New energy vehicle data access method supporting multiple types and multiple modes

Abstract

The present invention relates to the technical field of vehicle data access methods. Disclosed is a new energy vehicle data access method supporting multiple types and multiple modes, the method comprising the following steps: vehicle model classification and VIN parsing rule establishment, involving: analyzing vehicle model features of different new energy vehicles, extracting from VINs key information related to vehicle models, establishing a VIN parsing rule base, and distinguishing different vehicle models according to rules. The present invention can comprehensively support data access requirements of multiple types and multiple modes, effectively solve the problems in the prior art caused by the incompatibility of data formats, differences in communication protocols, and diversity of data acquisition modes, ensure seamless compatible access of data of different formats and different sources, and support multiple data transmission modes such as an active mode and a passive mode, thereby meeting diversified requirements of different platforms for new energy vehicle data, significantly improving the efficiency, accuracy and security of data access, and providing solid technical support for data management and application of the new energy vehicle industry.

Description

A method for accessing new energy vehicle data that supports multiple types and modes Technical Field

[0001] This invention relates to the field of vehicle data access methods, and more particularly to a method for accessing data from new energy vehicles that supports multiple types and modes. Background Technology

[0002] With the rapid development of new energy vehicle technology and the continuous improvement of vehicle intelligence, the amount of data generated by vehicles is experiencing explosive growth, and the types of data are becoming increasingly complex. Static vehicle data, such as vehicle model, vehicle identification number (VIN), and on-board terminal number, provides the basis for vehicle identification and basic information management. Dynamic vehicle data, encompassing numerous parameters such as vehicle speed, battery level, motor speed, and fault information, is crucial for real-time monitoring of vehicle operating status, performance evaluation, fault diagnosis, and the realization of intelligent driving functions. The access modes for new energy vehicle data are significantly diverse. Direct data transmission from the on-board terminal is a common method, enabling rapid data transmission and allowing enterprises or monitoring platforms to obtain vehicle operating information promptly. In addition, third-party platforms play an important role in data access, acting as data forwarders, relaying data from on-board terminals to other platforms, or as data providers, allowing enterprises to obtain the necessary data from third-party platforms. This multi-mode data access environment, while bringing greater flexibility to data management, also increases the complexity and difficulty of data access.

[0003] However, the following problems still exist:

[0004] Data format and communication protocol are incompatible:

[0005] Although the national standard GB / T 32960-2016, the Technical Specification for Remote Service and Management Systems for Electric Vehicles, only applies to vehicle monitoring data specified in the national standard. Its format and transmission frequency are strictly standardized and cannot be arbitrarily changed. However, in actual operation, automakers often need to collect and transmit a large amount of custom data. This forces companies to develop separate communication protocols and methods for this custom data, resulting in a lack of compatibility between data formats and communication protocols. During the data access process, data with different formats and protocols is prone to problems such as data parsing errors, transmission delays, and even data loss, seriously affecting the accuracy and integrity of data processing.

[0006] Challenges arising from differences in data acquisition patterns:

[0007] Because vehicle data comes from diverse sources and acquires data in various ways—such as monitoring platforms actively consuming data from third-party platforms or receiving data forwarded from third-party platforms—existing technologies cannot quickly and efficiently achieve data transmission between platforms when enterprises face data access scenarios involving multiple vehicle models and different data acquisition methods. The lack of a unified access method and management mechanism makes the data access process cumbersome and inefficient, failing to meet the real-time and accuracy requirements of new energy vehicle data, and hindering the effective utilization of new energy vehicle data and the further development of the industry.

[0008] To address the aforementioned issues, this application proposes a method for accessing new energy vehicle data that supports multiple types and modes. Summary of the Invention

[0009] (a) Purpose of the invention

[0010] To address the technical problems existing in the background art, this invention proposes a data access method for new energy vehicles that supports multiple types and modes. This invention can comprehensively support multiple types and modes of data access needs, effectively solving the problems caused by incompatible data formats, differences in communication protocols, and diverse data acquisition modes in the prior art. It ensures seamless compatibility access of data from different formats and sources, and supports multiple data transmission modes such as active and passive transmission to meet the diverse needs of different platforms for new energy vehicle data. This significantly improves the efficiency, accuracy, and security of data access, providing solid technical support for data management and application in the new energy vehicle industry.

[0011] (II) Technical Solution

[0012] To address the above problems, this invention provides a method for accessing data from new energy vehicles that supports multiple types and modes, characterized by comprising the following steps:

[0013] Vehicle model classification and VIN code parsing rules establishment:

[0014] Analyze the characteristics of different new energy vehicle models, extract key information related to the model from the VIN code, establish a VIN code parsing rule base, and distinguish different models according to the rules;

[0015] It supports regular updates to the VIN code parsing rule base to adapt to the emergence of new car models and changes in existing car model rules.

[0016] Data type association:

[0017] For each vehicle model, we sort out the national standard data and the vehicle manufacturer's custom data that need to be accessed, establish a mapping relationship between vehicle models and data types, classify and label national standard data according to standards, and define custom data in detail.

[0018] Data format specifications:

[0019] Analyze each data format, record data packet characteristics and format specification information, clarify the header identifier, packet tail check code rules, data length field position, and standardize field definitions, encoding methods, and data arrangement order;

[0020] Data access mode and protocol configuration:

[0021] Configure access mode options for vehicle models, such as direct connection to vehicle terminal, forwarding to third-party platform, and data acquisition from third-party platform. Record the access IP address and port number for direct connection to vehicle terminal, the API interface address for forwarding to third-party platform, and the interface address and acquisition method for data acquisition from third-party platform. For data interface protocols such as TCP, HTTP, and MQTT, set TCP connection timeout, HTTP request header format specifications, and MQTT topic subscription rules. Associate and store vehicle model, access mode, and protocol configuration information to form a configuration scheme.

[0022] Security settings:

[0023] Select encryption algorithms or keys for different vehicle models to encrypt transmitted data, configure identity authentication information for inter-platform access, including username, password, and digital certificate, and configure a whitelist of allowed IP addresses for third-party platforms.

[0024] Preferably, in the establishment of vehicle model classification and VIN code parsing rules, the VIN code parsing rule base is established based on the vehicle manufacturer, model series, and production year information to formulate differentiation rules.

[0025] Preferably, in the data type association, the definition specification of the automaker's custom data format includes the field meaning, data type, and data range content of the custom data.

[0026] Preferably, in the data access mode and protocol configuration, for the third-party platform forwarding mode, the data forwarding frequency and data caching strategy parameters of the third-party platform are also recorded.

[0027] Preferably, in the data access mode and protocol configuration steps, when setting MQTT protocol configuration parameters, the steps also include setting parameters such as MQTT message quality level and message retention policy.

[0028] Preferably, in the security settings, the encryption algorithm includes symmetric encryption algorithms such as AES and asymmetric encryption algorithms such as RSA, which are selected according to the importance and security requirements of the data.

[0029] Preferably, in the security settings, the digital certificate adopts the X.509 standard format and includes the certificate version, certificate serial number, signature algorithm identifier, issuer name, validity period, subject public key information, etc.

[0030] Preferably, in the data format specification step, the determination of the position of the data length field is carried out by either using a fixed position or by calculating it through a specific identifier, depending on the data format.

[0031] Preferably, in the data access mode and protocol configuration steps, when obtaining data from a third-party platform, different data acquisition timing methods such as timed acquisition and event-triggered acquisition are supported.

[0032] Preferably, the method also includes a data verification step. After the data is received, the integrity and accuracy of the data are verified according to the data format specifications and verification algorithm. If the verification fails, the data is retransmitted or an error message is displayed.

[0033] The above-described technical solution of the present invention has the following beneficial technical effects:

[0034] By integrating multiple key technologies such as VIN code parsing, data type association, data format standardization, access mode and protocol configuration, security settings, and data verification, the system achieves full automation and intelligence from data acquisition and processing to final access. In particular, the combination of VIN code parsing and data type association accurately identifies and classifies data from different vehicle models, ensuring data accuracy and integrity. Simultaneously, through multiple access modes and protocol configurations, it can flexibly adapt to different data sources and application scenarios, improving system compatibility and flexibility. Furthermore, comprehensive security measures and data verification mechanisms guarantee the security and reliability of data transmission, providing strong technical support for data management and application in new energy vehicles. Attached Figure Description

[0035] Figure 1 is a schematic diagram of the structure of a new energy vehicle data access method that supports multiple types and modes proposed in this invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments and the accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of the invention. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.

[0037] As shown in Figure 1, the present invention proposes a method for accessing data from new energy vehicles that supports multiple types and modes, characterized by comprising the following steps:

[0038] Vehicle Classification and VIN Code Parsing Rules Establishment

[0039] This study delves into the technical characteristics and configuration differences of various new energy vehicle models. Through in-depth analysis of a large number of vehicle VIN code samples, it accurately extracts key information closely related to the vehicle model, such as the manufacturer's unique code identifier, the specific character sequence of the model series, and the coding rules for the production year. Based on this key information, a comprehensive, detailed, and highly accurate VIN code parsing rule base is constructed. Within this rule base, a dedicated VIN code parsing rule is developed for each vehicle model, ensuring that the model can be quickly and accurately identified based on the vehicle's VIN code. For example, for a well-known new energy vehicle brand, the first three characters of its VIN code always represent the manufacturer, while the 4th to 6th characters clearly correspond to the model series. Through this precise mapping relationship, when a vehicle's VIN code is received, the brand and specific model can be accurately determined in a very short time.

[0040] To ensure the timeliness and accuracy of the VIN code parsing rule base, a regular update mechanism has been established. We closely monitor the dynamic development of the automotive industry and promptly collect relevant information on new vehicle models, including new VIN code encoding rules and changes in vehicle characteristics. Whenever a new model is launched or existing model rules are adjusted, the rule base update process is quickly initiated to incorporate the new parsing rules into the database, ensuring that the data access method always adapts to market changes and accurately identifies various new energy vehicle models.

[0041] Data type association

[0042] For each vehicle model that has been precisely categorized, the system systematically analyzes all types of data that need to be accessed throughout its entire lifecycle. For data regulated by national standards, the system strictly adheres to relevant standards and specifications, meticulously classifying, organizing, and precisely labeling the data. For data formats customized by vehicle manufacturers, the system collaborates closely with the manufacturer's R&D, engineering, and data management teams to deeply explore the business logic and application requirements behind the data, developing detailed definition specifications. These specifications cover the meaning of each field in the customized data, ensuring clarity, ease of understanding, and a clear business focus; they clearly define data types, selecting the most appropriate type representation based on the actual nature of the data, such as integer, floating-point, string, boolean, date, array, and structure types; and they strictly define the data range, specifying the upper and lower limits of each field's value to ensure the data's rationality and validity. In this way, a clear, accurate, and comprehensive mapping relationship is established between vehicle models and data types, ensuring that the data processing system can accurately identify and properly handle each data type during data access, effectively avoiding data confusion and erroneous processing.

[0043] Data format specifications

[0044] Each data format is analyzed in depth, and its data packet characteristics and format specifications are fully recorded. Regarding data packet characteristics, the specific format and content of the packet header identifier are clearly defined to ensure its uniqueness and easy identification. For example, a specific byte sequence (such as "0x55AA") or character combination (such as "##START##") is used as the starting marker, followed by key information such as the data packet type identifier and data length. The packet tail checksum rules are precisely determined. Based on the importance of the data and the accuracy requirements, appropriate checksum algorithms are selected, such as CRC-16, CRC-32, MD5, and SHA-1, and the position and length of the checksum in the data packet are clearly defined. For determining the position of the data length field, the diversity of data formats is fully considered. Depending on the characteristics of different data formats, a fixed position (such as bytes 3-6 of the data packet representing the length of the data portion) or calculation based on specific flag bits (such as calculating the data length based on certain flag bits in the packet header) is flexibly adopted. At the same time, the field definitions, encoding methods, and data arrangement order are meticulously standardized to ensure a high degree of consistency and compatibility when data is transmitted and processed across different systems.

[0045] Data access mode and protocol configuration

[0046] To meet the needs of different application scenarios and data sources, a variety of data access mode options are carefully configured for each vehicle model, including direct connection to the vehicle terminal, forwarding to a third-party platform, and acquisition from a third-party platform. For the direct connection mode, the access IP address and port number between the vehicle terminal and the enterprise monitoring platform are accurately recorded, along with network parameters such as subnet mask and gateway, ensuring stable and efficient data transmission from the vehicle terminal to the target platform. In the third-party platform forwarding mode, the API interface address, data forwarding frequency (e.g., once per minute, once every 5 minutes), data caching strategy (e.g., cache duration, cache size), and related interface parameters of the third-party platform are recorded in detail to ensure data can be successfully forwarded through the third-party platform according to predetermined rules. For the data acquisition mode from a third-party platform, the data acquisition interface address, data acquisition method (supporting different timing methods such as scheduled acquisition and event-triggered acquisition, such as acquiring the previous day's statistical data at 2 AM every day or immediately pushing fault data when the third-party platform detects a vehicle fault), and necessary authentication information are clearly defined.

[0047] For different data connection protocols (TCP, HTTP, MQTT, etc.), we conduct in-depth research on their respective characteristics, advantages, and applicable scenarios, and carefully set detailed protocol configuration parameters according to actual needs. For the TCP protocol, we reasonably set the connection timeout (e.g., 30 seconds), and adjust parameters such as the TCP buffer size (e.g., set the receive buffer and send buffer sizes to 8KB and 16KB respectively) and sliding window size (e.g., set to 64KB) according to the network environment and data transmission characteristics to optimize data transmission performance, establish a TCP connection pool, improve connection reuse rate, and reduce the overhead of connection establishment and closure. For the HTTP protocol, strictly standardize the request header format, including fields such as Content-Type (set to application / json, application / xml, etc. according to the data format), Authorization (use Bearer Token or Basic Auth for authentication), User-Agent (set to information such as the name and version number of the enterprise monitoring platform), and Accept (specify the acceptable response data format). Based on the requirements of third-party platforms and data security needs, reasonably set request header parameters to ensure the legitimacy and security of HTTP requests. Simultaneously, configure parameters such as the HTTP connection timeout (e.g., 10 seconds) and the maximum number of connections (e.g., 100 concurrent connections) to optimize HTTP communication performance. Regarding MQTT protocol configuration, set topic subscription rules, determining the topic name and wildcard rules based on data type and business needs. For example, subscribing to the "vehicle / data / #" topic means receiving all vehicle data-related topic messages; subscribing to the "vehicle / data / {vin} / battery" topic means only receiving battery data-related messages for a specific vehicle (VIN code {vin}). Simultaneously, parameters such as MQTT message quality level (e.g., QoS 0 means at most one transmission, suitable for scenarios with low data reliability requirements; QoS 1 means at least one transmission, ensuring messages are not lost but may be duplicated; QoS 2 means only one transmission, guaranteeing messages are neither lost nor duplicated, suitable for scenarios with extremely high data accuracy requirements) and message retention policy (e.g., setting it to True means retaining the last message, allowing new subscribers to obtain the latest data; setting it to False means not retaining messages) are configured to ensure the reliability and timeliness of message transmission. Vehicle model, access mode, and protocol configuration information are tightly linked and stored to form a complete and flexibly invoked configuration scheme, enabling the rapid selection of appropriate configuration parameters based on different vehicle models and access scenarios during data access.

[0048] Security Settings

[0049] We place great emphasis on data security, implementing comprehensive security measures at two key levels: data encryption and inter-platform access security. For data from different vehicle models, we scientifically select appropriate encryption algorithms or keys based on their sensitivity and importance. For highly sensitive data, such as vehicle location information, user privacy data, and vehicle control commands, we employ high-strength asymmetric encryption algorithms (such as RSA, with a key length of 2048 bits or more). We generate public and private key pairs, securely distributing the public key to in-vehicle terminals or third-party platforms for data encryption, while the private key is strictly managed by the enterprise monitoring platform for data decryption, ensuring that only authorized parties with the private key can decipher the encrypted data. For general vehicle operation data, we can use symmetric encryption algorithms (such as AES, with a key length of 128 or 256 bits) to improve encryption and decryption efficiency and reduce system resource consumption. Regarding data storage, we encrypt sensitive data fields in the database, such as using the database's built-in encryption function or encryption libraries to encrypt stored VIN codes, user passwords, and other fields, preventing database leaks from leading to unauthorized data access.

[0050] Regarding inter-platform access security, strict identity authentication information is configured, including setting complex and strong usernames and passwords, and combining multiple authentication methods such as digital certificates to ensure that only authorized legitimate platforms or devices can exchange data. The digital certificate adopts the internationally recognized X.509 standard format and includes the certificate version, certificate serial number, signature algorithm identifier, issuer name, validity period, and subject public key information. Verifying the validity of the digital certificate confirms the platform's identity. Simultaneously, a whitelist of allowed IP addresses is configured for third-party platforms to strictly restrict access from unauthorized external IP addresses, further enhancing data access security and effectively preventing illegal attacks and data leaks.

[0051] Data Validation

[0052] To ensure data integrity and accuracy, a rigorous data verification process is implemented after data access. The received data undergoes comprehensive verification according to data format specifications and pre-defined verification algorithms. The choice of verification algorithm depends on the data type and importance. For data integrity verification, algorithms such as CRC checksum and hash functions (e.g., SHA-256) can be used. For data accuracy verification, detailed verification rules are formulated based on data type and business rules. For example, for vehicle speed data, it is verified whether it is within a reasonable numerical range (e.g., 0-200 km / h); for vehicle VIN codes, it is verified whether they conform to the VIN code encoding rules and checksum calculation rules. A dedicated data verification module is developed to apply the verification rules during the data access process. If data verification fails, corresponding measures are taken based on the reason for the failure, such as data retransmission (the number of retransmissions and retransmission intervals can be set) or timely error prompts are sent to relevant personnel (via email, SMS, or system messages) for manual review and processing. This ensures that only valid data that passes rigorous verification is allowed to enter the subsequent data processing flow, guaranteeing high data quality and reliability.

[0053] It should be understood that the specific embodiments described above are merely illustrative or explanatory of the principles of the invention and do not constitute a limitation thereof. Therefore, any modifications, equivalent substitutions, improvements, etc., made without departing from the spirit and scope of the invention should be included within the protection scope of the invention. Furthermore, the appended claims are intended to cover all variations and modifications falling within the scope and boundaries of the appended claims, or equivalent forms of such scope and boundaries.

Claims

1. A method for accessing data from new energy vehicles that supports multiple types and modes, characterized in that, Includes the following steps: Vehicle model classification and VIN code parsing rules establishment: Analyze the characteristics of different new energy vehicle models, extract key information related to the model from the VIN code, establish a VIN code parsing rule base, and distinguish different models based on the rules; Data type association: For each vehicle model, we sort out the national standard data and the vehicle manufacturer's custom data that need to be accessed, establish a mapping relationship between vehicle models and data types, classify and label national standard data according to standards, and define custom data in detail. Data format specifications: Analyze each data format, record data packet characteristics and format specification information, clarify the header identifier, packet tail check code rules, data length field position, and standardize field definitions, encoding methods, and data arrangement order; Data access mode and protocol configuration: Configure vehicle models with options for direct connection to vehicle terminals, forwarding to third-party platforms, and access mode acquisition from third-party platforms. Record the access IP address and port number for direct connection to vehicle terminals, the API interface address for forwarding to third-party platforms, and the interface address and acquisition method for acquiring data from third-party platforms. For TCP, HTTP, and MQTT data interface protocols, set the TCP connection timeout, HTTP request header format specifications, and MQTT topic subscription rules. Associate and store vehicle model, access mode, and protocol configuration information to form a configuration scheme. Security settings: Select encryption algorithms or keys for different vehicle models to encrypt transmitted data, configure identity authentication information for inter-platform access, including username, password, and digital certificate, and configure a whitelist of allowed IP addresses for third-party platforms.

2. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, In the establishment of vehicle model classification and VIN code parsing rules, the VIN code parsing rule base is established based on vehicle manufacturer, model series, and production year information to formulate differentiation rules.

3. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 2, characterized in that, In the data type association, the definition specifications of the automaker's custom data format include the meaning of the fields, data type, and data range of the custom data.

4. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, In the data access mode and protocol configuration, for the third-party platform forwarding mode, the data forwarding frequency and data caching strategy parameters of the third-party platform are also recorded.

5. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, In the data access mode and protocol configuration steps, when setting MQTT protocol configuration parameters, it is also necessary to set the MQTT message quality level and message retention policy parameters.

6. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, In the security settings, the encryption algorithms include symmetric encryption algorithms such as AES and asymmetric encryption algorithms such as RSA, which are selected based on the importance and security requirements of the data.

7. A method for supporting multi-type and multi-mode new energy vehicle data access according to claim 6, characterized in that, In the security settings, the digital certificate adopts the X.509 standard format and includes the certificate version, certificate serial number, signature algorithm identifier, issuer name, validity period, and subject public key information.

8. The method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, In the data format specification process, the determination of the position of the data length field varies depending on the data format, and can be achieved by using a fixed position or by calculating it through a specific identifier.

9. A method for supporting multi-type and multi-mode new energy vehicle data access according to claim 8, characterized in that, In the data access mode and protocol configuration steps, when obtaining data from a third-party platform, different data acquisition timing methods are supported, such as timed acquisition and event-triggered acquisition.

10. A method for supporting multi-type and multi-mode new energy vehicle data access according to claim 1, characterized in that, It also includes a data verification step. After the data is received, the integrity and accuracy of the data are verified according to the data format specifications and verification algorithm. If the verification fails, the data is retransmitted or an error message is displayed.

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