Charging pile data unified standard formulating method and system based on Internet of Things platform, medium and processor

Abstract

The invention provides a charging pile data unified standard formulating method based on an Internet of Things platform, which comprises the following steps: S1, integrating a plurality of charging pile communication protocol analysis modules in the Internet of Things platform, and dynamically loading the corresponding protocol analysis modules according to the protocol types used by charging piles when the charging piles are accessed; s2, determining a unified standard according to the analyzed charging pile data; s3, establishing a protocol mapping table according to the determined unified standard, recording a data field mapping relationship between the data of different charging piles and the unified standard, and performing data conversion on the received charging pile data according to the mapping table; s4, performing cleaning, feature extraction and storage on the converted data; and S5, formulating a unified standard for the charging process and the multi-platform data interaction process. Charging pile data of different manufacturers can be accessed to an Internet of Things platform in a consistent specification, the universality and compatibility of the data are improved, and the complexity of data processing is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile data processing, and particularly to a method, a system, a medium and a processor for formulating a unified standard for charging pile data based on an Internet of Things platform. Background Art

[0002] The definition of the Internet of Things is a network that connects any item to the Internet through information sensing devices such as radio frequency identification (RFID), infrared sensors, global positioning systems, laser scanners, etc., and conducts information exchange and communication according to an agreed protocol to achieve intelligent identification, positioning, tracking, monitoring and management.

[0003] In recent years, China has become the world's largest producer and seller of new energy vehicles. As of September 2021, the number of new energy vehicles in China reached 6.4033 million, accounting for 60.29% of the global total. The continuous growth of the number of new energy vehicles has further promoted the construction of charging infrastructure. In terms of market size, according to Frost & Sullivan data, the market size of China's charging infrastructure (charging and swapping) has increased from 1.76 billion yuan in 2016 to 55.92 billion yuan in 2020, accounting for about 36.4% of the global market in 2020. It is expected that the domestic market size will reach 216.85 billion yuan in 2025, with an average annual compound growth rate of 36.2% from 2021 to 2025. With the rapid popularization of new energy vehicles, the market prospect of charging infrastructure will be further expanded.

[0004] The Internet of Things platform connects electric vehicles and their charging devices through terminals. The Internet of Things platform generally has functions such as data collection, data cleaning, data analysis and data storage. Data collection is to upload the operation data of various electrical devices on various intelligent in-vehicle terminals, electric vehicles, charging stations and charging devices in real time, and screen out useful data according to business needs. Data cleaning is to identify and process missing values and outliers after screening out the data. Data analysis is to apply various operation processing methods, such as clustering, statistics, regression, classification algorithms and models, to the cleaned data for multi-dimensional analysis of the data, such as the time dimension, the power change of different battery types, drive types, and charging powers; the location dimension, the power change of different regions and parking lots. Data storage is to classify the analyzed data and store it in a database.

[0005] However, due to the lack of a unified data standard, when data from each manufacturer is connected to the Internet of Things platform, it needs to be customized and imported, which consumes a lot of time and brings difficulties to the Internet of Things platform to connect data from different manufacturers, making it impossible for the Internet of Things platform to uniformly monitor and manage the data.

[0006] In view of this, there is a need for a method, system, medium and processor for formulating a unified standard for charging pile data based on the Internet of Things platform. Summary of the Invention

[0007] In view of the problem that there is no unified data standard in the prior art, and when data from each manufacturer is connected to the Internet of Things platform, customized import is required, which consumes a lot of time and causes difficulties in connecting data from different manufacturers to the Internet of Things platform. The present invention provides a method, system, medium and processor for formulating a unified standard for charging pile data based on the Internet of Things platform, which can enable charging pile data from different manufacturers to be connected to the Internet of Things platform in a consistent specification, improve the universality and compatibility of data, and reduce the complexity of data processing. The specific technical solutions are as follows:

[0008] A method for formulating a unified standard for charging pile data based on the Internet of Things platform, comprising:

[0009] S1: Integrate several charging pile communication protocol parsing modules in the Internet of Things platform, and dynamically load the corresponding protocol parsing module according to the protocol type used when the charging pile is connected;

[0010] S2: Determine a unified standard according to the parsed charging pile data;

[0011] S3: Establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table;

[0012] S4: Clean, extract features and store the converted data;

[0013] S5: Formulate a unified standard for the charging process and the multi-platform data interaction process.

[0014] Further, the determining of the unified standard according to the parsed charging pile data includes determining a unified standard for the charging pile data type, data format, data encoding, and communication protocol.

[0015] Further, the determination of the unified standard for the data format includes the following steps:

[0016] Evaluate and calculate the transmission rate, compression ratio, parsing time, memory occupancy, new field cost, and compatibility of various data formats;

[0017] Conduct a comprehensive evaluation of various data formats. The comprehensive evaluation formula is as follows:

[0018]

[0019] In the above formula, is the comprehensive score of the jth data format; n is the number of indicators participating in the evaluation; Weighted score based on basic indicators; W i is the weight of the i-th indicator, and is the evaluation calculation value of the j-th data format on the i-th indicator; is the normalization process of the evaluation calculation value of the j-th data format on the i-th indicator; is the part of the interactive influence of indicators; m is the number of pairs of indicators with interactive influence among the n indicators of the j-th data format, that is, the number of indicator interaction pairs; A k is the influence coefficient of the k-th indicator interaction pair among the m indicator interaction pairs; represents the interaction between the i-th indicator and the l-th indicator that make up the k-th indicator interaction pair, is the evaluation calculation value of the i-th indicator in the k-th indicator interaction pair, is the evaluation calculation value of the l-th indicator in the k-th indicator interaction pair; P j is the penalty term; R j is the reward term.

[0020] Further, the calculation formula of the interaction is as follows:

[0021]

[0022] where, is the correlation coefficient between the i-th k indicator and the l-th k indicator; is for to perform normalization; is for to perform normalization.

[0023] Further, the calculation formula of the correlation coefficient is as follows:

[0024]

[0025] where p is the number of data samples, R i , C i are the transmission rate and data compression ratio of the i-th sample respectively, is the average value of the transmission rate and data compression ratio.

[0026] Further, the calculation formula of the penalty term P j is as follows:

[0027]

[0028] In the above formula, q is the number of penalty factors; Bs is the weight of the s-th penalty factor; is the score of the j-th data format on the s-th penalty factor.

[0029] Furthermore, the reward term R j has the following calculation formula:

[0030]

[0031] In the above formula, r is the number of reward factors; C t is the weight of the t-th reward factor; is the score of the j-th data format on the t-th reward factor.

[0032] A charging pile data unified standard formulation system based on the Internet of Things platform, which is applied to the above-mentioned charging pile data unified standard formulation method based on the Internet of Things platform, includes:

[0033] A data access layer, which is used to integrate several charging pile communication protocol parsing modules in the Internet of Things platform, and dynamically load the corresponding protocol parsing module according to the protocol type used when the charging pile is accessed;

[0034] A standard layer, which is used to determine a unified standard according to the parsed charging pile data;

[0035] A mapping layer, which is used to establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table;

[0036] A processing layer, which is used to clean, extract features and store the converted data;

[0037] An interaction layer, which is used to formulate unified standards for the charging process and the multi-platform data interaction process.

[0038] A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored program, wherein when the program runs, it controls the device where the computer-readable storage medium is located to execute the above-mentioned charging pile data unified standard formulation method based on the Internet of Things platform.

[0039] A processor, the processor is used to run a program, wherein when the program runs, it executes the above-mentioned charging pile data unified standard formulation method based on the Internet of Things platform.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] 1. Unified data management

[0042] Unified data standard: In the existing technologies, the data formats, encodings, communication protocols, etc. of each manufacturer are different, resulting in difficulties in data access and management. This solution determines a unified standard for the classification of charging pile data types, data formats, encodings, and communication protocols, enabling the charging pile data of different manufacturers to be accessed into the Internet of Things platform in a consistent specification, improving the generality and compatibility of the data, and reducing the complexity of data processing. For example, the fields representing "charging status" of different manufacturers are uniformly mapped to "charging_status" and the encoding is standardized to facilitate the platform to uniformly process and manage the data.

[0043] Protocol parsing and conversion: In the face of multiple charging pile communication protocols, it is often difficult for existing technologies to effectively handle them. This solution integrates multiple protocol parsing modules in the Internet of Things platform, which can dynamically load the parsing modules according to the protocol type when the charging pile is accessed. At the same time, a protocol mapping table is established to convert different protocol data into a unified format to ensure that the platform can accurately obtain and process various charging pile data. For example, for protocol messages based on XML format or binary format, they can be accurately parsed and converted to achieve unified data access.

[0044] 2. Optimize the charging process

[0045] Standardize the charging process: The traditional charging process may vary due to the lack of a unified standard, affecting the user experience and operation management. This solution formulates unified charging start, stop, and billing processes, clarifies the triggering conditions and data interaction sequences of each link, and improves the standardization and stability of the charging process. For example, when charging starts, the interaction process between the user APP, the platform, and the charging pile is specified to ensure the orderly progress of charging.

[0046] Enhance the user experience: Considering factors such as the user's membership level, preferential treatment is given to senior members in the allocation of charging resources, which optimizes the user experience and is an aspect less concerned by existing technologies. In busy charging stations, senior members can obtain idle charging piles first, reducing waiting time.

[0047] 3. Enhance the multi-platform interaction ability

[0048] Standardized API interfaces: In the existing technologies, there may be problems such as inconsistent interfaces and difficult data sharing in the data interaction between charging piles and other platforms. This solution develops standardized API interfaces, clarifies the interface parameters, call frequency limits, and security authentication mechanisms, promotes the efficient data interaction and sharing between charging piles and power grid systems, payment systems, vehicle management systems, etc., and realizes the coordinated development of all links in the industrial chain. For example, for the interface to query the charging pile status, the input and output parameters, call frequency, and security authentication method are clearly defined to ensure the stability and security of data interaction.

[0049] 4. Strengthen data security and storage management

[0050] Data Security Assurance: There may be vulnerabilities in data security in the prior art. This solution uses the AES symmetric encryption algorithm to encrypt the transmitted data, combines digital certificates or pre-shared keys for device identity authentication, manages user permissions based on the Role-Based Access Control (RBAC) model, and has a regular data backup and recovery mechanism to comprehensively ensure data security. For example, during data transmission, the encrypted data is protected from leakage; through the RBAC model, the permissions of administrators and ordinary users are clearly defined to protect data security.

[0051] Efficient Data Storage: To address the problem of storing a large amount of charging pile data, this solution uses a distributed database (HBase) to store historical data, an in-memory database (Redis) to store real-time data, and a relational database (MySQL) to store metadata, etc. It selects the appropriate storage method according to the characteristics of the data to improve data storage and query efficiency. For example, HBase meets the requirements of high-concurrency writing and large-scale data storage, Redis enables real-time monitoring of the charging pile status, and MySQL facilitates complex queries and analysis. Description of the Drawings

[0052] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to actual scale.

[0053] Figure 1 It is a schematic flow diagram of a method for formulating a unified standard for charging pile data based on an Internet of Things platform;

[0054] Figure 2 It is a schematic structural diagram of a system for formulating a unified standard for charging pile data based on an Internet of Things platform. Detailed Embodiments

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0056] It should be understood that when used in this specification and the appended claims, the terms "comprises" and "comprising" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0057] It should also be understood that the terms used in the specification of the present invention are merely for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0058] It should be further understood that the term "and / or" used in the specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0059] Embodiment 1

[0060] As Figure 1 shown is a schematic flow diagram of a method for formulating a unified standard for charging pile data based on an Internet of Things platform, including the following steps:

[0061] S1: Integrate several charging pile communication protocol parsing modules in the Internet of Things platform, and dynamically load the corresponding protocol parsing module according to the protocol type used when the charging pile is connected.

[0062] Furthermore, the Internet of Things platform can build a unified data access layer, and the data access layer integrates protocol parsing modules for several charging pile communication protocols. Furthermore, several charging pile communication protocols include, for example, OCPP, GB / T27930, etc., and at the same time, an extension interface for custom protocols is reserved. When a new charging pile is connected, the corresponding protocol parsing module is dynamically loaded according to the protocol type used. Furthermore, the communication protocol parsing module can also develop corresponding parsing algorithms for the data message formats of different protocols. For example, for protocol messages based on XML format, an XML parser is used to extract key data fields; for binary format messages, parsing is performed according to the byte order and data type specified by the protocol.

[0063] Specifically, it includes the following steps:

[0064] S11: When the charging pile accesses the platform for data collection, the platform first obtains the communication protocol version information used by the charging pile through a specific handshake protocol. For example, for the OCPP protocol, the version number (such as OCPP 1.6, OCPP 2.0, etc.) is obtained during the handshake process.

[0065] S12: The platform dynamically loads the corresponding protocol parsing module according to the obtained protocol version number. For the data formats and instructions that are different in different versions of the protocol, special processing is performed in the parsing module. For example, OCPP 2.0 has added some new data fields and functions compared to OCPP1.6, and the parsing module can recognize and correctly process these differences (the parsing module has pre-stored the information requirements of each version).

[0066] S13: When the protocol is upgraded, the platform issues an upgrade notice in advance to inform the charging pile manufacturers and operators. During the upgrade process, the platform supports parallel processing of the old and new protocol versions, allowing some charging piles to use the old version protocol while gradually guiding them to upgrade to the new version protocol. For the charging piles using the old version protocol, the platform converts their data into a format compatible with the new version protocol through the protocol conversion layer to ensure normal data interaction.

[0067] S2: Determine a unified standard based on the parsed charging pile data.

[0068] Furthermore, the determination of the unified standard based on the parsed charging pile data includes determining unified standards for the charging pile data type classification, data format, data encoding, and communication protocol.

[0069] Furthermore, the data types include:

[0070] Real-time data: Clearly define data such as charging power, current, voltage, temperature, charging status (charging, idle, fault, etc.) as real-time data, and stipulate the collection frequency (e.g., once per second) and accuracy requirements (e.g., power accurate to 0.1 kW).

[0071] Non-real-time data: Determine charging power statistics, charging duration, user charging records, equipment maintenance records, etc. as non-real-time data, and set the collection frequency (e.g., once per hour). For example, for the charging power statistics in non-real-time data, the accuracy can be set to be accurate to 0.01 degrees. This means that when counting the charging power, it can accurately record up to two decimal places, such as a certain charging power record of 20.50 degrees, ensuring the accuracy of billing and data analysis.

[0072] Furthermore, the unification of the data format can be determined by the following steps:

[0073] S21: Evaluate the transmission rates of various data formats. Different data formats require different bandwidths and times during transmission. The transmission rate can be evaluated by calculating the amount of data transmitted per unit time. Let T be the transmission time (seconds), D be the amount of data transmitted (bits), then the transmission rate R is:

[0074]

[0075] The transmission tests can be respectively carried out on data in formats such as XML, CSV, Protocol Buffers, etc., record the transmission time and the amount of data, and calculate their respective transmission rates. Select the data format with a high transmission rate to reduce the transmission delay and improve the system response speed.

[0076] S22: Calculate the compression ratios of various data formats.

[0077] The data compression ratio can reflect the ability of a data format to save storage space and transmission bandwidth after compression. Let D_original be the size (in bits) of the original data, and D_compressed be the size (in bits) of the compressed data. Then the compression ratio C is:

[0078]

[0079] For different data formats, use the same compression algorithm (such as Gzip) to compress and calculate the compression ratio. The higher the compression ratio, the more advantageous the data format is in terms of compression and the more suitable it is for transmission in the case of limited bandwidth.

[0080] S23: Calculate the parsing time of various data formats. The data parsing time is an important indicator to measure the processing complexity of a data format. Let T parse be the time (in seconds) required to parse the data. By writing a test program, parse different formats of data multiple times, record the time of each parsing, and then take the average to obtain the average parsing time. Select the data format with a short parsing time to improve the data processing efficiency of the system.

[0081] S24: Evaluate the memory occupancy of various data formats. Different data formats occupy different amounts of memory space during parsing and processing. A memory analysis tool can be used to measure the memory occupancy of the system when parsing and processing different formats of data. Let M be the memory occupancy (in bytes). Select the data format with a small memory occupancy to reduce the memory overhead of the system and improve the stability of the system.

[0082] S25: Calculate the cost of adding new fields to various data formats. During the development of the system, it may be necessary to expand the data format and add new fields. Let C new be the cost of adding new fields, including the workload of modifying code, updating the database, etc. By evaluating the difficulty and required workload of adding new fields to different data formats, calculate the cost of adding new fields. Select the data format with a low cost of adding new fields to improve the scalability and flexibility of the system.

[0083] S26: Evaluate the compatibility of various data formats. The compatibility of data formats is also an important consideration. The compatibility can be evaluated by calculating the compatibility scores of different data formats with existing systems, third-party tools, and platforms. Let S compatibility be the compatibility score, with a value range of 0 - 100. The higher the score, the better the compatibility. Select the data format with good compatibility to reduce the difficulty and cost of system integration.

[0084] S27: Conduct a comprehensive evaluation of various data formats to determine the final standard format to be adopted. The calculation formula for the comprehensive evaluation is as follows:

[0085]

[0086] In the above formula, is the comprehensive score of the j-th data format; n is the number of indicators participating in the evaluation, which is 6 in this embodiment, namely transmission rate, data compression ratio, parsing time, memory occupancy, cost of new fields, and compatibility; is the weighted score of the basic indicator; W i is the weight of the i-th indicator, and is the evaluation calculation value of the j-th data format on the i-th indicator (the evaluation calculation results of steps S21 to S26); is to normalize the evaluation calculation value of the j-th data format on the i-th indicator to avoid the influence caused by different dimensions of different indicators; is the part of the interactive influence of indicators; m is the number of pairs of indicators with mutual influence among the n indicators of the j-th data format, that is, the number of indicator interaction pairs; A k is the influence coefficient of the k-th indicator interaction pair among the m indicator interaction pairs; represents the interaction between the i-th indicator and the l-th indicator that make up the k-th indicator interaction pair. For example, there may be an interaction relationship between the transmission rate and the data compression ratio. If the data compression ratio is high, it may improve the transmission rate to a certain extent; is the evaluation calculation value of the i-th indicator in the k-th indicator interaction pair, is the evaluation calculation value of the l-th indicator in the k-th indicator interaction pair; P j is the penalty term; R j is the reward term.

[0087] Furthermore, the data formats include XML, binary format, XML, CSV, Protocol Buffers, JSON, and so on.

[0088] Furthermore, the interaction can be determined by calculating the correlation coefficient of two indicators or setting an interaction function according to actual experience. Assuming a linear interaction function is used for calculation, the formula is as follows:

[0089]

[0090] Among them, is the k correlation coefficient between the i-th k indicator and the l-th indicator; Perform normalization processing; For Perform normalization processing.

[0091] Furthermore, the normalization formula can adopt linear normalization:

[0092]

[0093] where, min(X i ) and max(X i ) are respectively the minimum and maximum values of all n data formats on the i-th index.

[0094] Furthermore, the penalty term is used to deduct points for some data formats that do not meet the requirements or have defects. For example, if a certain data format has serious vulnerabilities in terms of security, or has extremely poor compatibility with some key systems, corresponding penalty terms can be set. The calculation of the penalty term is as follows:

[0095]

[0096] In the above formula, q is the number of penalty factors; B s is the weight of the s-th penalty factor; is the score of the j-th data format on the s-th penalty factor, and the value range can be set according to the actual situation, for example, [0, 1].

[0097] Furthermore, the reward term is used to add points to some data formats with outstanding advantages. For example, if a certain data format has good open standards, or has great potential in terms of future expandability, corresponding reward terms can be set. The calculation of the reward term can be set according to the specific situation, and the calculation formula is as follows:

[0098]

[0099] In the above formula, r is the number of reward factors; C t is the weight of the t-th reward factor; is the score of the j-th data format on the t-th reward factor, and the value range can be set according to the actual situation, for example, [0, 1].

[0100] Correlation analysis based on historical data: If there is a large amount of historical data on the performance of different data formats on various indicators, the influence coefficient can be determined by calculating the correlation coefficient between the indicators. Taking the pair of indicators of transmission rate and data compression ratio as an example, first collect the transmission rate R and data compression ratio C data of multiple data formats in different scenarios, and then use the Pearson correlation coefficient formula to calculate their correlation:

[0101]

[0102] where p is the number of data samples, and R i , C i are the transmission rate and data compression ratio of the i-th sample respectively, is the average value of the transmission rate and data compression ratio. The absolute value of the correlation coefficient reflects the degree of linear correlation between these two metrics. By appropriately scaling and adjusting to make it fall within the value range of the influence coefficient (such as [0, 1]), it can be used as the influence coefficient A of this pair of metric interactions k . If can be set to 0.4 after adjustment (assuming the adjustment rule is k ). )

[0103] Furthermore, common pairs of metric interactions are listed as follows:

[0104] Interaction pairs related to transmission efficiency

[0105] Transmission rate and data compression ratio: The higher the data compression ratio, the smaller the bandwidth occupied by the data during transmission, which may increase the transmission rate. A high compression ratio reduces the amount of data. When the network bandwidth is limited, the transmission time is shortened, improving the transmission rate. If a format with good compression performance is used, the time taken to transmit the same amount of data is shorter.

[0106] Transmission rate and compatibility: Data formats with good compatibility can better adapt to network devices and transmission protocols, affecting the transmission rate. If the data format has good compatibility with network devices and transmission protocols, the packet loss rate during transmission is low, the number of retransmissions is small, and the transmission rate is high.

[0107] Interaction pairs related to processing complexity

[0108] Parsing time and memory occupancy: For data formats with short parsing times, memory management during parsing may be more efficient, and the memory occupancy is also less. An efficient parsing algorithm does not require a large amount of temporary memory to store intermediate data when quickly parsing data, saving memory.

[0109] Parsing time and cost of adding new fields: If the data format is simple to parse, the changes to the parsing logic when adding new fields are small, and the cost of adding new fields is low. For a simple parsing format, adding new fields does not require significant modification of the parsing code, reducing development and maintenance costs.

[0110] Interaction pairs related to scalability

[0111] New field cost and compatibility: Data formats with low new field costs are more flexible and have better compatibility when interacting with other systems. When the data structure needs to be adjusted during interaction with other systems, formats with low new field costs can quickly adapt, reducing the difficulty of system integration.

[0112] Compatibility and data compression ratio: Data formats with good compatibility are more flexible when choosing compression algorithms and may increase the data compression ratio. Good compatibility means being able to adapt to multiple compression algorithms, selecting more efficient compression algorithms to increase the compression ratio, saving transmission bandwidth and storage costs.

[0113] Through this complex comprehensive evaluation formula, the advantages and disadvantages of different data formats can be evaluated more comprehensively and meticulously, so as to select the data format that is most suitable as the standard format for data transmission and storage. This implementation takes the adoption of the JSON data protocol as the standard format for data transmission and storage as an example.

[0114] Furthermore, the encoding can be unified using UTF-8 encoding to ensure accurate transmission and display of data between different systems and devices. By adopting unified naming and encoding of data fields, different manufacturers may use different names and encoding methods for the same data item. Therefore, a mapping table needs to be established in the Internet of Things platform to convert it into a unified standard name and encoding. For example, fields representing "charging status" from different manufacturers are uniformly mapped to "charging_status", and their encoding is unified into standard status codes (such as 0 for idle, 1 for charging, 2 for fault, etc.).

[0115] Furthermore, when determining a unified standard for the communication protocol, the following steps are included:

[0116] Select the MQTT protocol for real-time data. It features low latency, high reliability, and supports the publish / subscribe mode. For example, the charging pile, as the client, publishes real-time data to a specified topic, and the Internet of Things platform, as the subscriber, receives the data.

[0117] For non-real-time data, use the HTTP / HTTPS protocol. It can stably transmit even when the data volume is large and is convenient for integration with the existing network architecture.

[0118] S3: Establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table.

[0119] Specifically, it includes the following steps:

[0120] S31: Mapping table construction, analyzing the data structure and field meaning of different charging pile protocols (such as GB / T 27930 standard format, XML), and corresponding one-to-one with the data fields of the unified JSON data protocol to establish a mapping relationship. For example, the "charging current" field in a manufacturer's charging pile protocol is mapped to the "current" field in the unified protocol. For another example, taking the "charging mode" field in a manufacturer's charging pile protocol as an example, this field is represented by a digital code in its protocol, such as "01" for fast charging and "02" for slow charging. In the unified protocol, it is mapped to "charging_mode", and it is stipulated that "fast" means fast charging and "slow" means slow charging. Establish the mapping relationship of "01-fast" and "02-slow" in the mapping table.

[0121] S32: Data conversion. After receiving the data, the platform replaces and converts the data fields according to the mapping table, and converts the data of different data protocols into the format of the unified JSON data protocol.

[0122] S33: Dynamic update. With the emergence of new charging pile protocols or the update of existing protocols, the protocol mapping table is updated and maintained in a timely manner to ensure the accuracy of data conversion. For example, when a charging pile manufacturer launches a new protocol version and adds a "battery health" field, the IoT platform needs to add the mapping relationship of this field in the mapping table. Assuming that the "battery health" in the new protocol is expressed as a percentage integer and is mapped to "battery_health" in the unified protocol, the new mapping rules are recorded in the mapping table to ensure that the new data can be converted correctly.

[0123] S4: Clean, extract features and store the converted data.

[0124] The cleaning includes: removing invalid characters, duplicate data and obvious erroneous data. For example, if the charging power data has a negative value and does not conform to the actual situation, it is marked as invalid data and removed. Correcting erroneous data and filling missing values. For example, for missing temperature data, the average value of historical data can be used to fill it.

[0125] The storage includes: using a distributed database (such as HBase) to store massive amounts of historical data to cope with high concurrent writing and large-scale data storage requirements. Using an in-memory database (such as Redis) to store real-time data for fast query and processing, and to achieve real-time monitoring of the status of charging piles. Relational databases (such as MySQL) are used to store metadata, configuration information, and statistical data to facilitate complex queries and analysis.

[0126] S5: Establish unified standards for charging processes and multi-platform data interaction processes.

[0127] Furthermore, the charging process includes a charging start process, a charging stop process, and a billing process.

[0128] 1. Charging start process

[0129] The Internet of Things platform formulates unified charging start trigger conditions, such as when the user initiates a charging request through the APP, and at the same time the charging pile detects that the vehicle is normally connected and has charging conditions.

[0130] Specify the data interaction sequence: The user APP sends a charging request to the platform, including vehicle information, charging mode, etc.; after the platform verifies the legitimacy of the request, it issues a charging start instruction to the charging pile; after receiving the instruction, the charging pile conducts necessary safety inspections. If the inspection passes, it starts charging and feeds back the charging start status to the platform.

[0131] For example, when the user APP sends a charging request to the platform, in addition to vehicle information and charging mode, it also carries the user membership level information. When the platform verifies the legitimacy of the request, if the user is a premium member, charging resources can be preferentially allocated. For example, at a busy charging station, when multiple charging requests are detected, the platform preferentially allocates idle charging piles to premium members to improve the user experience.

[0132] 2. Charging stop process

[0133] Clarify the charging stop trigger conditions, including the user actively stopping, charging completion, and abnormal situations (such as overcurrent, overvoltage, etc.).

[0134] Standardize the data interaction sequence: When the charging stop condition is triggered, the charging pile first stops the charging operation, and then reports the charging stop status and related data (such as charging power, charging duration, etc.) to the platform; after receiving the information, the platform updates the user account information and the charging pile status, and pushes a charging stop notice to the user APP.

[0135] 3. Billing process

[0136] Formulate unified billing rules, and calculate the fees based on factors such as charging power, charging duration, and electricity price.

[0137] Specify the interaction process of billing data: The charging pile collects charging power and duration data in real time during charging and reports them to the platform regularly; the platform calculates the fees based on the received data and the preset billing rules, and feeds back the final fee information to the user APP and the payment system after charging ends.

[0138] Furthermore, the multi-platform data interaction process includes developing standardized API interfaces to support data interaction and sharing with other relevant platforms (such as the power grid system, payment system, vehicle management system). Through the interfaces, data synchronization and update are realized to promote the coordinated development of all links in the industrial chain. Specifically, it includes:

[0139] Define the input and output parameters for each API interface. For example, for the interface to query the status of a charging pile, the input parameters include the charging pile number, query time range, etc.; the output parameters include the real-time status of the charging pile (such as charging, idle, faulty, etc.), charging power, remaining power, etc. Provide a detailed description of the type, value range, and whether it is required for each parameter. For example, the type of the charging pile number parameter is a string, the value range is a specific number format, and it is a required parameter. To ensure the stability and security of the system, set a call frequency limit for each API interface. For example, the call frequency limit for the interface to query the status of a charging pile is no more than 10 times per minute. When the call frequency exceeds the limit, the system returns an error message, prompting the user to try again later. Use the OAuth 2.0 authentication mechanism to authenticate the API interface. The platform or application that calls the interface needs to first obtain an access token and send the access token as part of the request header to the platform each time the interface is called. The platform verifies the access token, and only requests that pass the verification can be processed.

[0140] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0141] 1. Unified data management

[0142] Unified data standards: In the prior art, the data formats, encodings, communication protocols, etc. of each manufacturer are different, resulting in difficulties in data access and management. This solution determines unified standards for the charging pile data type division, data format, encoding, and communication protocol, enabling the charging pile data of different manufacturers to be accessed to the Internet of Things platform in a consistent specification, improving the universality and compatibility of the data, and reducing the complexity of data processing. For example, the fields representing "charging status" of different manufacturers are uniformly mapped to "charging_status" and the encoding is standardized to facilitate the platform to uniformly process and manage the data.

[0143] Protocol parsing and conversion: Facing multiple charging pile communication protocols, it is often difficult to effectively process in the prior art. This solution integrates multiple protocol parsing modules in the Internet of Things platform, can dynamically load the parsing module according to the protocol type when the charging pile is accessed, and at the same time establishes a protocol mapping table to convert different protocol data into a unified format to ensure that the platform accurately obtains and processes various types of charging pile data. For example, for protocol messages based on XML format or binary format, they can be accurately parsed and converted to achieve unified data access.

[0144] 2. Optimize the charging process

[0145] Standardize the charging process: Traditional charging processes may vary due to the lack of a unified standard, affecting user experience and operation management. This solution formulates unified charging start, stop, and billing processes, clarifies the triggering conditions and data interaction sequences for each link, and improves the standardization and stability of the charging process. For example, when starting charging, it stipulates the interaction process among the user APP, the platform, and the charging pile to ensure the orderly progress of charging.

[0146] Enhance user experience: Considering factors such as user membership levels, this solution gives preferential treatment to premium members in the allocation of charging resources, optimizing the user experience, which is an aspect less concerned by existing technologies. At busy charging stations, premium members can obtain idle charging piles first, reducing waiting time.

[0147] 3. Enhance multi-platform interaction capabilities

[0148] Standardize API interfaces: In existing technologies, data interaction between charging piles and other platforms may have problems such as inconsistent interfaces and difficulties in data sharing. This solution develops standardized API interfaces, clarifies interface parameters, call frequency limits, and security authentication mechanisms, promotes efficient data interaction and sharing between charging piles and power grid systems, payment systems, vehicle management systems, etc., and realizes the coordinated development of all links in the industrial chain. For example, for the interface to query the status of charging piles, the input and output parameters, call frequency, and security authentication methods are clearly defined to ensure the stability and security of data interaction.

[0149] 4. Strengthen data security and storage management

[0150] Data security guarantee: There may be vulnerabilities in data security in existing technologies. This solution uses the AES symmetric encryption algorithm to encrypt transmitted data, combines digital certificates or pre-shared keys for device identity authentication, manages user permissions based on the role-based access control (RBAC) model, and has a regular data backup and recovery mechanism to comprehensively guarantee data security. For example, during data transmission, the data is encrypted to prevent leakage; through the RBAC model, the permissions of administrators and ordinary users are clearly defined to protect data security.

[0151] Efficient data storage: To address the storage challenges of a large amount of charging pile data, this solution uses a distributed database (HBase) to store historical data, an in-memory database (Redis) to store real-time data, a relational database (MySQL) to store metadata, etc., selects appropriate storage methods according to the characteristics of the data, and improves data storage and query efficiency. For example, HBase meets the requirements of high-concurrency writing and large-scale data storage, Redis enables real-time monitoring of the status of charging piles, and MySQL is convenient for complex queries and analysis.

[0152] Meanwhile, the unified standard for data format is determined by a calculation method, covering various aspects of evaluation and calculation such as data format, transmission rate, compression ratio, etc., bringing significant advantages to the charging pile data management and enhancing the scientificity, accuracy, adaptability, and efficiency of the system.

[0153] 1. Ensure comprehensiveness and scientificity: By determining the data format standard through a calculation method, various factors can be comprehensively considered, avoiding the limitations of single-factor decision-making. When evaluating the data format, multiple indicators such as transmission rate, compression ratio, parsing time, memory occupancy, cost of adding new fields, and compatibility are calculated and evaluated to ensure that the selected data format performs well in all key aspects, making the determined data standard more scientific. Taking the selection of data format as an example, if only the transmission rate is used to select the format, the disadvantages in parsing time or memory occupancy may be ignored, while comprehensive calculation and evaluation can avoid such problems and enable the selected data format to develop in a balanced manner in multiple aspects.

[0154] Improve accuracy and objectivity: The calculation process is based on specific data and formulas, reducing the interference of human subjective factors and making the determination of data standards more accurate and objective. When calculating indicators such as transmission rate and compression ratio, the results are obtained based on actual test data and strict calculation formulas. These quantified data provide a solid basis for decision-making. Compared with subjective judgment, the calculation method can more accurately reflect the performance of the data format in actual applications, thus determining a data standard that better meets the actual needs.

[0155] Adapt to the dynamic changes of the system: Using a calculation method to determine the data format standard facilitates flexible adjustment according to the actual situation. When new data formats appear, network environments change, or business requirements change in the system, the indicators can be recalculated, the weights adjusted, and then the data standard updated. When a new data format appears, its various indicators are calculated and evaluated, and compared with the existing data formats. If the new format has a higher comprehensive score, it can be included in the standard scope, enabling the data standard to adapt to the dynamic development of the system and maintain the best performance.

[0156] Improve the overall performance of the system: Precise calculation helps to select the optimal data standard, thereby improving the performance of the entire charging pile data management system. Selecting a data format with a high transmission rate, good compression ratio, and short parsing time can accelerate data transmission and processing speed, reduce memory occupancy, and improve the operation efficiency and stability of the system. During data storage and transmission, an efficient data format can reduce the occupancy of storage space, enhance the timeliness of data transmission, enabling the system to respond to user requests and process business more quickly, improving the user experience and operation efficiency.

[0157] Example 2

[0158] Such as Figure 2The figure shows a schematic structural diagram of a charging pile data unified standard formulation system based on an Internet of Things platform, which is applied to the above-mentioned method for formulating a unified standard for charging pile data based on an Internet of Things platform, including:

[0159] A data access layer, which is used to integrate several charging pile communication protocol parsing modules in the Internet of Things platform, and dynamically load the corresponding protocol parsing module according to the protocol type used when the charging pile is connected;

[0160] A standard layer, which is used to determine a unified standard according to the parsed charging pile data;

[0161] A mapping layer, which is used to establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table;

[0162] A processing layer, which is used to clean, extract features and store the converted data;

[0163] An interaction layer, which is used to formulate unified standards for the charging process and the multi-platform data interaction process.

[0164] Embodiment III

[0165] A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored program, wherein when the program runs, it controls the device where the computer-readable storage medium is located to execute the above-mentioned method for formulating a unified standard for charging pile data based on an Internet of Things platform.

[0166] Embodiment IV

[0167] A processor, the processor is used to run a program, wherein when the program runs, it executes the above-mentioned method for formulating a unified standard for charging pile data based on an Internet of Things platform.

[0168] This application provides a method for formulating a unified standard for charging pile data based on an Internet of Things platform, including: S1: Integrate several charging pile communication protocol parsing modules in the Internet of Things platform, and dynamically load the corresponding protocol parsing module according to the protocol type used when the charging pile is connected; S2: Determine a unified standard according to the parsed charging pile data; S3: Establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table; S4: Clean, extract features and store the converted data; S5: Formulate unified standards for the charging process and the multi-platform data interaction process. It can enable the charging pile data of different manufacturers to be connected to the Internet of Things platform in a consistent specification, improve the universality and compatibility of data, and reduce the complexity of data processing.

[0169] Those of ordinary skill in the art can realize that the units of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0170] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0171] In addition, the functional units in each embodiment of the present invention can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0172] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of each embodiment of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A method for formulating unified standards for charging pile data based on the Internet of Things platform, characterized in that: include: S1: Integrate several charging pile communication protocol parsing modules in the IoT platform. When a charging pile is connected, the corresponding protocol parsing module is dynamically loaded according to the protocol type used. S2: Determine a unified standard based on the analyzed charging pile data; S3: Establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table; S4: Clean, extract features and store the converted data; S5: Establish unified standards for charging processes and multi-platform data interaction processes.

2. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 1 is characterized in that: Determining a unified standard based on the parsed charging pile data includes determining a unified standard for charging pile data type classification, data format, data encoding and communication protocol.

3. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 2 is characterized in that: The determination of the unified data format standard includes the following steps: Evaluate and calculate the transmission rate, compression ratio, parsing time, memory usage, new field cost, and compatibility of various data formats; A comprehensive evaluation is conducted on various data formats. The comprehensive evaluation formula is as follows: In the above formula, is the comprehensive score of the jth data format; n is the number of indicators involved in the evaluation; is the weighted score of the basic indicators; i is the weight of the ith indicator, and Calculate the evaluation value of the j-th data format on the i-th indicator; To normalize the evaluation calculation value of the j-th data format on the i-th indicator; is the interactive influence part of the indicators; m is the number of pairs of indicators that have mutual influence among the n indicators in the jth data format, that is, the number of indicator interaction pairs; A k is the influence coefficient of the kth indicator interaction pair among the m indicator interaction pairs; represents the interaction between the ith indicator and the lth indicator that constitute the kth indicator interaction pair, is the evaluation value of the i-th indicator in the k-th indicator interaction pair, is the evaluation value of the lth indicator in the kth indicator interaction pair; P j is the penalty term; R j For reward items.

4. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 3 is characterized in that: The calculation formula of the interaction is as follows: in, is the i k The first indicator and the k The correlation coefficient between the indicators; For Perform normalization processing; For Perform normalization.

5. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 4 is characterized in that: The correlation coefficient The calculation formula is as follows: Where p is the number of data samples, R i , C i are the transmission rate and data compression ratio of the i-th sample, respectively. It is the average value of transmission rate and data compression ratio.

6. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 3 is characterized in that: Penalty term P j The calculation formula is as follows: In the above formula, q is the number of penalty factors; B s is the weight of the sth penalty factor; is the score of the j-th data format on the s-th penalty factor.

7. The method for formulating unified standards for charging pile data based on the Internet of Things platform according to claim 3 is characterized in that: The reward item R j The calculation formula is as follows: In the above formula, r is the number of reward factors; C t is the weight of the tth reward factor; is the score of the j-th data format on the t-th reward factor.

8. A charging pile data unified standard formulation system based on the Internet of Things platform, characterized in that: The method for formulating a unified standard for charging pile data based on an Internet of Things platform as described in any one of claims 1 to 7 comprises: The data access layer is used to integrate several charging pile communication protocol analysis modules in the IoT platform. When a charging pile is connected, the corresponding protocol analysis module is dynamically loaded according to the protocol type used by the charging pile. The standard layer is used to determine a unified standard based on the parsed charging pile data; A mapping layer, which is used to establish a protocol mapping table according to the determined unified standard, record the data field mapping relationship between the data of different charging piles and the unified standard, and perform data conversion on the received charging pile data according to the mapping table; The processing layer is used to clean, extract features and store the transformed data; The interaction layer is used to establish unified standards for the charging process and multi-platform data interaction process.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the method for formulating unified standards for charging pile data based on the Internet of Things platform as described in any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein when the program is running, the method for formulating a unified standard for charging pile data based on an Internet of Things platform as described in any one of claims 1 to 7 is executed.

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