous software version can be rolled back during the upgrade process, thereby improving the reliability and stability of the system. The security and accuracy of data transmission are improved, and only legal and complete incremental data are transmitted to the charging pile through verification; when the version incremental encoding data is less than or equal to the preset threshold, incremental transmission is adopted to reduce the transmission volume, reduce the network burden, and improve the transmission efficiency. The charging pile decodes and obtains incremental data or complete version data to ensure the availability of the data; the incremental data is merged with the current version, or the complete version data is applied to realize the upgrade of the software version. Through the incremental upgrade method, the transmission time and bandwidth required for the upgrade are reduced. The online upgrade of the charging pile software is realized to ensure that the charging pile system always runs on the latest software version; real-time monitoring is performed during the upgrade process, and once an abnormality occurs, it can be quickly rolled back to the previous version to ensure the continuity and stability of the charging service. Therefore, the present invention provides a method and system for automatic online upgrade of charging pile software, which analyzes the user's charging pile usage off-peak period to plan the upgrade time, accurately analyzes the network stability, can make upgrade judgments based on the network stability, and incrementally upgrade the new software version data, reduce data transmission, and improve the efficiency and stability of data transmission.

[0012] Preferably, step S1 comprises the following steps:

[0013] Step S11: Obtain charging pile usage history data and charging pile geographic location data through a charging pile monitoring system;

[0014] Step S12: performing regional division according to the geographical location data of the charging piles, thereby obtaining regional data of the charging piles;

[0015] Step S13: performing charging pile information matching on the charging pile area data and the charging pile usage history data, thereby obtaining charging pile information matching data;

[0016] Step S14: performing off-peak period analysis on the charging pile usage history data corresponding to each area in the charging pile area data according to the charging pile information matching data, thereby obtaining off-peak period data on the regional charging pile usage;

[0017] Step S15: Setting an upgrade time window according to off-peak data of regional charging piles, thereby obtaining upgrade time period data.

[0018] The present invention obtains the usage history data of the charging pile through the monitoring system, and can deeply understand the usage frequency, peak period and off-peak period of the charging pile, providing a basis for formulating the upgrade period plan; obtaining the geographical location data of the charging pile is helpful for subsequent regional division and analysis. The charging piles can be reasonably divided according to the geographical location data, and the charging piles can be divided into different areas, which is convenient for subsequent regional analysis and optimization; according to the divided areas, the relevant data of the charging piles in each area are sorted and obtained. The regional data and the usage history data are matched to ensure the consistency and accuracy of the data, providing a reliable basis for subsequent analysis; the charging pile information matching data is obtained, including the usage history information of the charging piles in each area. According to the information matching data, the charging pile usage history data in each area is analyzed during the off-peak period to find the off-peak period of charging demand in each area; the off-peak period of each area is determined to avoid a large impact on the charging pile service when formulating the upgrade time period. Based on the regional off-peak period data, a suitable upgrade time window is set to ensure that the upgrade operation is carried out as much as possible during the off-peak period of charging demand to reduce the impact on users; and the optimized upgrade time period data is obtained to ensure that the impact of the upgrade operation on users is minimized.

[0019] Preferably, in step S3, the network stability index is calculated, wherein the network stability index calculation formula is specifically:

[0020]

[0021] In the formula, N represents the network stability index, n represents an integer approaching infinity, x represents the network bandwidth value, y represents the network delay value, z represents the data packet loss rate, and f(x, y, z) represents the network status function. represents the partial derivative of f(x,y,z) with respect to x, and r represents the maximum distance of the network connection.

[0022] The present invention constructs a network stability index calculation formula for calculating the network stability index of the charging pile network status data; in the formula Some of the complex combinations of network bandwidth, delay and data packet loss rate are introduced, and logarithmic operations are introduced to help comprehensively consider the impact of these network parameters on stability; the network bandwidth, delay and data packet loss rate are integrated, and the impact on network instability is amplified through logarithmic operations to better capture the comprehensive characteristics of the network state; among them, limit operations are constructed to enable the network stability index to tend to stability when it approaches infinity; through limit operations, it is ensured that the network stability index tends to stability when the data volume is large enough, making the calculation results more reliable and universal. The "partial derivative" of the network state function with respect to bandwidth, that is, the sensitivity of the network state to bandwidth changes, is quantified by calculating the partial derivative of bandwidth, making the network stability index more targeted and sensitive. The network state function comprehensively considers the impact of bandwidth, delay and packet loss rate. The network state function is formed by comprehensive processing of bandwidth, delay and packet loss rate, which more comprehensively reflects the actual stability of the network. The inverse sine function is partially introduced, and the relationship between bandwidth and delay is normalized by the maximum distance of the network connection; the network bandwidth and delay are associated with the maximum distance of the network connection and processed by the inverse sine function, so that the network stability index has adaptability to the network connection distance and is more in line with the actual network environment.

[0023] Preferably, step S4 comprises the following steps:

[0024] Step S41: obtaining charging pile software version data; using a hash function to generate a version data summary of the charging pile software version data, thereby obtaining a version data summary; performing version backup encryption on the charging pile software version data, thereby obtaining version backup encrypted data;

[0025] Step S42: performing version data integration on the version data summary and the version backup encrypted data, thereby obtaining secure backup data; obtaining server software version data; performing format standardization processing on the charging pile software version data and the server software version data, thereby obtaining version format standard data;

[0026] Step S43: extracting version key features from the version format standard data, thereby obtaining version key feature data, wherein the version key feature data includes file-level feature data and version-level feature data;

[0027] Step S44: performing similarity analysis according to the version key feature data, thereby obtaining similarity analysis data; dividing the version format standard data into difference blocks according to the version key feature data and the similarity analysis data, thereby obtaining difference block data;

[0028] Step S45: variable-length encoding is performed on the difference block data and incremental extraction is performed to obtain incremental encoded data; incremental optimization encoding is performed on the incremental encoded data to obtain version incremental encoded data.

[0029] The present invention provides a basis for subsequent secure backup and version comparison by acquiring the software version data of the charging pile; uses a hash function to generate a unique version data summary for the software version data for subsequent version integrity verification; encrypts the software version data through an encryption algorithm to protect the security of the backup data. The version data summary and the version backup encryption data are integrated into secure backup data to ensure the integrity and confidentiality of the backup; the software version data of the server is acquired for subsequent version comparison; the formats of the software version data of the charging pile and the server are unified to facilitate subsequent version comparison and difference analysis. Key features are extracted from the version data, including file-level feature data and version-level feature data, for subsequent similarity analysis and difference analysis. By comparing the key features of the versions, similarity analysis is performed to identify the similarity between the software versions of the charging pile and the server; according to the similarity analysis results, the version data is divided into difference blocks to prepare for incremental encoding; variable-length encoding is performed on the difference block data to reduce the amount of transmitted data, and incremental extraction is performed at the same time to obtain incremental encoded data; the incremental encoded data is optimized to further reduce the size of the transmitted data and improve the transmission efficiency.

[0030] Preferably, step S43 includes the following steps:

[0031] Step S431: performing version data structure analysis on the version format standard data, thereby obtaining the version data structure;

[0032] Step S432: extracting file-level features from the version format standard data according to the version data structure, thereby obtaining file-level feature data;

[0033] Step S433: extracting version-level features from the version format standard data according to the version data structure, thereby obtaining version-level feature data;

[0034] The file-level feature extraction in step S432 includes the following steps:

[0035] Step S4321: extracting a file list from the version format standard data, thereby obtaining file list data; performing file binary conversion on the version format standard data, thereby obtaining file binary data;

[0036] Step S4322: Utilize the MD5 hash function, the file list data, and the file binary data to perform file hash calculation on the version format standard data and perform file content comparison, thereby obtaining version file content change data;

[0037] Step S4323: Compare the file size and type of the version format standard data, thereby obtaining file size and type change data;

[0038] Step S4324: performing file meta information comparison on the version format standard data, thereby obtaining file meta information change data;

[0039] The version-level feature extraction in step S433 includes the following steps:

[0040] Step S4331: performing version number change identification on the version format standard data, thereby obtaining version number change data;

[0041] Step S4332: Analyze the overall file size and quantity changes of the version format standard data, thereby obtaining overall file size and quantity change data;

[0042] Step S4333: Analyze the version release time of the version format standard data to obtain the version release time data.

[0043] The present invention obtains the data structure of the software version by structural analysis of the version format standard data, which provides a basis for subsequent feature extraction and difference analysis. Detailed file-level feature extraction is performed on the software version data to more accurately analyze the differences between versions; wherein, the file-level feature extraction can obtain a list of all files contained in the software version, which provides a basis for subsequent file-level feature extraction; the hash value of the file is calculated using the MD5 hash function to quickly detect changes in the file content; the differences in the file content between versions are compared to obtain detailed data on the changes in the file content, and the specific changes in the file content are identified, rather than just the existence or non-existence of the file; the size and type changes of the files between versions are compared to extract the data on the changes in the file size and type; the meta information of the files between versions is compared to extract the change data of the file meta information. Version-level feature extraction is performed on the software version data to analyze the differences between versions from an overall level, wherein the version-level feature extraction can identify and extract the change data of the version number between versions; the changes in the overall file size and quantity are analyzed to extract the data on the changes in the overall file size and quantity; the changes in the version release time are analyzed to extract the data on the version release time.

[0044] Preferably, step S5 comprises the following steps:

[0045] Step S51: when the version increment encoded data is less than or equal to the preset guaranteed version increment threshold, extract verification data from the version increment encoded data to obtain data to be verified;

[0046] Step S52: performing a version increment legality check on the version increment encoded data, thereby obtaining version increment legality data;

[0047] Step S53: setting the applicability threshold and calculating the version applicability index according to the charging pile software version data and the version increment coding data, thereby obtaining the applicability threshold and the version applicability index;

[0048] Step S54: Performing a suitability judgment on the version suitability index and the suitability threshold. When the version suitability index is greater than or equal to the suitability threshold, version suitability data is generated and step S55 is executed; when the version suitability index is less than the suitability threshold, the version increment encoded data transmission fails and step S56 is executed;

[0049] Step S55: Generate an incremental verification report for the data to be verified according to the version increment legitimacy data and the version applicability data, thereby obtaining an incremental verification report; transmit the incremental verification report and the version increment encoding data to the charging pile, and execute step S6;

[0050] Step S56: When the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version encoded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile.

[0051] The present invention extracts the data to be verified from the version increment coded data to prepare for subsequent legitimacy verification and applicability judgment. Through legitimacy verification, it is ensured that the extracted version increment data is complete and not tampered with; the legal source of the version increment data is verified by using the digital signature technology to enhance the credibility of the data. According to the current software version and the version increment coded data of the charging pile, the applicability threshold is set to determine whether the version is applicable; by considering multiple factors of version applicability, the version applicability index is calculated to quantitatively evaluate the version applicability. It is determined whether the version applicability index reaches the set applicability threshold to decide whether to continue the incremental verification; and decision support information is provided. If the version applicability index is high enough, the incremental verification can be continued, otherwise the complete version coding transmission is performed. A detailed incremental verification report is generated, including the verification result and the verification timestamp information; and decision support information is provided. If the verification passes, the generated incremental verification report and the version increment coded data are transmitted to the charging pile. The server and the charging pile software version data are fully version-encoded to back up the entire software version for transmission to the charging pile; the fault-tolerant mechanism when the version increment coded data is greater than the threshold or the transmission fails ensures that the charging pile can obtain the complete version data.

[0052] Preferably, step S53 includes the following steps:

[0053] Step S531: extracting the applicability data to be compared from the version increment coded data, thereby obtaining the applicability data to be compared; generating a version difference report for the applicability data to be compared using the charging pile software version data, thereby obtaining the version difference report;

[0054] Step S532: Perform version change complexity analysis on the version difference report to obtain version change complexity data; perform user experience evaluation based on the version difference report to obtain user experience evaluation data; perform compatibility requirement analysis on the charging pile system to obtain compatibility requirement data; obtain historical verification data, and extract historical threshold adjustment coefficients based on the historical verification data to obtain historical threshold adjustment coefficients;

[0055] Step S533: performing applicability threshold weight allocation on the version change complexity data, the user experience evaluation data, the compatibility requirement data, and the historical threshold adjustment coefficient, thereby obtaining applicability threshold weight data;

[0056] Step S534: setting the applicability threshold according to the applicability threshold weight data, thereby obtaining the applicability threshold;

[0057] Step S535: Calculate the version applicability index based on the version difference report to obtain the version applicability index.

[0058] The present invention extracts the applicability data to be compared with the charging pile software version from the version increment encoding data, and prepares to generate a version difference report. The version difference report is analyzed to evaluate the complexity of the version change, including the new functions and the defects repaired; the version change complexity data is obtained for the subsequent applicability threshold weight allocation. By analyzing the version difference report, the impact of the new version on the user experience is evaluated, including the interface changes and the interaction mode; the user experience evaluation data is obtained for the subsequent applicability threshold weight allocation. The compatibility requirements of the charging pile system, including the compatibility of hardware and software, are analyzed to understand the compatibility impact of the new version on the existing system. Historical verification data is collected, including the applicability verification results of previous versions; based on the historical verification data, the historical threshold adjustment coefficient is extracted for adjusting the applicability threshold according to historical experience. Based on various data, the weight of the applicability threshold is assigned to determine the relative importance of each factor in the applicability judgment. Combined with the applicability threshold weight data, the applicability threshold is set to determine whether the new version is applicable to the current charging pile software. Based on the version difference report, the applicability threshold and the weight data, the version applicability index is calculated to provide a quantitative indicator for subsequent judgment. The higher the applicability index, the more applicable the new version is to the current system.

[0059] Preferably, in step S535, the version applicability index is calculated, wherein the version applicability index calculation formula is specifically:

[0060]

[0061] Where A represents the applicability of the incremental version to the current version, a represents the change complexity of the incremental version relative to the current version, β represents the compatibility score of the incremental version relative to the current version, m represents the auxiliary variable in the limit operation, ΔV represents the total change between the current version and the incremental version, ΔT represents the time interval between the current version and the incremental version, γ represents the emphasis on stability in version applicability, δ represents the change angle direction of the incremental version relative to the current version, f represents the change frequency within the time interval between the current version and the incremental version, ∈ represents the functional change factor, Indicates the performance impact factor.

[0062] The present invention constructs a version applicability index calculation formula for calculating the version applicability index based on the version difference report; the ln(a+β) part of the formula performs logarithmic operations on the change complexity a of the incremental version and the compatibility score β, which helps to take the two into comprehensive consideration, making the version applicability index more comprehensive and interpretable. The part calculates the ratio of the total change amount and time interval between the current version and the incremental version to consider the relative change rate between versions; it helps to more accurately reflect the change frequency between versions. Part of it is used to adjust the applicability index to make it more sensitive to the direction and stability of version changes. The part represents the partial derivative of the change frequency with respect to the auxiliary variable m, which is used to consider the sensitivity of the version applicability to the change frequency; it helps to better reflect the impact of the version change frequency on the applicability. Partially considers the combined impact of functional changes and performance impact on version applicability; helps balance the impact of functionality and performance.

[0063] Preferably, the present invention further provides a charging pile software automatic online upgrade system, which is used to execute the charging pile software automatic online upgrade method as described above, comprising:

[0064] The charging pile upgrade time planning module is used to obtain the charging pile usage history data; perform upgrade time period planning on the charging pile usage history data, thereby obtaining the upgrade time period data;

[0065] The network cycle monitoring module is used to perform network cycle monitoring on the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data;

[0066] A network stability judgment module is used to calculate the network stability index of the charging pile network status data, thereby obtaining the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, step S4 is executed; when the network stability index is less than the preset minimum network stability index, the execution returns to step S2;

[0067] Software version incremental extraction is used to obtain charging pile software version data; perform secure backup of the charging pile software version data, thereby obtaining secure backup data; obtain server-side software version data; perform version difference encoding and incremental extraction of the server-side software version data and the charging pile software version data, thereby obtaining version incremental encoding data;

[0068] The incremental coding data transmission judgment module is used to perform incremental verification on the incremental version coding data and transmit it to the charging pile when the incremental version coding data is less than or equal to the preset guaranteed version increment threshold; when the incremental version coding data is greater than the preset guaranteed version increment threshold or the incremental version coding data transmission fails, perform complete version coding on the server software version data and the charging pile software version data, thereby obtaining the complete version coding data, and transmit the complete version coding data to the charging pile;

[0069] The software version upgrade monitoring module is used for the charging pile to decode the version incremental encoding data or the complete version encoding data and merge the versions to obtain the version upgrade data; according to the version upgrade data, the software version is upgraded and the upgrade monitoring rollback operation is performed to realize the automatic online upgrade of the charging pile software.

[0070] By collecting the historical data of charging pile usage, the present invention can deeply understand the user's charging behavior pattern, the usage during peak and trough periods, and provide basic data for subsequent upgrade period planning. By calculating the network stability index, the network connection quality of the charging pile can be quantitatively evaluated; when the network stability index reaches or exceeds the preset minimum stability index, it is ensured that the subsequent upgrade operation is carried out in a stable network environment to reduce the upgrade risk. The software version data of the current charging pile and the server is obtained to provide a basis for subsequent upgrade operations; the security backup ensures that the previous software version can be rolled back during the upgrade process, thereby improving the reliability and stability of the system. The security and accuracy of data transmission are improved, and only legal and complete incremental data are transmitted to the charging pile through verification; when the version incremental encoding data is less than or equal to the preset threshold, incremental transmission is adopted to reduce the transmission volume, reduce the network burden, and improve the transmission efficiency. The charging pile decodes and obtains incremental data or complete version data to ensure the availability of the data; the incremental data is merged with the current version, or the complete version data is applied to realize the upgrade of the software version. Through the incremental upgrade method, the transmission time and bandwidth required for the upgrade are reduced. The online upgrade of the charging pile software is realized to ensure that the charging pile system always runs on the latest software version; real-time monitoring is performed during the upgrade process, and once an abnormality occurs, it can be quickly rolled back to the previous version to ensure the continuity and stability of the charging service. Therefore, the present invention provides a method and system for automatic online upgrade of charging pile software, which analyzes the user's charging pile usage off-peak period to plan the upgrade time, accurately analyzes the network stability, can make upgrade judgments based on the network stability, and incrementally upgrade the new software version data, reduce data transmission, and improve the efficiency and stability of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A schematic diagram of the steps of a method for automatically upgrading charging pile software online;

[0072] Figure 2 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0073] Figure 3 for Figure 1 Detailed implementation steps of step S5;

[0074] Figure 4 for Figure 3Detailed implementation steps of step S53;

[0075] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0076] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0077] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0078] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0079] To achieve this, please refer to Figures 1 to 4 The present invention provides a method for automatically upgrading charging pile software online, comprising the following steps:

[0080] Step S1: Obtaining charging pile usage history data; performing upgrade period planning on the charging pile usage history data, thereby obtaining upgrade period data;

[0081] Step S2: Perform network periodic monitoring of the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data;

[0082] Step S3: Calculate the network stability index of the charging pile network status data to obtain the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, execute step S4; when the network stability index is less than the preset minimum network stability index, return to execute step S2;

[0083] Step S4: Obtain charging pile software version data; perform a secure backup of the charging pile software version data, thereby obtaining secure backup data; obtain server software version data; perform version difference encoding and incremental extraction of the server software version data and the charging pile software version data, thereby obtaining version incremental encoding data;

[0084] Step S5: When the version increment coded data is less than or equal to the preset guaranteed version increment threshold, the version increment coded data is incrementally verified and transmitted to the charging pile; when the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version coded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile;

[0085] Step S6: The charging pile decodes the version increment coded data or the complete version coded data and performs version merging to obtain version upgrade data; performs software version upgrade according to the version upgrade data and performs upgrade monitoring and rollback operations to realize automatic online upgrade of the charging pile software.

[0086] By collecting the historical data of charging pile usage, the present invention can deeply understand the user's charging behavior pattern, the usage during peak and trough periods, and provide basic data for subsequent upgrade period planning. By calculating the network stability index, the network connection quality of the charging pile can be quantitatively evaluated; when the network stability index reaches or exceeds the preset minimum stability index, it is ensured that the subsequent upgrade operation is carried out in a stable network environment to reduce the upgrade risk. The software version data of the current charging pile and the server is obtained to provide a basis for subsequent upgrade operations; the security backup ensures that the previous software version can be rolled back during the upgrade process, thereby improving the reliability and stability of the system. The security and accuracy of data transmission are improved, and only legal and complete incremental data are transmitted to the charging pile through verification; when the version incremental encoding data is less than or equal to the preset threshold, incremental transmission is adopted to reduce the transmission volume, reduce the network burden, and improve the transmission efficiency. The charging pile decodes and obtains incremental data or complete version data to ensure the availability of the data; the incremental data is merged with the current version, or the complete version data is applied to realize the upgrade of the software version. Through the incremental upgrade method, the transmission time and bandwidth required for the upgrade are reduced. The online upgrade of the charging pile software is realized to ensure that the charging pile system always runs on the latest software version; real-time monitoring is performed during the upgrade process, and once an abnormality occurs, it can be quickly rolled back to the previous version to ensure the continuity and stability of the charging service. Therefore, the present invention provides a method and system for automatic online upgrade of charging pile software, which analyzes the user's charging pile usage off-peak period to plan the upgrade time, accurately analyzes the network stability, can make upgrade judgments based on the network stability, and incrementally upgrade the new software version data, reduce data transmission, and improve the efficiency and stability of data transmission.

[0087] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of a method for automatically upgrading the software of a charging pile online according to the present invention. In this example, the method for automatically upgrading the software of a charging pile online includes the following steps:

[0088] Step S1: Obtaining charging pile usage history data; performing upgrade period planning on the charging pile usage history data, thereby obtaining upgrade period data;

[0089] In the embodiment of the present invention, the API or data interface provided by the charging pile monitoring system is used to obtain the charging pile usage history data, including the charging time and charging amount information, by request. The charging pile usage history data is analyzed to identify the off-peak period and formulate the upgrade period plan; including using the time series analysis tool to identify the typical off-peak period of each day. Based on the off-peak period planning, the upgrade time period data is generated to determine the upgrade time window of each charging pile (the off-peak period when the user uses the charging pile).

[0090] Step S2: Perform network periodic monitoring of the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data;

[0091] In the embodiment of the present invention, a charging pile monitoring tool is used to perform network periodic monitoring of the charging pile during the upgrade period (the network periodic monitoring time interval can be set to once every few minutes or hours, depending on the requirements for the real-time nature of the network status); it involves regularly sending network requests and recording network connection status and bandwidth information. The network status data returned by the monitoring tool is collected, including stability and delay information.

[0092] Step S3: Calculate the network stability index of the charging pile network status data to obtain the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, execute step S4; when the network stability index is less than the preset minimum network stability index, return to execute step S2;

[0093] In an embodiment of the present invention, the network status data obtained by the network monitoring tool includes information on network delay, available bandwidth, and packet loss rate; the network stability index of the charging pile network status data is calculated using a network stability index calculation formula; the calculated network stability index is compared with a preset minimum network stability index; if the network stability index is greater than or equal to the minimum network stability index, step S4 is executed; if the network stability index is less than the minimum network stability index, the process returns to step S2.

[0094] Among them, the process of waiting for the next round of network cycle monitoring: set the waiting time interval, which is usually consistent with the monitoring cycle. After the waiting time is over, re-perform network cycle monitoring and repeat the above steps until the execution condition is met.

[0095] Step S4: Obtain charging pile software version data; perform a secure backup of the charging pile software version data, thereby obtaining secure backup data; obtain server software version data; perform version difference encoding and incremental extraction of the server software version data and the charging pile software version data, thereby obtaining version incremental encoding data;

[0096] In the embodiment of the present invention, the current running software version data is obtained by querying the local storage of the charging pile; the charging pile software version data is encrypted using a secure backup algorithm, such as the data encryption standard AES, to generate secure backup data. By establishing secure communication with the server, the latest software version information of the server is queried. The incremental part of the difference is extracted using the version difference coding algorithm to generate version incremental coding data.

[0097] Step S5: When the version increment coded data is less than or equal to the preset guaranteed version increment threshold, the version increment coded data is incrementally verified and transmitted to the charging pile; when the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version coded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile;

[0098] In an embodiment of the present invention, the size of the version incremental encoded data is obtained and compared with a preset guaranteed version incremental threshold (such as 100MB); if the incremental size is less than or equal to the threshold, incremental verification is performed; otherwise, full version encoding is performed. The verification data extraction rule is called to extract the data to be verified; the incremental verification algorithm is executed to ensure the integrity and correctness of the data to be verified; an incremental verification report is generated, including the verification results and related information. The verified data to be verified, the incremental verification report, and the version incremental encoded data are transmitted to the charging pile; security protocols and encryption mechanisms are used during the transmission process to ensure the security of the data.

[0099] When the incremental size is greater than the preset threshold or the transmission fails, the following steps are performed: the server software version data and the charging pile software version data are fully encoded; the full version encoding data is generated. The full version encoding data is transmitted to the charging pile; during the transmission process, the security protocol and encryption mechanism are also used to ensure the security of the full version encoding data.

[0100] Step S6: The charging pile decodes the version increment coded data or the complete version coded data and performs version merging to obtain version upgrade data; performs software version upgrade according to the version upgrade data and performs upgrade monitoring and rollback operations to realize automatic online upgrade of the charging pile software;

[0101] In an embodiment of the present invention, a corresponding decoding algorithm is used to restore the version increment coded data or the complete version coded data to the original data; and the decoded data is obtained. The decoded data is checked to ensure its integrity and correctness; if it is the version increment coded data, the decoded data is merged with the current version of the charging pile to generate the merged version data; if it is the complete version coded data, the decoded data is directly used as the merged version data. Based on the merged version data, version upgrade data applicable to the charging pile is generated; including information about possible configuration changes, function additions or repairs. The generated version upgrade data is applied to the charging pile to implement the software version upgrade; the operating system and application of the charging pile are updated to ensure the availability of new functions and solve possible security vulnerabilities or problems. Monitoring is implemented during the upgrade process to check whether the upgrade operation is successful; the stability and performance of the new version are checked to ensure that no new problems are introduced. If problems are found during the upgrade process, or serious stability or performance problems are detected in the new version, a rollback operation is performed; the rollback restores the software version of the charging pile to the state before the upgrade to ensure that the system can operate normally. Record detailed logs of upgrade and rollback operations, including the time, results, and possible error information of the operation.

[0102] Preferably, step S1 comprises the following steps:

[0103] Step S11: Obtain charging pile usage history data and charging pile geographic location data through a charging pile monitoring system;

[0104] Step S12: performing regional division according to the geographical location data of the charging piles, thereby obtaining regional data of the charging piles;

[0105] Step S13: performing charging pile information matching on the charging pile area data and the charging pile usage history data, thereby obtaining charging pile information matching data;

[0106] Step S14: performing off-peak period analysis on the charging pile usage history data corresponding to each area in the charging pile area data according to the charging pile information matching data, thereby obtaining off-peak period data on the regional charging pile usage;

[0107] Step S15: Setting an upgrade time window according to off-peak data of regional charging piles, thereby obtaining upgrade time period data.

[0108] The present invention obtains the usage history data of the charging pile through the monitoring system, and can deeply understand the usage frequency, peak period and off-peak period of the charging pile, providing a basis for formulating the upgrade period plan; obtaining the geographical location data of the charging pile is helpful for subsequent regional division and analysis. The charging piles can be reasonably divided according to the geographical location data, and the charging piles can be divided into different areas, which is convenient for subsequent regional analysis and optimization; according to the divided areas, the relevant data of the charging piles in each area are sorted and obtained. The regional data and the usage history data are matched to ensure the consistency and accuracy of the data, providing a reliable basis for subsequent analysis; the charging pile information matching data is obtained, including the usage history information of the charging piles in each area. According to the information matching data, the charging pile usage history data in each area is analyzed during the off-peak period to find the off-peak period of charging demand in each area; the off-peak period of each area is determined to avoid a large impact on the charging pile service when formulating the upgrade time period. Based on the regional off-peak period data, a suitable upgrade time window is set to ensure that the upgrade operation is carried out as much as possible during the off-peak period of charging demand to reduce the impact on users; and the optimized upgrade time period data is obtained to ensure that the impact of the upgrade operation on users is minimized.

[0109] In the embodiment of the present invention, the API or data interface provided by the charging pile monitoring system is used to obtain the charging pile usage history data and geographic location data. Using the geographic location data, a suitable algorithm is used to divide the charging piles into regions, which can be divided according to distance or administrative area factors; the divided charging piles are grouped into different regions to obtain a list of charging piles in each region. The charging pile usage history data is matched with the regional data to determine the region to which each charging pile belongs; an association between the charging pile and the region is established to form charging pile information matching data, including charging pile ID and regional ID information. According to the charging pile information matching data, the charging pile usage history data in each region is analyzed during the off-peak period; the off-peak charging data of the charging piles in each region is identified and extracted, including the start and end time of the off-peak period and the information of the charging amount. Based on the off-peak period data of the regional charging piles, the upgrade time window is analyzed to find the most suitable upgrade time period for each region; according to the analysis results, the upgrade time period data is generated, including the upgrade start time and end time for each region.

[0110] Preferably, in step S3, the network stability index is calculated, wherein the network stability index calculation formula is specifically:

[0111]

[0112] In the formula, N represents the network stability index, n represents an integer approaching infinity, x represents the network bandwidth value, y represents the network delay value, z represents the data packet loss rate, and f(x, y, z) represents the network status function. represents the partial derivative of f(x,y,z) with respect to x, and r represents the maximum distance of the network connection.

[0113] The present invention constructs a network stability index calculation formula for calculating the network stability index of the charging pile network status data; in the formula Some of the complex combinations of network bandwidth, delay and data packet loss rate are introduced, and logarithmic operations are introduced to help comprehensively consider the impact of these network parameters on stability; the network bandwidth, delay and data packet loss rate are integrated, and the impact on network instability is amplified through logarithmic operations to better capture the comprehensive characteristics of the network state; among them, limit operations are constructed to enable the network stability index to tend to stability when it approaches infinity; through limit operations, it is ensured that the network stability index tends to stability when the data volume is large enough, making the calculation results more reliable and universal. The "partial derivative" of the network state function with respect to bandwidth, that is, the sensitivity of the network state to bandwidth changes, is quantified by calculating the partial derivative of bandwidth, making the network stability index more targeted and sensitive. The network state function comprehensively considers the impact of bandwidth, delay and packet loss rate. The network state function is formed by comprehensive processing of bandwidth, delay and packet loss rate, which more comprehensively reflects the actual stability of the network. The inverse sine function is partially introduced, and the relationship between bandwidth and delay is normalized by the maximum distance of the network connection; the network bandwidth and delay are associated with the maximum distance of the network connection and processed by the inverse sine function, so that the network stability index has adaptability to the network connection distance and is more in line with the actual network environment.

[0114] Preferably, step S4 comprises the following steps:

[0115] Step S41: obtaining charging pile software version data; using a hash function to generate a version data summary of the charging pile software version data, thereby obtaining a version data summary; performing version backup encryption on the charging pile software version data, thereby obtaining version backup encrypted data;

[0116] Step S42: performing version data integration on the version data summary and the version backup encrypted data, thereby obtaining secure backup data; obtaining server software version data; performing format standardization processing on the charging pile software version data and the server software version data, thereby obtaining version format standard data;

[0117] Step S43: extracting version key features from the version format standard data, thereby obtaining version key feature data, wherein the version key feature data includes file-level feature data and version-level feature data;

[0118] Step S44: performing similarity analysis according to the version key feature data, thereby obtaining similarity analysis data; dividing the version format standard data into difference blocks according to the version key feature data and the similarity analysis data, thereby obtaining difference block data;

[0119] Step S45: variable-length encoding is performed on the difference block data and incremental extraction is performed to obtain incremental encoded data; incremental optimization encoding is performed on the incremental encoded data to obtain version incremental encoded data.

[0120] The present invention provides a basis for subsequent secure backup and version comparison by acquiring the software version data of the charging pile; uses a hash function to generate a unique version data summary for the software version data for subsequent version integrity verification; encrypts the software version data through an encryption algorithm to protect the security of the backup data. The version data summary and the version backup encryption data are integrated into secure backup data to ensure the integrity and confidentiality of the backup; the software version data of the server is acquired for subsequent version comparison; the formats of the software version data of the charging pile and the server are unified to facilitate subsequent version comparison and difference analysis. Key features are extracted from the version data, including file-level feature data and version-level feature data, for subsequent similarity analysis and difference analysis. By comparing the key features of the versions, similarity analysis is performed to identify the similarity between the software versions of the charging pile and the server; according to the similarity analysis results, the version data is divided into difference blocks to prepare for incremental encoding; variable-length encoding is performed on the difference block data to reduce the amount of transmitted data, and incremental extraction is performed at the same time to obtain incremental encoded data; the incremental encoded data is optimized to further reduce the size of the transmitted data and improve the transmission efficiency.

[0121] As an example of the present invention, refer to Figure 2 As shown, in this example, step S4 includes:

[0122] Step S41: obtaining charging pile software version data; using a hash function to generate a version data summary of the charging pile software version data, thereby obtaining a version data summary; performing version backup encryption on the charging pile software version data, thereby obtaining version backup encrypted data;

[0123] In the embodiment of the present invention, the current software version information of the charging pile is queried; a hash function is used to perform a summary calculation on the charging pile software version data; and the charging pile software version data is encrypted for version backup, thereby obtaining version backup encrypted data.

[0124] Step S42: performing version data integration on the version data summary and the version backup encrypted data, thereby obtaining secure backup data; obtaining server software version data; performing format standardization processing on the charging pile software version data and the server software version data, thereby obtaining version format standard data;

[0125] In the embodiment of the present invention, the version data summary and the version backup encrypted data are integrated into a data structure; the software version information of the server is queried; and the formats of the charging pile and server software version data are unified.

[0126] Step S43: extracting version key features from the version format standard data, thereby obtaining version key feature data, wherein the version key feature data includes file-level feature data and version-level feature data;

[0127] In the embodiment of the present invention, the data structure and fields of the version format standard data are parsed to identify the structure and fields of the version data, and the structural model of the version data is established; the file list data is extracted according to the structural model of the version data, the hash value of each file is calculated and compared, and the meta information changes of the files are compared. The version number information is extracted and the version number changes are identified; the changes in the overall file size and quantity are analyzed to identify the overall change trend; and the version release time information is extracted.

[0128] Step S44: performing similarity analysis according to the version key feature data, thereby obtaining similarity analysis data; dividing the version format standard data into difference blocks according to the version key feature data and the similarity analysis data, thereby obtaining difference block data;

[0129] In the embodiment of the present invention, an algorithm (such as cosine similarity or edit distance) is used to perform similarity analysis on the key feature data of the versions; the result of the similarity analysis is represented as a similarity matrix or other forms of data structure. Based on the result of the similarity analysis, similarity data is extracted, including the similarity relationship between versions; the similarity data is saved for subsequent steps. Based on the similarity data, a difference block division strategy between versions is determined; according to the division strategy, the version format standard data is divided into a number of difference blocks.

[0130] Specific implementation process: Assume that there are two versions of software data A and B, and their key feature data are Key_Feature_A and Key_Feature_B.

[0131] Similarity analysis: Use a similarity algorithm to calculate the similarity between Key_Feature_A and Key_Feature_B. Assume that the similarity analysis result is Similarity_Matrix, where the element (i, j) represents the similarity between the i-th feature in Key_Feature_A and the j-th feature in Key_Feature_B.

[0132] Get similarity analysis data: Extract similarity data from Similarity_Matrix and save it as Similarity_Data.

[0133] Differential block partitioning: Based on Similarity_Data, formulate a differential block partitioning strategy. Assume that the partitioning strategy determines that the second feature of A is different from the third feature of B, and divides them into a differential block. Save the result of differential block partitioning as Differential_Block_Data.

[0134] Finally, Differential_Block_Data contains the difference block information between versions A and B, which will be used to generate incremental encoded data in subsequent steps.

[0135] Step S45: performing variable length encoding on the difference block data and performing incremental extraction, thereby obtaining incremental encoded data; performing incremental optimization encoding on the incremental encoded data, thereby obtaining version incremental encoded data;

[0136] In the embodiment of the present invention, the difference block data is subjected to variable length coding, such as Huffman coding, and the variable length coded data is called Variable_Length_Coded_Data. The Variable_Length_Coded_Data is optimized for incremental coding to reduce the size of the transmitted data.

[0137] Preferably, step S43 includes the following steps:

[0138] Step S431: performing version data structure analysis on the version format standard data, thereby obtaining the version data structure;

[0139] Step S432: extracting file-level features from the version format standard data according to the version data structure, thereby obtaining file-level feature data;

[0140] Step S433: extracting version-level features from the version format standard data according to the version data structure, thereby obtaining version-level feature data;

[0141] The file-level feature extraction in step S432 includes the following steps:

[0142] Step S4321: extracting a file list from the version format standard data, thereby obtaining file list data; performing file binary conversion on the version format standard data, thereby obtaining file binary data;

[0143] Step S4322: Utilize the MD5 hash function, the file list data, and the file binary data to perform file hash calculation on the version format standard data and perform file content comparison, thereby obtaining version file content change data;

[0144] Step S4323: Compare the file size and type of the version format standard data, thereby obtaining file size and type change data;

[0145] Step S4324: performing file meta information comparison on the version format standard data, thereby obtaining file meta information change data;

[0146] The version-level feature extraction in step S433 includes the following steps:

[0147] Step S4331: performing version number change identification on the version format standard data, thereby obtaining version number change data;

[0148] Step S4332: Analyze the overall file size and quantity changes of the version format standard data, thereby obtaining overall file size and quantity change data;

[0149] Step S4333: Analyze the version release time of the version format standard data to obtain the version release time data.

[0150] The present invention obtains the data structure of the software version by structural analysis of the version format standard data, which provides a basis for subsequent feature extraction and difference analysis. Detailed file-level feature extraction is performed on the software version data to more accurately analyze the differences between versions; wherein, the file-level feature extraction can obtain a list of all files contained in the software version, which provides a basis for subsequent file-level feature extraction; the hash value of the file is calculated using the MD5 hash function to quickly detect changes in the file content; the differences in the file content between versions are compared to obtain detailed data on the changes in the file content, and the specific changes in the file content are identified, rather than just the existence or non-existence of the file; the size and type changes of the files between versions are compared to extract the data on the changes in the file size and type; the meta information of the files between versions is compared to extract the change data of the file meta information. Version-level feature extraction is performed on the software version data to analyze the differences between versions from an overall level, wherein the version-level feature extraction can identify and extract the change data of the version number between versions; the changes in the overall file size and quantity are analyzed to extract the data on the changes in the overall file size and quantity; the changes in the version release time are analyzed to extract the data on the version release time.

[0151] In the embodiment of the present invention, the version format standard data is parsed to identify the data structure and fields therein, and a structural model of the version data is established; the version format standard data is analyzed to extract the structural information of the version data.

[0152] Among them, file-level feature extraction: extract file list data from the version data structure; perform MD5 hash calculation on each file to generate a file hash value; compare file hash values ​​to identify changes in file content. Compare file size and type information to identify changes in file size and type. Compare file meta-information (such as creation time, modification time) to identify changes in meta-information.

[0153] Among them, version-level feature extraction: extract version number information and identify version number changes. Analyze the changes in the overall file size and quantity and identify the overall change trend. If the version number changes, it indicates a major function or structure adjustment, and the version number change is regarded as an important version-level feature. Extract version release time information.

[0154] Preferably, step S5 comprises the following steps:

[0155] Step S51: when the version increment encoded data is less than or equal to the preset guaranteed version increment threshold, extract verification data from the version increment encoded data to obtain data to be verified;

[0156] Step S52: performing a version increment legality check on the version increment encoded data, thereby obtaining version increment legality data;

[0157] Step S53: setting the applicability threshold and calculating the version applicability index according to the charging pile software version data and the version increment coding data, thereby obtaining the applicability threshold and the version applicability index;

[0158] Step S54: performing applicability judgment on the version applicability index and the applicability threshold. When the version applicability index is greater than or equal to the applicability threshold, version applicability data is generated and step S45 is executed; when the version applicability index is less than the applicability threshold, the version incremental encoded data transmission fails and step S46 is executed;

[0159] Step S55: Generate an incremental verification report for the data to be verified according to the version increment legitimacy data and the version applicability data, thereby obtaining an incremental verification report; transmit the incremental verification report and the version increment encoding data to the charging pile, and execute step S6;

[0160] Step S56: When the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version encoded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile.

[0161] The present invention extracts the data to be verified from the version increment coded data to prepare for subsequent legitimacy verification and applicability judgment. Through legitimacy verification, it is ensured that the extracted version increment data is complete and not tampered with; the legal source of the version increment data is verified by using the digital signature technology to enhance the credibility of the data. According to the current software version and the version increment coded data of the charging pile, the applicability threshold is set to determine whether the version is applicable; by considering multiple factors of version applicability, the version applicability index is calculated to quantitatively evaluate the version applicability. It is determined whether the version applicability index reaches the set applicability threshold to decide whether to continue the incremental verification; and decision support information is provided. If the version applicability index is high enough, the incremental verification can be continued, otherwise the complete version coding transmission is performed. A detailed incremental verification report is generated, including the verification result and the verification timestamp information; and decision support information is provided. If the verification passes, the generated incremental verification report and the version increment coded data are transmitted to the charging pile. The server and the charging pile software version data are fully version-encoded to back up the entire software version for transmission to the charging pile; the fault-tolerant mechanism when the version increment coded data is greater than the threshold or the transmission fails ensures that the charging pile can obtain the complete version data.

[0162] As an example of the present invention, refer to Figure 3 As shown, in this example, step S5 includes:

[0163] Step S51: when the version increment encoded data is less than or equal to the preset guaranteed version increment threshold, extract verification data from the version increment encoded data to obtain data to be verified;

[0164] In the embodiment of the present invention, the size of the original incremental data is calculated in bytes; when the version incremental encoded data is less than or equal to a preset guaranteed version incremental threshold (such as 100MB); according to the verification data extraction rule, the data to be verified is extracted from the original incremental data to obtain the data to be verified;

[0165] Among them, the verification data extraction rules are as follows: in the original incremental data, the data structure is defined, including the format of the data block, identifier, and metadata information; the data blocks related to the upgrade are identified based on the defined identifiers or specific tags; version information is included in the data block, and the data blocks related to the current software version are filtered out based on the version information, and only the data related to the current version needs to be verified; data integrity tags are added to the data blocks to identify which data blocks need to be checked during the verification phase; which data blocks are incrementally encoded are marked so that these blocks can be identified and decoded during verification.

[0166] Step S52: performing a version increment legality check on the version increment encoded data, thereby obtaining version increment legality data;

[0167] In the embodiment of the present invention, a digital signature and a security algorithm are used to perform a version increment legitimacy check to generate version increment legitimacy data.

[0168] Step S53: setting the applicability threshold and calculating the version applicability index according to the charging pile software version data and the version increment coding data, thereby obtaining the applicability threshold and the version applicability index;

[0169] In the embodiment of the present invention, the applicability threshold setting algorithm is used to calculate the applicability threshold by considering the characteristics of the current version and the incremental encoding data. The applicability data to be compared and the charging pile software version data are used to generate a version difference report; the applicability threshold weight is allocated according to the historical threshold adjustment coefficient, version change complexity, user experience evaluation and compatibility requirements to obtain the applicability threshold weight data; the applicability threshold calculation algorithm is used to calculate the version applicability index by considering various weights and indicators.

[0170] Step S54: Performing a suitability judgment on the version suitability index and the suitability threshold. When the version suitability index is greater than or equal to the suitability threshold, version suitability data is generated and step S55 is executed; when the version suitability index is less than the suitability threshold, the version increment encoded data transmission fails and step S56 is executed;

[0171] In the embodiment of the present invention, it is determined whether the version applicability index is greater than or equal to the applicability threshold; if the version applicability index meets the condition, version applicability data is generated; if the version applicability index is less than the applicability threshold, step S56 is executed.

[0172] Step S55: Generate an incremental verification report for the data to be verified according to the version increment legitimacy data and the version applicability data, thereby obtaining an incremental verification report; transmit the incremental verification report and the version increment encoding data to the charging pile, and execute step S6;

[0173] In the embodiment of the present invention, a secure decoding algorithm is used to decode the data to be verified to obtain the original data; the version increment legitimacy verification data generated in the previous step S52 is obtained; the digital signature and the security algorithm are used to perform a version increment legitimacy verification on the decoded original data to ensure the integrity and legitimacy of the data; the version applicability data generated in the previous step S53 is obtained; based on the applicability data, it is determined whether the decoded original data is applicable to the current software version; based on the results of the legitimacy verification and applicability judgment, a detailed incremental verification report is generated; the report includes information on the verification results, applicability judgment, verification data, and original data. The incremental verification report and the version increment encoded data are transmitted to the charging pile.

[0174] Step S56: When the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version encoded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile.

[0175] In an embodiment of the present invention, when the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails; the latest software version data is obtained from the server; the latest software version data is encoded to obtain the complete version coded data; and the complete version coded data is transmitted to the charging pile.

[0176] Preferably, step S53 includes the following steps:

[0177] Step S531: extracting the applicability data to be compared from the version increment coded data, thereby obtaining the applicability data to be compared; generating a version difference report for the applicability data to be compared using the charging pile software version data, thereby obtaining the version difference report;

[0178] Step S532: Perform version change complexity analysis on the version difference report to obtain version change complexity data; perform user experience evaluation based on the version difference report to obtain user experience evaluation data; perform compatibility requirement analysis on the charging pile system to obtain compatibility requirement data; obtain historical verification data, and extract historical threshold adjustment coefficients based on the historical verification data to obtain historical threshold adjustment coefficients;

[0179] Step S533: performing applicability threshold weight allocation on the version change complexity data, the user experience evaluation data, the compatibility requirement data, and the historical threshold adjustment coefficient, thereby obtaining applicability threshold weight data;

[0180] Step S534: setting the applicability threshold according to the applicability threshold weight data, thereby obtaining the applicability threshold;

[0181] Step S535: Calculate the version applicability index based on the version difference report to obtain the version applicability index.

[0182] The present invention extracts the applicability data to be compared with the charging pile software version from the version increment encoding data, and prepares to generate a version difference report. The version difference report is analyzed to evaluate the complexity of the version change, including the new functions and the defects repaired; the version change complexity data is obtained for the subsequent applicability threshold weight allocation. By analyzing the version difference report, the impact of the new version on the user experience is evaluated, including the interface changes and the interaction mode; the user experience evaluation data is obtained for the subsequent applicability threshold weight allocation. The compatibility requirements of the charging pile system, including the compatibility of hardware and software, are analyzed to understand the compatibility impact of the new version on the existing system. Historical verification data is collected, including the applicability verification results of previous versions; based on the historical verification data, the historical threshold adjustment coefficient is extracted for adjusting the applicability threshold according to historical experience. Based on various data, the weight of the applicability threshold is assigned to determine the relative importance of each factor in the applicability judgment. Combined with the applicability threshold weight data, the applicability threshold is set to determine whether the new version is applicable to the current charging pile software. Based on the version difference report, the applicability threshold and the weight data, the version applicability index is calculated to provide a quantitative indicator for subsequent judgment. The higher the applicability index, the more applicable the new version is to the current system.

[0183] As an example of the present invention, refer to Figure 4 As shown, in this example, step S53 includes:

[0184] Step S531: extracting the applicability data to be compared from the version increment coded data, thereby obtaining the applicability data to be compared; generating a version difference report for the applicability data to be compared using the charging pile software version data, thereby obtaining the version difference report;

[0185] In an embodiment of the present invention, applicability data to be compared related to the charging pile software version is extracted from the version increment encoded data, including functional modules, configuration files, and program interfaces; a comparison tool is used to compare the applicability data to be compared with the charging pile software version data, and difference information is recorded; the difference information includes newly added, modified, and deleted files, functions, and configurations; it is assumed that the applicability data to be compared includes the configuration file, charging module, and user interface module of the charging pile; the version difference report may include information that a configuration item has been added, the algorithm of the charging module has been modified, and a user interface element that is no longer used has been deleted.

[0186] Step S532: Perform version change complexity analysis on the version difference report to obtain version change complexity data; perform user experience evaluation based on the version difference report to obtain user experience evaluation data; perform compatibility requirement analysis on the charging pile system to obtain compatibility requirement data; obtain historical verification data, and extract historical threshold adjustment coefficients based on the historical verification data to obtain historical threshold adjustment coefficients;

[0187] In an embodiment of the present invention, detailed change information is obtained from the version difference report, including newly added functions, modified functions, and deleted functions; based on the indicators of the number, type, and scope of impact of the changes, a version change complexity analysis is performed to generate version change complexity data. Key indicators related to user experience are extracted from the version difference report, such as interface changes and interaction process changes; based on the extracted indicators, a user experience evaluation is performed to generate user experience evaluation data. A detailed analysis is performed on the charging pile system to understand the relationship between system components and modules; key information is extracted from the version difference report and system architecture analysis, including interface changes and data structure changes; based on the extracted key information, compatibility requirements are formulated to generate compatibility requirement data. Historical data on version upgrades is obtained from historical verification records, including successful upgrades and failed rollbacks; historical verification data is analyzed to identify influencing factors in different situations; based on the analysis results of historical verification data, historical threshold adjustment coefficients are extracted.

[0188] Step S533: performing applicability threshold weight allocation on the version change complexity data, the user experience evaluation data, the compatibility requirement data, and the historical threshold adjustment coefficient, thereby obtaining applicability threshold weight data;

[0189] In an embodiment of the present invention, the complexity of the changes contained in the incremental version is considered; if the changes are relatively simple, they may be more easily applicable to the current version, so the threshold weight can be lowered. The compatibility requirements of the charging pile system are considered; if the new version is highly compatible with the old version, the threshold can be appropriately lowered so that more incremental versions can be accepted. The threshold is adjusted based on historical verification data; by analyzing the application of the incremental version of the previous version, an empirical value of applicability can be obtained, and it can be used as a reference to set the threshold. Consider the impact of user experience; if the incremental version has little impact on user experience, the threshold can be appropriately increased so that more incremental versions can be applied.

[0190] Step S534: setting the applicability threshold according to the applicability threshold weight data, thereby obtaining the applicability threshold;

[0191] In the embodiment of the present invention, the suitability threshold is set based on the suitability threshold weight data to obtain the suitability threshold.

[0192] Step S535: Calculate the version applicability index based on the version difference report, thereby obtaining the version applicability index;

[0193] In the embodiment of the present invention, the version difference report and the applicability threshold are used to calculate the version applicability index to obtain the version applicability index.

[0194] Preferably, in step S535, the version applicability index is calculated, wherein the version applicability index calculation formula is specifically:

[0195]

[0196] Where A represents the applicability of the incremental version to the current version, α represents the change complexity of the incremental version relative to the current version, β represents the compatibility score of the incremental version relative to the current version, m represents the auxiliary variable in the limit operation, ΔV represents the total change between the current version and the incremental version, ΔT represents the time interval between the current version and the incremental version, γ represents the emphasis on stability in version applicability, δ represents the change angle direction of the incremental version relative to the current version, f represents the change frequency within the time interval between the current version and the incremental version, ∈ represents the functional change factor, Indicates the performance impact factor.

[0197] The present invention constructs a version applicability index calculation formula for calculating the version applicability index based on the version difference report; the ln(α+β) part of the formula performs logarithmic operations on the change complexity a of the incremental version and the compatibility score β, which helps to take the two into comprehensive consideration, making the version applicability index more comprehensive and interpretable. The part calculates the ratio of the total change amount and time interval between the current version and the incremental version to consider the relative change rate between versions; it helps to more accurately reflect the change frequency between versions. Part of it is used to adjust the applicability index to make it more sensitive to the direction and stability of version changes. The part represents the partial derivative of the change frequency with respect to the auxiliary variable m, which is used to consider the sensitivity of the version applicability to the change frequency; it helps to better reflect the impact of the version change frequency on the applicability. Partially considers the combined impact of functional changes and performance impact on version applicability; helps balance the impact of functionality and performance.

[0198] Preferably, step S6 comprises the following steps:

[0199] Step S61: the charging pile decodes the version increment coded data or the complete version coded data to obtain decoded data;

[0200] Step S62: Perform integrity check on the decoded data using a verification algorithm, thereby obtaining integrity check data;

[0201] Step S63: performing version merging on the decoded data according to the integrity check data, thereby obtaining version merged data;

[0202] Step S64: Generate version upgrade data according to the version merge data, thereby obtaining version upgrade data;

[0203] Step S65: Perform software version upgrade according to the version upgrade data and perform upgrade monitoring and rollback operations to achieve automatic online upgrade of the charging pile software.

[0204] Through the decoding operation, the charging pile of the present invention can restore the encoded incremental data or complete version data, making it readable and usable, providing a basis for subsequent verification and upgrade operations. The decoded data is verified by a verification algorithm to ensure that the data has not been damaged or tampered with during the transmission and decoding process; verification data that records the integrity of the data is generated for subsequent judgment of the reliability of the decoded data. According to the integrity verification data, the decoded data is version merged to ensure the correctness and consistency of the data and prepare data for subsequent software version upgrades. The merged data is used to generate the final version upgrade data, including updated program code and configuration files; version upgrade data containing update information is generated for actual software version upgrade operations. According to the generated version upgrade data, the software version upgrade operation is performed to ensure that the charging pile system runs on the latest software version and improve system performance and functions; real-time monitoring is performed during the upgrade process, and once an abnormality is found or the upgrade fails, it is quickly rolled back to the previous version to ensure the stability of the system and the continuity of services.

[0205] In an embodiment of the present invention, the version increment coded data or the complete version coded data is extracted from the upgrade data; the coded data is restored to the original data using the corresponding decoding algorithm. The decoded data is integrity checked using a predetermined verification algorithm (such as CRC, hash function); integrity check data is generated and recorded for subsequent confirmation of whether the data is complete and has not been tampered with. The integrity check data is checked to ensure that the decoded data has not been damaged or tampered with; if the integrity check passes, the decoded data is merged with the current version of the charging pile to generate version merge data. Based on the version merge data, version upgrade data applicable to the charging pile is generated; in the case of including incremental data, the version merge data is applied to the current version to generate new software version data. The generated version upgrade data is applied to the charging pile to implement the software version upgrade; monitoring is implemented during the upgrade process to check whether the upgrade operation is successful; if the upgrade fails or an exception occurs, a rollback operation is performed to roll back the charging pile software to the previous stable version; and detailed logs of the upgrade and rollback operations are recorded for subsequent analysis and improvement.

[0206] Preferably, the present invention further provides a charging pile software automatic online upgrade system, which is used to perform the above-mentioned charging pile software automatic online upgrade, comprising:

[0207] The charging pile upgrade time planning module is used to obtain the charging pile usage history data; perform upgrade time period planning on the charging pile usage history data, thereby obtaining the upgrade time period data;

[0208] The network cycle monitoring module is used to perform network cycle monitoring on the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data;

[0209] A network stability judgment module is used to calculate the network stability index of the charging pile network status data, thereby obtaining the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, step S4 is executed; when the network stability index is less than the preset minimum network stability index, the execution returns to step S2;

[0210] Software version incremental extraction is used to obtain charging pile software version data; perform secure backup of the charging pile software version data, thereby obtaining secure backup data; obtain server-side software version data; perform version difference encoding and incremental extraction of the server-side software version data and the charging pile software version data, thereby obtaining version incremental encoding data;

[0211] The incremental coding data transmission judgment module is used to perform incremental verification on the incremental version coding data and transmit it to the charging pile when the incremental version coding data is less than or equal to the preset guaranteed version increment threshold; when the incremental version coding data is greater than the preset guaranteed version increment threshold or the incremental version coding data transmission fails, perform complete version coding on the server software version data and the charging pile software version data, thereby obtaining the complete version coding data, and transmit the complete version coding data to the charging pile;

[0212] The software version upgrade monitoring module is used for the charging pile to decode the version incremental encoding data or the complete version encoding data and merge the versions to obtain the version upgrade data; according to the version upgrade data, the software version is upgraded and the upgrade monitoring rollback operation is performed to realize the automatic online upgrade of the charging pile software.

[0213] By collecting the historical data of charging pile usage, the present invention can deeply understand the user's charging behavior pattern, the usage during peak and trough periods, and provide basic data for subsequent upgrade period planning. By calculating the network stability index, the network connection quality of the charging pile can be quantitatively evaluated; when the network stability index reaches or exceeds the preset minimum stability index, it is ensured that the subsequent upgrade operation is carried out in a stable network environment to reduce the upgrade risk. The software version data of the current charging pile and the server is obtained to provide a basis for subsequent upgrade operations; the security backup ensures that the previous software version can be rolled back during the upgrade process, thereby improving the reliability and stability of the system. The security and accuracy of data transmission are improved, and only legal and complete incremental data are transmitted to the charging pile through verification; when the version incremental encoding data is less than or equal to the preset threshold, incremental transmission is adopted to reduce the transmission volume, reduce the network burden, and improve the transmission efficiency. The charging pile decodes and obtains incremental data or complete version data to ensure the availability of the data; the incremental data is merged with the current version, or the complete version data is applied to realize the upgrade of the software version. Through the incremental upgrade method, the transmission time and bandwidth required for the upgrade are reduced. The online upgrade of the charging pile software is realized to ensure that the charging pile system always runs on the latest software version; real-time monitoring is performed during the upgrade process, and once an abnormality occurs, it can be quickly rolled back to the previous version to ensure the continuity and stability of the charging service. Therefore, the present invention provides a method and system for automatic online upgrade of charging pile software, which analyzes the user's charging pile usage off-peak period to plan the upgrade time, accurately analyzes the network stability, can make upgrade judgments based on the network stability, and incrementally upgrade the new software version data, reduce data transmission, and improve the efficiency and stability of data transmission.

[0214] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0215] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for automatically upgrading charging pile software online, characterized in that: The following steps are involved: Step S1: Obtaining charging pile usage history data; performing upgrade period planning on the charging pile usage history data, thereby obtaining upgrade period data; Step S2: Perform network periodic monitoring of the charging pile through the charging pile monitoring tool according to the upgrade time period data, so as to obtain the charging pile network status data; Step S3: Calculate the network stability index of the charging pile network status data to obtain the network stability index; when the network stability index is greater than or equal to the preset minimum network stability index, execute step S4; when the network stability index is less than the preset minimum network stability index, return to execute step S2; the network stability index is calculated in step S3, where the network stability index calculation formula is specifically: ； ； In the formula, represents the network stability index, represents an integer approaching infinity, Indicates the network bandwidth value. Indicates the network delay value. Indicates the data packet loss rate. represents the network status function, express right The partial derivative of Indicates the maximum distance of the network connection; Step S4: Obtain charging pile software version data; perform a safe backup of the charging pile software version data, thereby obtaining safe backup data; Obtain server software version data; perform version difference encoding on the server software version data and the charging pile software version data and perform incremental extraction to obtain version incremental encoding data; Step S5: When the version increment coded data is less than or equal to the preset guaranteed version increment threshold, the version increment coded data is incrementally verified and transmitted to the charging pile; when the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version coded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile; Step S6: The charging pile decodes the version increment coded data or the complete version coded data and performs version merging, thereby obtaining version upgrade data; The software version is upgraded according to the version upgrade data and the upgrade monitoring and rollback operation is performed to realize the automatic online upgrade of the charging pile software.

2. The method for automatic online upgrade of charging pile software according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Obtain charging pile usage history data and charging pile geographic location data through a charging pile monitoring system; Step S12: performing regional division according to the geographical location data of the charging piles, thereby obtaining regional data of the charging piles; Step S13: performing charging pile information matching on the charging pile area data and the charging pile usage history data, thereby obtaining charging pile information matching data; Step S14: performing off-peak period analysis on the charging pile usage history data corresponding to each area in the charging pile area data according to the charging pile information matching data, thereby obtaining off-peak period data on the regional charging pile usage; Step S15: Setting an upgrade time window according to off-peak data of regional charging piles, thereby obtaining upgrade time period data.

3. The method for automatic online upgrading of charging pile software according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: obtaining charging pile software version data; using a hash function to generate a version data summary of the charging pile software version data, thereby obtaining a version data summary; performing version backup encryption on the charging pile software version data, thereby obtaining version backup encrypted data; Step S42: performing version data integration on the version data summary and the version backup encrypted data, thereby obtaining secure backup data; obtaining server software version data; performing format standardization processing on the charging pile software version data and the server software version data, thereby obtaining version format standard data; Step S43: extracting version key features from the version format standard data, thereby obtaining version key feature data, wherein the version key feature data includes file-level feature data and version-level feature data; Step S44: performing similarity analysis according to the version key feature data, thereby obtaining similarity analysis data; dividing the version format standard data into difference blocks according to the version key feature data and the similarity analysis data, thereby obtaining difference block data; Step S45: variable-length encoding is performed on the difference block data and incremental extraction is performed to obtain incremental encoded data; incremental optimization encoding is performed on the incremental encoded data to obtain version incremental encoded data.

4. The method for automatic online upgrade of charging pile software according to claim 3, characterized in that: Step S43 includes the following steps: Step S431: performing version data structure analysis on the version format standard data, thereby obtaining the version data structure; Step S432: extracting file-level features from the version format standard data according to the version data structure, thereby obtaining file-level feature data; Step S433: extracting version-level features from the version format standard data according to the version data structure, thereby obtaining version-level feature data; The file-level feature extraction in step S432 includes the following steps: Step S4321: extracting a file list from the version format standard data, thereby obtaining file list data; performing file binary conversion on the version format standard data, thereby obtaining file binary data; Step S4322: Utilize the MD5 hash function, the file list data, and the file binary data to perform file hash calculation on the version format standard data and perform file content comparison, thereby obtaining version file content change data; Step S4323: Compare the file size and type of the version format standard data, thereby obtaining file size and type change data; Step S4324: performing file meta information comparison on the version format standard data, thereby obtaining file meta information change data; The version-level feature extraction in step S433 includes the following steps: Step S4331: performing version number change identification on the version format standard data, thereby obtaining version number change data; Step S4332: Analyze the overall file size and quantity changes of the version format standard data, thereby obtaining overall file size and quantity change data; Step S4333: Analyze the version release time of the version format standard data to obtain the version release time data.

5. The method for automatic online upgrading of charging pile software according to claim 1, characterized in that: Step S5 includes the following steps: Step S51: when the version increment encoded data is less than or equal to the preset guaranteed version increment threshold, extract verification data from the version increment encoded data to obtain data to be verified; Step S52: performing a version increment legality check on the version increment encoded data, thereby obtaining version increment legality data; Step S53: setting the applicability threshold and calculating the version applicability index according to the charging pile software version data and the version increment coding data, thereby obtaining the applicability threshold and the version applicability index; Step S54: Performing a suitability judgment on the version suitability index and the suitability threshold. When the version suitability index is greater than or equal to the suitability threshold, version suitability data is generated and step S55 is executed; when the version suitability index is less than the suitability threshold, the version increment encoded data transmission fails and step S56 is executed; Step S55: Generate an incremental verification report for the data to be verified according to the version increment legitimacy data and the version applicability data, thereby obtaining an incremental verification report; transmit the incremental verification report and the version increment encoding data to the charging pile, and execute step S6; Step S56: When the version increment coded data is greater than the preset guaranteed version increment threshold or the version increment coded data transmission fails, the server software version data and the charging pile software version data are fully version encoded to obtain the complete version coded data, and the complete version coded data is transmitted to the charging pile.

6. The method for automatic online upgrade of charging pile software according to claim 5, characterized in that: Step S53 includes the following steps: Step S531: extracting the applicability data to be compared from the version increment coded data, thereby obtaining the applicability data to be compared; generating a version difference report for the applicability data to be compared using the charging pile software version data, thereby obtaining the version difference report; Step S532: Perform version change complexity analysis on the version difference report to obtain version change complexity data; perform user experience evaluation based on the version difference report to obtain user experience evaluation data; perform compatibility requirement analysis on the charging pile system to obtain compatibility requirement data; obtain historical verification data, and extract historical threshold adjustment coefficients based on the historical verification data to obtain historical threshold adjustment coefficients; Step S533: performing applicability threshold weight allocation on the version change complexity data, the user experience evaluation data, the compatibility requirement data, and the historical threshold adjustment coefficient, thereby obtaining applicability threshold weight data; Step S534: setting the applicability threshold according to the applicability threshold weight data, thereby obtaining the applicability threshold; Step S535: Calculate the version applicability index based on the version difference report to obtain the version applicability index.

7. The method for automatic online upgrade of charging pile software according to claim 6, characterized in that: In step S535, the version applicability index is calculated, wherein the version applicability index calculation formula is specifically: ； In the formula, Indicates the applicability of the incremental version to the current version. Indicates the complexity of the incremental version relative to the current version. Indicates the compatibility score of the incremental version relative to the current version. represents the auxiliary variable in the limit operation, Indicates the total change between the current version and the incremental version. Indicates the time interval between the current version and the incremental version. Indicates the emphasis on stability in version applicability. Indicates the change angle of the incremental version relative to the current version. Indicates the frequency of changes in the time interval between the current version and the incremental version. represents the function change factor, Indicates the performance impact factor.

8. The method for automatic online upgrade of charging pile software according to claim 1, characterized in that: Step S6 includes the following steps: Step S61: the charging pile decodes the version increment coded data or the complete version coded data to obtain decoded data; Step S62: Perform integrity check on the decoded data using a verification algorithm, thereby obtaining integrity check data; Step S63: performing version merging on the decoded data according to the integrity check data, thereby obtaining version merged data; Step S64: Generate version upgrade data according to the version merge data, thereby obtaining version upgrade data; Step S65: Perform software version upgrade according to the version upgrade data and perform upgrade monitoring and rollback operations to achieve automatic online upgrade of the charging pile software.

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