Hydrogen filling monitoring method and device based on internet of vehicles

Abstract

The application provides a hydrogen filling monitoring method and device based on Internet of Vehicles, and relates to the technical fields of Internet of Vehicles and energy data monitoring. The hydrogen filling monitoring method based on Internet of Vehicles comprises the following steps: collecting hydrogen use process data, wherein the hydrogen use process data comprises hydrogen filling position data, vehicle driving behavior data, driving event data, hydrogen filling behavior data and hydrogen use accounting data; based on the hydrogen use process data, using corresponding hydrogen data processing algorithms and corresponding algorithm rule engines, performing calculation processing and identification judgment on vehicle hydrogen use behavior to obtain an identification result of the vehicle hydrogen use behavior; and outputting monitoring result data of whether the hydrogen use process is abnormal based on the identification result, so that accurate hydrogen filling behavior data can be obtained, real-time and accurate monitoring of the vehicle hydrogen use process is realized, and the work efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle networking and energy data monitoring technology, specifically to a hydrogen filling monitoring method and device based on vehicle networking. Background Technology

[0002] Because hydrogen fuel cell logistics vehicles and hydrogen refueling stations are still in the early stages of industrial development, supporting digital platforms and supply chain digital collaboration systems are generally lacking. Real-time online transmission of refueling and settlement data between hydrogen fuel cell logistics vehicle management units and refueling stations cannot yet be achieved, causing significant inconvenience for both parties. Currently, hydrogen fuel cell logistics vehicle management units and refueling stations face the following problems: misreporting the number of refuelings or the weight of refueling; underreporting the number of refuelings or the weight of refueling; vehicles not refueling at designated stations as required; and the inability to synchronize refueling records between different stations in real time, still relying on tools like WeChat or manual recording, which easily leads to identification and statistical errors, resulting in inaccurate energy data. All of these problems impose significant management costs on logistics vehicle management. Summary of the Invention

[0003] In view of this, the embodiments of this specification provide a hydrogen refueling monitoring method and device based on the Internet of Vehicles, which can acquire accurate hydrogen refueling behavior data, realize real-time and accurate monitoring of the hydrogen use process of vehicles, improve the efficiency of hydrogen energy data monitoring and management, and reduce management and operation costs.

[0004] The embodiments in this specification provide the following technical solutions:

[0005] On the one hand, a hydrogen filling monitoring method based on vehicle-to-everything (V2X) is provided, including:

[0006] Collect hydrogen consumption process data, which includes hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data;

[0007] Based on the hydrogen usage process data, the corresponding hydrogen data processing algorithm and algorithm rule engine are used to calculate, process and identify the hydrogen usage behavior of vehicles, and obtain the identification results of the hydrogen usage behavior of vehicles.

[0008] Based on the identification results, monitoring data on whether the hydrogen use process is abnormal is output.

[0009] In some embodiments, based on the hydrogen consumption process data, a corresponding hydrogen consumption data processing algorithm and a corresponding algorithm rule engine are used to calculate, process, and identify vehicle hydrogen consumption behavior to obtain the identification result of vehicle hydrogen consumption behavior, including:

[0010] Based on real-time coordinate data recorded by GIS and GPS, real-time data collected by TBOX from the hydrogen system, and electronic fences of hydrogen refueling stations, the system compares location differences to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling.

[0011] Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen filling algorithm, and the hydrogen filling behavior of the vehicle is judged by the engine according to the hydrogen filling rules, and the hydrogen filling behavior judgment result is obtained.

[0012] In some embodiments, based on the hydrogen consumption process data, a corresponding hydrogen consumption data processing algorithm and a corresponding algorithm rule engine are used to calculate, process, and identify vehicle hydrogen consumption behavior to obtain the identification result of vehicle hydrogen consumption behavior, including:

[0013] The initiation of hydrogen refueling by the vehicle triggers the reading of real-time temperature and pressure data of the hydrogen system.

[0014] Based on the real-time temperature and pressure data of the hydrogen system, the hydrogen filling weight is calculated according to the hydrogen filling mass algorithm, and the hydrogen filling weight is determined by the rule engine based on whether hydrogen filling is completed.

[0015] Based on the hydrogen refueling weight, recent hydrogen refueling records, recent mileage, and hydrogen refueling station reconciliation data, the hydrogen refueling weight is judged by the hydrogen refueling volume ratio rule engine to obtain a judgment result on whether the hydrogen refueling weight is abnormal.

[0016] In some embodiments, based on the hydrogen consumption process data, a corresponding hydrogen consumption data processing algorithm and a corresponding algorithm rule engine are used to calculate, process, and identify vehicle hydrogen consumption behavior to obtain the identification result of vehicle hydrogen consumption behavior, including:

[0017] Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen consumption slicing algorithm. Based on the recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery usage, voltage and current data, the hydrogen consumption process is monitored by the hydrogen consumption rule engine to obtain identification results of whether the hydrogen consumption process is abnormal.

[0018] In some embodiments, it also includes:

[0019] If the monitoring result data indicates an abnormality in the hydrogen use process, a hydrogen use abnormality alarm will be triggered and recorded.

[0020] On the other hand, a hydrogen filling monitoring device based on vehicle networking is also provided, including:

[0021] The hydrogen collection module is used to collect hydrogen consumption process data, which includes hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data.

[0022] The hydrogen consumption calculation and identification module is used to calculate and identify the vehicle's hydrogen consumption behavior based on the hydrogen consumption process data, using the corresponding hydrogen data processing algorithm and algorithm rule engine, and to obtain the identification result of the vehicle's hydrogen consumption behavior.

[0023] The hydrogen monitoring data output module is used to output monitoring result data on whether the hydrogen use process is abnormal based on the identification results.

[0024] In some embodiments, the hydrogen calculation and identification module is used for:

[0025] Based on real-time coordinate data recorded by GIS and GPS, real-time data collected by TBOX from the hydrogen system, and electronic fences of hydrogen refueling stations, the system compares location differences to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling.

[0026] Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen filling algorithm, and the hydrogen filling behavior of the vehicle is judged by the engine according to the hydrogen filling rules, and the hydrogen filling behavior judgment result is obtained.

[0027] In some embodiments, the hydrogen calculation and identification module is used for:

[0028] The initiation of hydrogen refueling by the vehicle triggers the reading of real-time temperature and pressure data of the hydrogen system.

[0029] Based on the real-time temperature and pressure data of the hydrogen system, the hydrogen filling weight is calculated according to the hydrogen filling mass algorithm, and the hydrogen filling weight is determined by the rule engine based on whether hydrogen filling is completed.

[0030] Based on the hydrogen refueling weight, recent hydrogen refueling records, recent mileage, and hydrogen refueling station reconciliation data, the hydrogen refueling weight is judged by the hydrogen refueling volume ratio rule engine to obtain a judgment result on whether the hydrogen refueling weight is abnormal.

[0031] In some embodiments, the hydrogen calculation and identification module is used for:

[0032] Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen consumption slicing algorithm. Based on the recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery usage, voltage and current data, the hydrogen consumption process is monitored by the hydrogen consumption rule engine to obtain identification results of whether the hydrogen consumption process is abnormal.

[0033] In some embodiments, the device further includes a hydrogen usage anomaly alarm module. If the monitoring result data is monitoring result data indicating an anomaly in the hydrogen usage process, the hydrogen usage anomaly alarm module is triggered to issue a hydrogen usage anomaly alarm and record the hydrogen usage anomaly alarm.

[0034] Compared with the prior art, the beneficial effects that the above-mentioned technical solutions adopted in the embodiments of this specification can achieve include at least:

[0035] First, based on the GIS+GPS location of the hydrogen refueling action and combined with the route planning at the business level, it is possible to accurately determine whether the vehicle is refueling at the designated hydrogen refueling station. Furthermore, by cross-referencing electronic fence data with the temperature and pressure change trends of the hydrogen system, it is possible to accurately determine whether the vehicle has arrived at the hydrogen refueling station and the hydrogen refueling action, thereby obtaining accurate hydrogen refueling behavior data and avoiding data deviations such as over-reporting, under-reporting, and omissions in vehicle hydrogen consumption behavior data.

[0036] Secondly, based on the collected hydrogen system pressure and temperature signals and their changing trends, combined with algorithms such as the hydrogen filling process accounting model in the algorithm library, the hydrogen weight is accurately calculated and compared with the metering data synchronized with the hydrogen refueling station. This can identify metering deviations, provide accurate data evidence, and facilitate the resolution of metering disputes.

[0037] Furthermore, based on the collected hydrogen system pressure and temperature signals and their changing trends, the algorithm calculation and the analysis and judgment of the algorithm rule engine can detect whether the hydrogen consumption during vehicle use is abnormal in real time and proactively, avoiding losses and risks caused by untimely detection.

[0038] In addition, through the intelligent algorithms, digital tools, and graphical interfaces provided by the system, managers can promptly and quickly identify various data deviations. By accurately monitoring hydrogen usage data in real time and synchronizing data between different sites through the system architecture, work efficiency can be greatly improved, thereby reducing management costs. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a schematic diagram of the hydrogen filling monitoring method based on the Internet of Vehicles provided in the embodiments of this application;

[0041] Figure 2 This is a flowchart illustrating the calculation, processing, and identification process for hydrogen consumption behavior in vehicles, provided in an embodiment of this application.

[0042] Figure 3 This is a flowchart illustrating the calculation, processing, and identification process for hydrogen consumption behavior in vehicles, provided in an embodiment of this application.

[0043] Figure 4This is a flowchart illustrating the calculation, processing, and identification process for hydrogen consumption behavior in vehicles, provided in an embodiment of this application.

[0044] Figure 5 This is a schematic diagram of the structure of the hydrogen filling monitoring device based on the Internet of Vehicles provided in this application embodiment;

[0045] Figure 6 This is a schematic diagram of the hydrogen filling monitoring system architecture based on the Internet of Vehicles provided in the embodiments of this application;

[0046] Figure 7 This is a schematic diagram of the map monitoring interface in the full-map monitoring provided in the embodiments of this application;

[0047] Figure 8 This is a schematic diagram of the data monitoring interface in the full-map monitoring provided in this application embodiment;

[0048] Figure 9 This is a schematic diagram of data collection based on GPS electronic fence provided in an embodiment of this application;

[0049] Figure 10 This is a schematic diagram of the hydrogen collection system of the fuel cell vehicle TBOX provided in the embodiments of this application;

[0050] Figure 11 This is a schematic diagram of the trend chart of hydrogen use process data for vehicles provided in the embodiments of this application. Detailed Implementation

[0051] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0052] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0054] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0055] Additionally, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that practice can be carried out without these specific details.

[0056] Example 1

[0057] This embodiment provides a hydrogen filling monitoring method based on vehicle-to-everything (V2X) communication, which includes the following steps:

[0058] S1. Collect hydrogen consumption process data, including hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data;

[0059] S2. Based on hydrogen usage process data, using the corresponding hydrogen data processing algorithm and algorithm rule engine, calculate, process and identify vehicle hydrogen usage behavior to obtain the identification result of vehicle hydrogen usage behavior.

[0060] S3. Based on the identification results, output monitoring data on whether the hydrogen use process is abnormal.

[0061] Specifically, hydrogen refueling location data can include imported GIS high-precision map data, GPS real-time location data, and real-time data collected by the TBOX hydrogen collection system built into the vehicle at the factory. This data can be obtained through data processing such as abnormal data filtering, speed generation, trajectory generation, duration generation, and recalculation of missing data. Vehicle driving behavior data can include data such as rapid acceleration, rapid deceleration, speeding, idling, and throttle depth. Driving event data can include data such as entering and exiting areas and vehicle start-stop. Hydrogen refueling behavior data can include behavior data such as hydrogen refueling start identification, hydrogen refueling end identification, and hydrogen refueling quantity calculation. Hydrogen consumption calculation data can include hydrogen consumption data sliced ​​and calculated according to time and operating conditions (stationary, idling, rapid acceleration, rapid deceleration, different speed ranges).

[0062] In step S2 above, based on the hydrogen usage process data, the corresponding hydrogen usage data processing algorithm and algorithm rule engine are used to calculate, process, and identify the vehicle's hydrogen usage behavior to obtain the identification result of the vehicle's hydrogen usage behavior. This can be implemented in the following way:

[0063] like Figure 2 As shown, based on real-time coordinate records from GIS and GPS, real-time data from the hydrogen system collected by TBOX, and electronic fences at hydrogen refueling stations, location differences are compared to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling.

[0064] Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen filling algorithm, and the hydrogen filling behavior of the vehicle is judged by the engine according to the hydrogen filling rules, and the hydrogen filling behavior judgment result is obtained.

[0065] Through the algorithm and algorithm rule engine of this process, it is possible to accurately determine new hydrogen refueling behavior of vehicles, whether hydrogen refueling is done at designated hydrogen refueling stations, and whether there are abnormal behaviors such as over-reporting, under-reporting, or omission of hydrogen refueling times.

[0066] In addition, in step S2 above, based on the hydrogen usage process data, using the corresponding hydrogen usage data processing algorithm and the corresponding algorithm rule engine to calculate, process, and identify the vehicle's hydrogen usage behavior, and obtain the identification result of the vehicle's hydrogen usage behavior, it can also be implemented in the following way:

[0067] like Figure 3 As shown, the vehicle's hydrogen refueling process triggers the reading of real-time temperature and pressure data of the hydrogen system.

[0068] Based on real-time temperature and pressure data of the hydrogen system, the hydrogen filling weight is calculated according to the hydrogen filling mass algorithm, and the hydrogen filling weight is determined by the rule engine based on whether hydrogen filling has ended.

[0069] Based on hydrogen refueling weight, recent hydrogen refueling records, recent mileage, and hydrogen refueling station reconciliation data, the hydrogen refueling weight is judged by the hydrogen refueling volume comparison rule engine. By verifying the data, it is determined whether there is a significant difference in the weight of this hydrogen refueling, thereby obtaining a judgment result on whether the hydrogen refueling weight is abnormal.

[0070] In addition, in step S2 above, based on the hydrogen usage process data, using the corresponding hydrogen usage data processing algorithm and the corresponding algorithm rule engine to calculate, process, and identify the vehicle's hydrogen usage behavior, and obtain the identification result of the vehicle's hydrogen usage behavior, it can also be implemented in the following way:

[0071] like Figure 4 As shown, based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen consumption slicing algorithm. Based on recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery usage, voltage, and current data, the hydrogen consumption process is monitored by the hydrogen consumption rule engine based on whether the hydrogen consumption is too fast. The engine obtains the identification results of whether the hydrogen consumption process is abnormal and can record hydrogen consumption abnormality alarms.

[0072] Through the algorithm and algorithm rule engine of this process, the hydrogen use process can be continuously monitored, and abnormal behaviors such as hydrogen leakage or diversion caused by equipment failure or human sabotage can be detected in a timely manner.

[0073] Furthermore, preferably, the hydrogen filling monitoring method based on the Internet of Vehicles provided in this application embodiment further includes the following steps:

[0074] If the monitoring results show that the hydrogen use process is abnormal, a hydrogen use anomaly alarm will be triggered and recorded. This will enable timely monitoring and acquisition of data on abnormal hydrogen use conditions. Furthermore, the hydrogen use anomaly alarm record will allow for data retention and synchronization, and will also be used for subsequent data analysis.

[0075] Example 2

[0076] In this embodiment, a hydrogen filling monitoring device based on the Internet of Vehicles is provided, such as... Figure 5 As shown, the device includes:

[0077] The hydrogen collection module 21 is used to collect hydrogen consumption process data, which includes hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data.

[0078] The hydrogen consumption calculation and identification module 22 is used to calculate and identify the hydrogen consumption behavior of vehicles based on hydrogen consumption process data, using relevant hydrogen data processing algorithms and corresponding algorithm rule engines, and to obtain the identification results of the hydrogen consumption behavior of vehicles.

[0079] The hydrogen monitoring data output module 23 is used to output monitoring result data on whether the hydrogen use process is abnormal based on the identification results.

[0080] Specifically, the hydrogen calculation and identification module 22 can be used to: compare location differences based on real-time coordinate recording data from GIS and GPS, real-time data from the hydrogen system collected by TBOX, and electronic fences of hydrogen refueling stations to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling; and, based on the read real-time temperature and pressure data of the hydrogen system, perform calculations according to the hydrogen filling algorithm, and determine the vehicle's hydrogen refueling behavior according to the hydrogen refueling rule engine to obtain the hydrogen refueling behavior judgment result.

[0081] In addition, the hydrogen calculation and identification module 22 can also be used for: triggering the reading of real-time data on the temperature and pressure of the hydrogen system when the vehicle starts refueling; calculating the hydrogen filling weight based on the real-time data on the temperature and pressure of the hydrogen system according to the hydrogen filling quality algorithm, and determining the hydrogen filling weight according to the rule engine based on whether the hydrogen refueling has ended; and judging the hydrogen filling weight based on the hydrogen filling weight, recent hydrogen refueling records, recent mileage, and hydrogen refueling station reconciliation data, and obtaining the judgment result of whether the hydrogen filling weight is abnormal.

[0082] In addition, the hydrogen consumption calculation and identification module 22 can also be used to: calculate based on the real-time temperature and pressure data of the hydrogen system read, according to the hydrogen consumption slicing algorithm, and monitor the hydrogen consumption process based on the recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery usage, voltage and current data, according to the hydrogen consumption rule engine to obtain the identification result of whether the hydrogen consumption process is abnormal, and can record the hydrogen consumption abnormal alarm through the hydrogen consumption abnormal alarm module described below.

[0083] Preferably, the hydrogen filling monitoring device based on the Internet of Vehicles provided in this application embodiment also includes a hydrogen usage anomaly alarm module (not shown in the figure). If the monitoring result data is monitoring result data indicating an anomaly in the hydrogen usage process, the hydrogen usage anomaly alarm module is triggered to issue a hydrogen usage anomaly alarm and record the hydrogen usage anomaly alarm.

[0084] Example 3

[0085] The hydrogen filling monitoring method and apparatus based on the Internet of Vehicles provided in the embodiments of this application (including embodiments 1, 2, or other possible embodiments) can be implemented using the following system architecture. For example... Figure 6 As shown, the system architecture mainly includes a device layer, a data acquisition subsystem, an algorithm library, an algorithm rule engine, and a system platform. It should be noted that this system architecture is merely exemplary, and any other possible system architecture can be implemented without departing from the inventive concept of this application.

[0086] Specifically, the device layer is compatible with various intelligent vehicle devices, including GPS devices, TBOX, vehicle terminals, dashcams, cameras, and various communication gateways. If the device layer has remote communication capabilities, it can send data to the data acquisition platform independently, or it can aggregate data through Tbox or other communication gateways and then send the data to the data acquisition platform.

[0087] In addition, the data acquisition subsystem in this hydrogen filling monitoring system architecture mainly implements functions such as communication gateway, instruction encapsulation / parsing, data verification, data processing, data storage, and data forwarding.

[0088] Specifically, the communication gateway: the data acquisition platform's communication adapter is now compatible with mainstream communication protocols, such as 808 / 809 / 32960, etc. This component allows for rapid expansion of communication data access and supports dynamic loading and unloading of devices. Preferably, it utilizes IoT cloud platform technologies combined with vehicle networking technologies to develop a communication gateway compatible with multiple protocols, enabling real-time, scheduled, or on-demand connections with various onboard intelligent devices in hydrogen fuel cell logistics vehicles. Simultaneously, dynamic loading / unloading and configurable parsing technologies have been developed for various communication protocols (808 / 809 / 32960, etc.), making protocol expansion more flexible and avoiding the drawbacks of platform-wide restart loading, thus facilitating the maintenance of overall data integrity and stability.

[0089] Regarding data collection, for example, such as Figure 7 and Figure 8 As shown, high-precision map data can be imported into a GIS system to establish a high-precision map coordinate system. Through the latitude and longitude signal metadata uploaded by the vehicle's GPS device, data processing can be performed in the GIS system to generate real-time coordinates, real-time speed, route, parking duration, rapid acceleration, rapid deceleration, and driver fatigue data. This data can be further enhanced using the electronic fence of the hydrogen refueling station (for example, such as...). Figure 9 (As shown) can generate the time points and durations of a driver's entry and exit from a hydrogen refueling station, used to make a preliminary judgment on the vehicle's hydrogen refueling behavior. Further, exemplarily as follows... Figure 10 As shown, real-time data from the hydrogen system can be obtained by using a TBOX to collect hydrogen data or by directly installing a CAN protocol communication gateway. This allows for the acquisition of pressure, temperature, and other data from multiple sensors, enabling accurate judgments on actual hydrogen refueling actions based on the most accurate data.

[0090] Command encapsulation / parsing: Based on the transmission requirements of various devices, various protocol commands can be encapsulated / parsed, and commands can be sent or data can be received according to the interaction sequence.

[0091] Data validation: For the collected and parsed data, data validation can be performed according to the agreed validation mode to remove dirty data.

[0092] Data processing: The collected data can be processed according to set rules to generate secondary data.

[0093] Data storage: Collected data can be stored in a database / file on a scheduled or real-time basis according to the configured storage requirements.

[0094] Data forwarding: For collected data and alarm data, the subscribed data can be forwarded to the designated location through various message middleware, SMS interface and other real-time communication interfaces according to the configured parameters.

[0095] In addition, the algorithm library in this hydrogen filling monitoring system architecture mainly focuses on processing the collected data through various algorithms to form business-usable data. The main algorithms include the following:

[0096] Based on hydrogen refueling location data: abnormal data filtering, velocity generation, trajectory generation, duration generation, and recalculation of missing data, etc.

[0097] Based on vehicle driving behavior data: rapid acceleration, rapid deceleration, speeding, idling speed, throttle depth, etc.

[0098] Based on driving event data categories: entry and exit areas, vehicle start and stop, etc.;

[0099] Based on hydrogen refueling behavior data: hydrogen refueling start identification, hydrogen refueling end identification, and hydrogen refueling amount calculation;

[0100] Based on hydrogen consumption calculation data: the hydrogen consumption is calculated by segmenting the data according to time and operating conditions (stationary, idling, rapid acceleration, rapid deceleration, and different speed ranges).

[0101] Preferably, based on the collected real-time data of the hydrogen system, dirty data can be filtered out using a filtering model in the algorithm library, and the hydrogen filling process calculation model can be used to accurately calculate the hydrogen addition weight. Additionally, by collecting and processing the hydrogen system data, it is possible to create segments according to different time periods and operating conditions, dynamically calculate the hydrogen consumption within each segment, and use this data to determine whether the hydrogen consumption process is abnormal and whether there is a hydrogen leak (caused by human error or equipment problems).

[0102] The corresponding algorithm rule engine in this hydrogen filling monitoring system architecture can accurately identify whether there is abnormal hydrogen filling behavior by cross-comparison and statistical analysis of various rules on the collected real-time data, processed secondary data, and business data. The main components of the algorithm rule engine are:

[0103] Rule configuration: Configure the required input data items, rule operation logic, and result output method for the rule;

[0104] Rule scheduling: Configure the scheduling time, frequency, and running mode of rules;

[0105] Calculation of operation rules: Decision rules are formulated using configuration, code, and machine learning methods;

[0106] Rule logic implementation: Based on various data inputs, the logic encoding of various rules such as hydrogen refueling start behavior comparison, hydrogen refueling end behavior comparison, real-time comparison of hydrogen use process, hydrogen consumption statistical anomaly comparison, and hydrogen leakage early warning is implemented;

[0107] Output results: The results of the rule engine's calculations are stored in the database or sent out as messages.

[0108] Preferably, GPS data and hydrogen system data can be used to accurately determine whether a vehicle has refueled and the amount of hydrogen refueled. By calculating dynamic hydrogen consumption and combining it with hydrogen leak alarm data, it is possible to determine whether there are any abnormalities in the hydrogen consumption process. Simultaneously, a comprehensive analysis and comparison of mileage, route, and business data can be performed to determine whether the vehicle's hydrogen refueling and consumption behavior is abnormal. Furthermore, intelligent analysis and decision-making can be performed on the collected real-time data, secondary processed data, and multi-rule comparison data, providing real-time alarms / warnings for detected abnormal behaviors and data, generating alarm / warning reports. In addition, by using IoT metadata or processed data such as GPS data and on-board instrument data, combined with business data and hydrogen refueling station settlement data, multi-dimensional analysis can be performed to comprehensively determine whether the vehicle's hydrogen refueling and consumption behavior is abnormal. Finally, reports and charts are provided to management personnel for querying and downloading, as exemplified by... Figure 11 The chart shown is a trend chart of hydrogen usage data for vehicles.

[0109] Based on the above device layer, data acquisition subsystem, algorithm library, and algorithm rule engine, this system architecture also implements a system platform that facilitates real-time monitoring, querying, and application for users.

[0110] Through the data acquisition subsystem and rule engine subsystem, data preparation has been completed. Various business operations and management are then completed through system platform and user interaction. The main functions of the system platform include:

[0111] Real-time monitoring: Monitors the vehicle's current location, speed, hydrogen system, fuel cell system and other real-time parameters through GIS maps and charts, and supports trajectory playback and multi-condition data playback;

[0112] Data Query: Query various types of data according to different dimensions, different time slices, and different working conditions. Supports multi-dimensional chart display and multi-dimensional comparison display.

[0113] Behavior statistics and replay: View the identified hydrogen refueling start, hydrogen refueling end, hydrogen refueling amount and hydrogen usage behavior events and judgment status, and support multi-dimensional data combination replay;

[0114] Alarms / Warnings: Users can query alarm / warning information, receive alarm / warning information via SMS, WeChat, DingTalk, and email, and process alarm / warning information online.

[0115] Statistical analysis: Supports multi-dimensional, multi-time period, and multi-working-condition data combination queries, chart (trend chart, bar chart, pie chart, etc.) analysis and comparative analysis; supports data drill-down at different levels of granularity;

[0116] Various configuration modules: configuration of various basic data and rules;

[0117] Access control: Assign operation permissions according to different positions and roles.

[0118] In this specification, similar or identical parts between the various embodiments can be referred to mutually, and each embodiment focuses on describing the differences from other embodiments. In particular, for the apparatus or system architecture embodiments described later, since they correspond to the methods, the relevant parts can be referred to the description of the system embodiments. Furthermore, this specification uses specific terms to describe the embodiments. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different places in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0119] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented by hardware devices, they can also be implemented solely by software solutions, such as installing the described system on existing processing devices or mobile devices.

[0120] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

Claims

1. A hydrogen filling monitoring method based on vehicle-to-everything (V2X) communication, characterized in that, include: Collect hydrogen consumption process data, which includes hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data; Based on real-time coordinate data recorded by GIS and GPS, real-time data collected by TBOX from the hydrogen system, and electronic fences of hydrogen refueling stations, the system compares location differences to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling. Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen filling algorithm, and the hydrogen filling behavior of the vehicle is judged by the hydrogen filling rule engine according to the hydrogen filling behavior, and the hydrogen filling behavior judgment result is obtained. The initiation of hydrogen refueling by the vehicle triggers the reading of real-time temperature and pressure data of the hydrogen system. Based on the real-time temperature and pressure data of the hydrogen system, the hydrogen filling weight is calculated according to the hydrogen filling mass algorithm, and the hydrogen filling weight is determined by the rule engine based on whether hydrogen filling is completed. Based on the hydrogen refueling weight, recent hydrogen refueling records, recent driving mileage, and hydrogen refueling station reconciliation data, the rule engine judges the hydrogen refueling weight according to the hydrogen refueling volume ratio to obtain the judgment result of whether the hydrogen refueling weight is abnormal. Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen consumption slicing algorithm. Based on the recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery consumption, voltage and current data, the hydrogen consumption process is monitored by the hydrogen consumption rule engine to obtain the identification results of whether the hydrogen consumption process is abnormal. Based on the identification results, monitoring data on whether the hydrogen use process is abnormal is output.

2. The hydrogen filling monitoring method based on vehicle networking according to claim 1, characterized in that, Also includes: If the monitoring result data indicates an abnormality in the hydrogen use process, a hydrogen use abnormality alarm will be triggered and recorded.

3. A hydrogen filling monitoring device based on vehicle-to-everything (V2X) communication, characterized in that, include: The hydrogen collection module is used to collect hydrogen consumption process data, which includes hydrogen refueling location data, vehicle driving behavior data, driving event data, hydrogen refueling behavior data, and hydrogen consumption accounting data. Using a hydrogen computing and identification module, based on real-time coordinate records from GIS and GPS, real-time data from the hydrogen system collected by TBOX, and electronic fences at hydrogen refueling stations, the system compares location differences to determine whether a vehicle is at the corresponding hydrogen refueling station and whether it is refueling. Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen filling algorithm, and the hydrogen filling behavior of the vehicle is judged by the hydrogen filling rule engine according to the hydrogen filling behavior, and the hydrogen filling behavior judgment result is obtained. The initiation of hydrogen refueling by the vehicle triggers the reading of real-time temperature and pressure data of the hydrogen system. Based on the real-time temperature and pressure data of the hydrogen system, the hydrogen filling weight is calculated according to the hydrogen filling mass algorithm, and the hydrogen filling weight is determined by the rule engine based on whether hydrogen filling is completed. Based on the hydrogen refueling weight, recent hydrogen refueling records, recent driving mileage, and hydrogen refueling station reconciliation data, the rule engine judges the hydrogen refueling weight according to the hydrogen refueling volume ratio to obtain the judgment result of whether the hydrogen refueling weight is abnormal. Based on the real-time temperature and pressure data of the hydrogen system, calculations are performed according to the hydrogen consumption slicing algorithm. Based on the recent vehicle operating conditions, recent mileage, vehicle GPS location data, vehicle speed, and power battery consumption, voltage and current data, the hydrogen consumption process is monitored by the hydrogen consumption rule engine to obtain the identification results of whether the hydrogen consumption process is abnormal. The hydrogen monitoring data output module is used to output monitoring result data on whether the hydrogen use process is abnormal based on the identification results.

4. The hydrogen filling monitoring device based on vehicle networking according to claim 3, characterized in that, It also includes a hydrogen usage anomaly alarm module. If the monitoring result data is monitoring result data indicating an anomaly in the hydrogen usage process, the hydrogen usage anomaly alarm module is triggered to issue a hydrogen usage anomaly alarm and record the hydrogen usage anomaly alarm.

Images