CN117970822A

CN117970822A - Automatic unmanned hydrogenation system and hydrogenation method thereof

Info

Publication number: CN117970822A
Application number: CN202410389377.4A
Authority: CN
Inventors: 张彬; 袁文英; 贾伟超; 刘瑶
Original assignee: Shaanxi Heishi Green Energy Energy Technology Co ltd
Current assignee: Shaanxi Heishi Green Energy Energy Technology Co ltd
Priority date: 2024-04-02
Filing date: 2024-04-02
Publication date: 2024-05-03
Anticipated expiration: 2044-04-02
Also published as: CN117970822B

Abstract

The invention relates to the technical field of automatic hydrogenation, in particular to an automatic unmanned hydrogenation system and a hydrogenation method thereof. The method comprises the following steps: acquiring initial data of a vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data; and obtaining initial transmission data of the hydrotreater. According to the invention, through vehicle position information extraction, real-time environment sensing, hydrogenation control strategy generation, communication optimization and dynamic path planning adjustment, the safety, adaptability and efficiency of the automatic unmanned hydrogenation system are improved.

Description

Automatic unmanned hydrogenation system and hydrogenation method thereof

Technical Field

The invention relates to the technical field of automatic hydrogenation, in particular to an automatic unmanned hydrogenation system and a hydrogenation method thereof.

Background

With the increasing environmental awareness and the limitation of traditional energy sources, hydrogen energy is becoming a highly efficient and clean energy medium. However, the widespread use of hydrogen energy is challenged by its storage, transportation and supply. In this context, automated unmanned hydrogenation systems have evolved. The hydrogen energy storage technology has undergone the development from traditional hydrogen compression, liquefaction to advanced hydrogen adsorption and chemical hydrogen storage, and provides a foundation for the efficient utilization of hydrogen energy. Then, the hydrogen energy transportation technology gradually realizes a safer and more efficient hydrogen transportation system, and lays a foundation for realizing an unmanned hydrogenation system. In the aspect of hydrogenation technology, the initial hydrogen compression station and the liquefaction station gradually evolve into high-pressure liquid hydrogen and liquid hydrogen hydrogenation stations, so that the hydrogenation efficiency is improved. However, these systems still rely on manual operation, with certain security risks. With the development of automation technology, unmanned hydrogenation systems are gradually in the way of the corner. In recent years, unmanned hydrogenation systems have realized remote monitoring, intelligent scheduling and safety control using advanced sensing techniques, artificial intelligence and machine learning algorithms. This makes the hydrogenation process more automated, efficient, and greatly reduces the risk of human error. However, the current automatic hydrogenation still cannot well ensure the correct butt joint between the hydrotreater and the vehicle and the adaptability between different vehicle types, so that the hydrogenation precision is low.

Disclosure of Invention

Based on this, there is a need to provide an automated unmanned hydrogenation system and a hydrogenation method thereof, so as to solve at least one of the above technical problems.

To achieve the above object, an automated unmanned hydrogenation method, for use on a hydrogenation station and a vehicle, comprises the steps of: step S1: acquiring initial data of a vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

Step S2: obtaining initial transmission data of a hydrotreater; generating a control strategy for the initial transmission data of the hydrotreater to obtain a hydrogenation control strategy; remote hydrogenation monitoring is carried out on the accurate positioning data of the vehicle based on a hydrogenation control strategy, and real-time hydrogenation state monitoring control data is generated;

Step S3: communication bandwidth allocation is carried out on the real-time hydrogenation state monitoring control data, and communication bandwidth allocation data are generated; data compression is carried out on the communication bandwidth allocation data, and communication transmission optimization data are generated; performing information interaction on the real-time hydrogenation state monitoring control data based on the communication transmission optimization data to generate hydrogenation interaction information data;

Step S4: carrying out real-time traffic condition sensing analysis through the environment sensing fusion data to generate traffic condition information data; performing hydrogenation path planning adjustment based on traffic condition information data, vehicle accurate positioning data and real-time hydrogenation state monitoring control data to generate hydrogenation path adjustment data; and performing autonomous hydrogenation butt joint on the hydrogenation station and the vehicle through the hydrogenation path adjustment data so as to execute an automatic unmanned hydrogenation instruction.

The invention is based on collecting initial information about the vehicle. Sensor data of the vehicle, initial position, vehicle standard data, etc. may be included. Position information of the vehicle is extracted from the vehicle initial data. This may include acquiring the current geographic location of the vehicle using Global Positioning System (GPS) or other positioning technology. A real-time environment map is created using the vehicle position information and the vehicle standard data. This map may display environmental information of roads, buildings, etc. around the vehicle. The identification and tracking of the target object is performed on a real-time environment map. This may involve using sensor data (e.g., cameras) to detect and track surrounding objects, such as other vehicles, pedestrians, etc. And fusing the data obtained in the previous steps to form more comprehensive environment perception data. This may provide more detailed and comprehensive information about the vehicle surroundings, helping the intelligent system to better understand and cope with different situations. Initial transmission data is obtained from the hydrotreater. This may include data including Guan Jiaqing information about the current state of the device, hydrogen delivery rate, pressure, etc. And generating a control strategy according to the initial transmission data. This may include determining optimal hydrogenation rates, pressure control, etc. to ensure a safe and efficient hydrogenation process. And using the generated hydrogenation control strategy to remotely hydrogenate and monitor the accurate positioning data of the vehicle. This may include monitoring various parameters in the hydrogenation process, as well as updating control data in real time to maintain monitoring and control of the hydrogenation state. And distributing communication bandwidth to the real-time hydrogenation state monitoring control data. This may include ensuring that different types of data transmissions get enough bandwidth to ensure stability and real-time of communications. The allocated communication bandwidth data is compressed to reduce bandwidth usage during data transmission. Data compression helps to improve communication efficiency, reduce transmission delay, and more efficiently utilize bandwidth when network resources are limited. And carrying out information interaction on the real-time hydrogenation state monitoring control data by utilizing the optimized communication transmission data. This may include transmitting the hydrogenation state information in real time for more flexible and efficient monitoring and control. And carrying out real-time traffic condition perception analysis by utilizing the environment perception fusion data generated before. This may include detecting traffic flow, accidents, engineering, etc. conditions on the road to generate accurate traffic condition information data. And adjusting the hydrogenation path planning by combining traffic condition information, vehicle position data and real-time hydrogenation state monitoring data. This may involve selecting an optimal hydrotreater, generating optimized hydrotreater path adjustment data considering real-time traffic conditions and vehicle hydrotreater demands. And utilizing the hydrogenation path adjustment data, and performing autonomous hydrogenation butt joint on the vehicle and the hydrogenation station. This may include executing automated unmanned hydrogenation instructions, ensuring that the vehicle reaches the hydrogenation station safely and efficiently in an optimized path, and completing the hydrogenation process. Therefore, the safety, adaptability and efficiency of the automatic unmanned hydrogenation system are improved through vehicle position information extraction, real-time environment sensing, hydrogenation control strategy generation, communication optimization and dynamic path planning adjustment.

In this specification, there is provided an automated unmanned hydrogenation system for performing an automated unmanned hydrogenation method as described above, the automated unmanned hydrogenation system comprising: the environment sensing module is used for acquiring initial data of the vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

The hydrogenation monitoring module is used for acquiring initial transmission data of the hydrotreater; generating a control strategy for the initial transmission data of the hydrotreater to obtain a hydrogenation control strategy; remote hydrogenation monitoring is carried out on the accurate positioning data of the vehicle based on a hydrogenation control strategy, and real-time hydrogenation state monitoring control data is generated;

the communication transmission module is used for carrying out communication bandwidth allocation on the real-time hydrogenation state monitoring control data and generating communication bandwidth allocation data; data compression is carried out on the communication bandwidth allocation data, and communication transmission optimization data are generated; performing information interaction on the real-time hydrogenation state monitoring control data based on the communication transmission optimization data to generate hydrogenation interaction information data;

The intelligent docking module is used for carrying out real-time traffic condition perception analysis through the environment perception fusion data to generate traffic condition information data; performing hydrogenation path planning adjustment based on traffic condition information data, vehicle accurate positioning data and real-time hydrogenation state monitoring control data to generate hydrogenation path adjustment data; and performing autonomous hydrogenation butt joint on the hydrogenation station and the vehicle through the hydrogenation path adjustment data so as to execute an automatic unmanned hydrogenation instruction.

The invention has the advantage of collecting initial information about the vehicle. Position information is extracted from the vehicle initial data. A real-time environment map is created using the vehicle location information and the vehicle standard data, reflecting the environment around the vehicle. And identifying and tracking the target object on the real-time environment map to generate object identification tracking data. And fusing the vehicle position information, the real-time environment map and the object identification tracking data to generate environment perception fusion data, and providing comprehensive environment cognition for the system. Initial transmission data is collected about the hydrotreater. And generating a hydrogenation control strategy based on the initial transmission data of the hydrotreater, and determining how to carry out hydrogenation. The hydrogenation control strategy is used for carrying out remote hydrogenation monitoring on the vehicle, so that real-time hydrogenation state monitoring control data are generated, and the high efficiency and the safety of the hydrogenation process are ensured. And carrying out communication bandwidth allocation on the real-time hydrogenation state monitoring control data to ensure timely data transmission. And data compression is carried out on the communication bandwidth allocation data, so that the communication cost is reduced and the transmission efficiency is improved. And carrying out optimized information interaction on the real-time hydrogenation state monitoring control data by utilizing the compressed data to generate hydrogenation interaction information data, so as to promote efficient communication between systems. And carrying out real-time traffic condition sensing analysis by using the environment sensing fusion data to generate accurate traffic condition information data. And adjusting the hydrogenation path planning based on the traffic condition information, the vehicle accurate positioning data and the real-time hydrogenation state monitoring control data to generate hydrogenation path adjustment data. The hydrogenation station and the vehicle realize autonomous hydrogenation butt joint by adjusting data through the hydrogenation path, and an automatic unmanned hydrogenation instruction is executed, so that the autonomy and the efficiency of the hydrogenation process are improved. The hydrogenation process and the vehicle operation management are realized with high efficiency, and the method can have beneficial effects on improving the overall performance and the user experience of the hydrogen fuel cell vehicle. Therefore, the safety, adaptability and efficiency of the automatic unmanned hydrogenation system are improved through vehicle position information extraction, real-time environment sensing, hydrogenation control strategy generation, communication optimization and dynamic path planning adjustment.

Drawings

FIG. 1 is a schematic flow diagram of steps of an automated unmanned hydrogenation process;

FIG. 2 is a flowchart illustrating the detailed implementation of step S2 in FIG. 1;

FIG. 3 is a detailed flowchart illustrating the implementation of step S23 in FIG. 1;

FIG. 4 is a flowchart illustrating the detailed implementation of step S4 in FIG. 1;

The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.

Detailed Description

The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.

Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.

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

To achieve the above object, referring to fig. 1 to 4, the present invention provides an automated unmanned hydrogenation method for a hydrogenation station and a vehicle, comprising the steps of: step S1: acquiring initial data of a vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

In the embodiment of the present invention, as described with reference to fig. 1, a schematic flow chart of steps of an automated unmanned hydrogenation method of the present invention is provided, and in this example, the automated unmanned hydrogenation method includes the following steps: step S1: acquiring initial data of a vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

In the embodiment of the invention, the initial data of the vehicle, including the information of position, speed, direction and the like, is acquired by using the vehicle-mounted sensor (such as GPS, inertial navigation system, camera and the like) and the vehicle interface. Standard data of the vehicle is acquired through vehicle network connection, and may include information such as vehicle type, manufacturer, performance parameters and the like. Accurate location information of the vehicle is extracted using GPS data or data from other location sensors. And arranging the extracted position information into a data format to form vehicle position information data. An initial environment map is constructed using the vehicle position information data and the vehicle standard data. And updating the environment map by using the real-time data, and keeping the real-time property of the map. Real-time map construction may be performed using SLAM (Simultaneous Localization AND MAPPING) or the like. The recognition and tracking of the target object are performed by using sensors such as an image or a laser radar. Object identification tracking data is generated using computer vision techniques, such as object detection and tracking algorithms. And fusing the vehicle position information data, the real-time environment map and the object identification tracking data. And comprehensively considering information of different data sources by utilizing a fusion algorithm to generate comprehensive environment perception fusion data.

In the embodiment of the invention, the initial transmission data of the hydrotreater is acquired by using a sensor or monitoring equipment, which may include relevant parameters such as hydrogen flow, pressure, temperature and the like. Based on the initial transmission data of the hydrotreater, a hydrogenation control strategy is generated using a control algorithm. The control strategy may involve adjusting the hydrogen flow, maintaining a specific pressure and temperature, etc. to ensure a safe and efficient hydrogenation process. And applying the generated hydrogenation control strategy to the accurate positioning data of the vehicle. A remote monitoring system is established by using a communication technology, so that real-time communication can be carried out between the hydrotreater and the vehicle. And monitoring the real-time position of the vehicle, and dynamically adjusting the hydrogenation control strategy according to the position of the vehicle. Generating real-time hydrogenation state monitoring control data which may include information such as hydrogenation progress, real-time hydrogen parameters, system states and the like. Safety measures such as monitoring hydrogen leakage, abnormal temperature and the like are implemented, and corresponding emergency measures are adopted. And deploying a fault detection and processing mechanism to ensure that the system can respond and process in time when an abnormal situation occurs. Critical data during hydrogenation is recorded for subsequent analysis and optimization. And by utilizing a data analysis technology, useful information is extracted, a control strategy is optimized, and the hydrogenation efficiency and the safety are improved.

In the embodiment of the invention, the property and the size of the control data are monitored by knowing the real-time hydrogenation state. Communication requirements, including data transmission rate and delay requirements, are assessed. And the available communication bandwidth is distributed by using a proper algorithm, so that the real-time performance and reliability requirements of the system are met. An appropriate data compression algorithm is selected, and factors such as compression ratio, speed and decompression complexity are considered. Dynamic compression is implemented to adjust the compression level according to changes in real-time communication bandwidth. Using an efficient communication protocol, packet size, protocol overhead and reliability are considered. Appropriate error detection and correction mechanisms are implemented to ensure reliable data transmission. For real-time control data, a flow control mechanism is implemented to avoid data loss and communication delays. And a clear information interaction specification is formulated, so that mutual understanding among different components is ensured. The hydrogenation interaction information data can be updated in real time so as to reflect the current state of the system. Security is a concern in information interactions, using encryption and authentication mechanisms to prevent unauthorized access.

In the embodiment of the invention, various environment sensing sensors, such as cameras, radars, lidars and the like, are deployed to collect surrounding environment information. And fusing the data acquired by the sensors to form comprehensive environment sensing data. Traffic conditions are perceived and analyzed in real time using machine learning or other algorithms to generate traffic condition information data. Based on traffic condition information, vehicle positioning data and real-time hydrogenation state monitoring control data, an efficient path planning algorithm is used, and factors such as traffic flow, road conditions, availability of a hydrogenation station and the like are considered. The system needs to be able to respond in real time to changes in traffic conditions, dynamically adjusting the hydrogenation path to optimize the travel route of the vehicle. The format of the hydrogenation path adjustment data is determined to facilitate data interaction between systems. The hydrogenation path adjustment data should contain key information such as path information after adjustment, hydrogenation station information and the like. Accurate vehicle positioning systems are used to ensure accuracy of vehicle position. And setting a communication protocol between the vehicle and the hydrogen adding station, so as to ensure that the two parties can perform effective information interaction. An autonomous control system of the vehicle and the docking station is implemented to execute unmanned docking commands. Encryption and authentication mechanisms are used in the data transmission and communication processes, so that the safety of information is ensured. The system is designed to cope with various fault conditions including sensor faults, communication faults, etc. And (3) performing system testing in a simulation environment to ensure the stability and performance of the system. And testing and optimizing in an actual scene, and verifying the performance of the system under the real traffic condition.

Preferably, step S1 comprises the steps of: step S11: acquiring vehicle initial data by using a vehicle-mounted sensor;

step S12: performing data preprocessing on initial data of the vehicle to generate standard data of the vehicle, wherein the data preprocessing comprises data denoising, data missing value filling and data standardization;

Step S13: extracting vehicle position information from the vehicle standard data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map;

Step S14: performing target object identification tracking on the real-time environment map to generate object identification tracking data, wherein the target object identification tracking comprises vehicles and pedestrians; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

step S15: and carrying out self-adaptive positioning correction on the initial data of the vehicle through the environment perception fusion data to generate accurate positioning data of the vehicle.

According to the invention, the vehicle-mounted sensor is utilized to acquire initial data, and the data preprocessing comprises denoising, missing value filling and standardization, so that high-quality vehicle standard data is generated. The method is beneficial to improving the reliability of data and providing accurate input for subsequent steps. Vehicle location information extraction and real-time environment mapping provide comprehensive awareness of the surrounding environment of the vehicle. The real-time map provides accurate space information for the system and provides a basis for intelligent decision and navigation. Target object identification tracking is performed on the real-time environment map, including vehicles, pedestrians and the like, and real-time perception of surrounding objects is provided. Important information is provided for driving decision and behavior planning, and traffic safety is improved. And the vehicle position information, the real-time environment map and the object identification tracking data are fused, so that the perception capability of the whole environment is improved. The self-adaptive positioning correction corrects the initial data of the vehicle through the environment-aware fusion data, so that the accurate positioning of the vehicle is improved.

In the embodiment of the invention, various data of the surrounding environment of the vehicle are acquired by using various vehicle-mounted sensors, such as a laser radar, a camera, a radar, a GPS and the like. By these sensors, information such as the position, speed, direction, and position of surrounding objects of the vehicle is acquired. Filters or other signal processing techniques are used to reduce noise in the sensor data. The missing data is filled in using interpolation methods or other filling techniques. The data collected by the various sensors are standardized to ensure that they are on the same scale, avoiding affecting subsequent processing due to scale differences. And extracting accurate position information of the vehicle from the vehicle standard data by utilizing positioning information such as GPS and the like. Vehicle position information data including longitude, latitude, altitude, and the like is generated. And constructing a real-time environment map by using the vehicle position information data, and considering the accuracy and the instantaneity of the map. The map is combined with the vehicle standard data, and the vehicle position and surrounding environment information in the map are updated. Target object recognition, including vehicles and pedestrians, is performed on the real-time environment map using computer vision techniques. The motion of the targets is tracked, and object identification tracking data is generated, including information such as the position, the speed and the like of the targets. And fusing the vehicle position information, the real-time environment map and the object identification tracking data to comprehensively sense the state of the surrounding environment of the vehicle. And a fusion algorithm, such as Kalman filtering or other fusion technologies, is used for synthesizing data from different sources, so that the accuracy and the robustness of sensing are improved. And carrying out self-adaptive positioning correction on the initial data of the vehicle by using the environment-aware fusion data. And generating accurate positioning data of the vehicle, and improving the accuracy of the vehicle on the map so as to better support applications such as navigation, automatic driving and the like.

Preferably, step S2 comprises the steps of: step S21: obtaining initial transmission data of a hydrotreater by using a hydrotreater sensor;

Step S22: performing signal processing on the initial transmission data of the hydrotreater to generate standard transmission data of the hydrotreater, wherein the signal processing comprises data filtering, data downsampling and data normalization;

Step S23: the standard transmission data of the hydrotreater is subjected to hydrotreater state monitoring, so that hydrotreater state monitoring data are generated; abnormality detection is carried out on the hydrotreater state monitoring data by using an abnormality detection algorithm, so that hydrotreater abnormality detection data are generated; performing control strategy generation on the hydrotreater state monitoring data based on the hydrotreater abnormality detection data to obtain a hydrogenation control strategy;

Step S24: performing remote hydrogenation monitoring response on the accurate positioning data of the vehicle based on a hydrogenation control strategy to generate hydrogenation response data; and maintaining the hydrogenation response data through the cloud platform to generate real-time hydrogenation state monitoring control data.

According to the invention, the system can monitor and know the current state and performance of the hydrotreater by acquiring the initial transmission data of the hydrotreater. Noise in sensor data is reduced through a filtering technology, and data quality is improved. Reducing the amount of data helps to increase processing efficiency and reduce storage requirements. The data is standardized, so that the data is ensured to be on the same scale, and the subsequent processing is convenient. The state of the hydrotreater is monitored, including parameters such as temperature, pressure, flow and the like, so as to ensure the normal operation of the hydrotreater. Potential problems or abnormal conditions are identified through an abnormality detection algorithm, and the reliability and safety of the system are improved. The abnormal detection data is utilized to generate a control strategy, so that the abnormal condition of the hydrotreater can be automatically dealt with, and the stability and the safety of the system are improved. The remote hydrogenation monitoring response to the accurate positioning data of the vehicle is realized, and the vehicle is ensured to be hydrogenated when required. Hydrogenation response data: and providing timely and effective hydrogenation control information to meet the hydrogenation requirement of the vehicle. And the cloud platform is utilized to maintain hydrogenation response data, so that the monitoring and management of the whole system are realized. Generating real-time hydrogenation state monitoring control data, so that operators can know the state of the hydrotreater in real time and take necessary control measures.

As an example of the present invention, referring to fig. 2, the step S2 in this example includes: step S21: obtaining initial transmission data of a hydrotreater by using a hydrotreater sensor;

According to the embodiment of the invention, the proper type of sensor is selected according to the characteristics of the hydrotreater and the parameters to be monitored. For example, temperature sensors, pressure sensors, flow sensors, etc. may be used, depending on the hydrotreater parameters that need to be monitored. The selected sensor is correctly installed on the hydrotreater, so that the position and the mode of the sensor can accurately capture the required data. The installation process may need to be customized according to the design of the hydrotreater. The sensor is connected with a data acquisition system. This may involve the use of cables or other means of communication. After connection, calibration of the sensor is performed to ensure that the acquired data accurately reflects the actual situation. The data acquisition system is started and data is read from the sensor. This may be accomplished through the use of an embedded system, data acquisition card, or other specialized hardware device. The acquired data needs to be recorded and stored for subsequent processing and analysis. This may be accomplished by creating a database, using a data recording device, or transmitting to a cloud platform over a network, etc. If real-time monitoring of the status of the hydrotreater is desired, a system can be provided to display the sensor data in real-time. This helps to quickly detect problems that may occur with the hydrotreater.

In the embodiment of the invention, the proper filter type is selected according to the application requirement, such as a low-pass filter, a high-pass filter or a band-pass filter. Parameters of the filter are set, including cut-off frequency, filter order, etc. The selection of these parameters should be based on the signal characteristics and the desired signal smoothness. A filter is applied to the hydrotreater initially transmitted data to remove noise, interference, or unwanted frequency components. The downsampling ratio is determined according to the application requirements and the system performance requirements. Downsampling may reduce the amount of data and improve processing efficiency. And carrying out downsampling operation on the initial transmission data of the hydrotreater. Average value sampling, maximum value sampling and other methods can be adopted to ensure that the downsampled data can still effectively reflect the system state. The normalized range to which the data is mapped is determined, typically [0, 1] or [ -1, 1]. And carrying out normalization operation on the downsampled data, and mapping the data to a determined range. This helps to eliminate scale differences between different sensors, making the data easier to compare and analyze.

In the embodiment of the invention, key characteristics are extracted from the standard transmission data of the hydrotreater, and the characteristics can reflect the operation state of the hydrotreater, such as temperature, pressure, flow and the like. The hydro-generator state monitoring model is built using supervised learning or unsupervised learning methods, such as Support Vector Machines (SVMs), neural networks, decision trees, etc. The model is trained using historical data to enable it to accurately identify different hydrotreater states. Suitable anomaly detection algorithms are selected, such as algorithms based on statistical methods (mean-variance detection), algorithms based on machine learning (isolated forests, gaussian mixture models), etc. The hydro-generator state monitoring data is input into a selected algorithm to identify abnormal data points that are inconsistent with normal operating conditions. And extracting the data points marked as abnormal by the abnormality detection algorithm to form the hydrotreater abnormality detection data. The anomaly data is analyzed to determine the cause and possible effects of the anomaly. Based on the abnormal analysis result, a corresponding hydrotreater control strategy is formulated. This may include adjusting operating parameters, raising alarms, or taking other control actions. The formulated control strategy is applied to the hydrotreater system to ensure that the system can keep stable and safe operation under abnormal conditions.

In the embodiment of the invention, the accurate positioning data of the vehicle is obtained by using an advanced global positioning system (such as GPS), an inertial navigation system or other positioning technologies. Accuracy and real-time performance of positioning data are ensured, so that effective monitoring and response of the vehicle can be carried out. The hydrogenation control strategy generated based on the previous steps is applied to the hydrogenation process of the vehicle. The control strategy may include adjustments to parameters such as hydrogenation rate, hydrogenation pressure, hydrogenation temperature, etc. to meet the needs of the vehicle while ensuring hydrogenation safety. The real-time positioning data of the vehicle is transmitted to the central monitoring system by means of telecommunication, such as the internet. And the central monitoring system responds to the hydrogenation requirement of the vehicle in real time according to the received positioning data and in combination with a preset hydrogenation control strategy. Possible responses include adjusting the hydro-station equipment parameters, controlling the hydro-valve, sending instructions to the vehicle, etc. And recording the result of the remote hydrogenation monitoring response as hydrogenation response data. Including information on the positioning of the vehicle, the implemented control strategy, the hydrogenation status, etc. And uploading the hydrogenation response data to the cloud platform for storage and maintenance. And generating real-time hydrogenation state monitoring control data through analysis and processing of the cloud platform. The real-time monitoring data may be used to generate reports, analyze, optimize control strategies, and support decision-making.

Preferably, step S23 includes the steps of: step S231: the method comprises the steps of monitoring the state of a hydrotreater according to standard transmission data of the hydrotreater to generate monitoring data of the state of the hydrotreater, wherein the monitoring data of the state of the hydrotreater comprise hydrogen pressure data and hydrogen temperature data;

Step S232: performing gas density compression analysis according to the hydrogen pressure data and the hydrogen temperature data to generate hydrogen compression density data; carrying out hydrogen thermal expansion calculation on the hydrogen compression density data by utilizing a hydrogen compression expansion analysis formula to obtain a hydrogen thermal expansion coefficient;

Step S233: comparing the thermal expansion coefficient of the hydrogen with a preset standard thermal expansion threshold, and generating a hydrogen danger signal when the thermal expansion coefficient of the hydrogen is larger than or equal to the preset standard thermal expansion threshold; when the thermal expansion coefficient of the hydrogen is less than a standard thermal expansion threshold value preset in the rain, generating a hydrogen normal signal;

Step S234: hydrogen dangerous signals are subjected to hydrogen addition station abnormality detection, and hydrogen addition station abnormality detection data are generated; carrying out hydrogenation efficiency analysis on the hydrogen normal signal to generate hydrogenation efficiency data; forward hydrogenation speed regulation and control are carried out according to the hydrogenation efficiency data, so that a hydrogenation forward speed control strategy is generated;

step S235: negative hydrogenation speed regulation and control are carried out based on the abnormal detection data, and a hydrogenation negative speed control strategy is generated; and carrying out strategy combination on the hydrogenation positive speed control strategy and the hydrogenation negative speed control strategy to generate a hydrogenation control strategy.

The invention generates the monitoring data of the state of the hydrotreater in real time through monitoring the hydrogen pressure and temperature data. This helps to find and solve problems that may occur in the hydrotreater in time, ensuring the stability and safety of the hydrogenation process. And (5) obtaining the compression density and the thermal expansion coefficient of the hydrogen by utilizing gas density compression analysis and thermal expansion calculation. These data provide a deeper understanding of the hydrogen state and help to develop a reasonable hydrogenation control strategy. And generating a danger signal by comparing the thermal expansion coefficient of the hydrogen with a preset standard thermal expansion threshold. This allows the system to alert in time when a potentially dangerous situation occurs and take the necessary action, such as halting the hydrogenation process. And (3) carrying out hydrogenation efficiency analysis on the hydrogen normal signal, and helping to optimize the hydrogenation process. And generating a forward hydrogenation speed control strategy according to the hydrogenation efficiency data so as to improve the hydrogenation efficiency. Abnormality detection data of the hydrogen addition station is generated by abnormality detection of the hydrogen hazard signal. And generating a negative hydrogenation speed control strategy according to the abnormal detection data so as to cope with possible problems and ensure the system safety. And combining the positive hydrogenation speed control strategy and the negative hydrogenation speed control strategy to generate a comprehensive hydrogenation control strategy. This helps balance the hydrogenation rate and improves the operating efficiency and stability of the overall system.

As an example of the present invention, referring to fig. 3, the step S23 in this example includes: step S231: the method comprises the steps of monitoring the state of a hydrotreater according to standard transmission data of the hydrotreater to generate monitoring data of the state of the hydrotreater, wherein the monitoring data of the state of the hydrotreater comprise hydrogen pressure data and hydrogen temperature data;

In the embodiment of the invention, a hydrogen pressure sensor and a hydrogen temperature sensor are arranged at key positions of the hydrotreater. These sensors are responsible for acquiring real-time hydrogen pressure and temperature data. A data acquisition system is deployed that is responsible for reading data from the hydrogen pressure sensor and the hydrogen temperature sensor on a periodic or real-time basis. The system may be a hardware device or an embedded system. And (3) carrying out standardized processing on the raw data acquired from the sensor, and ensuring the consistency and comparability of the data. This may include unit conversion, calibration, and data format normalization. Algorithms are designed to monitor changes in hydrogen pressure and temperature. When the data change is detected, the system records corresponding state monitoring data and performs real-time processing when needed. And generating the monitoring data of the state of the hydrotreater according to the monitored hydrogen pressure and temperature data. The data may include current hydrogen pressure and temperature values, and may also include trend information over time. A real-time notification or alarm system is integrated to enable timely notification to an operator when an abnormal condition is detected. This helps to quickly respond to potential problems, ensuring the safety of the hydrogenation process. The generated hydrotreater state monitoring data is stored in an accessible database for future analysis, review and verification. This also helps to build up historical data records for system performance assessment.

in the embodiment of the invention, the hydrogen pressure data and the temperature data are converted into the hydrogen density data by using a hydrogen state equation, such as an ideal gas equation or an actual gas equation. This can be achieved by one of the following equations: Wherein, the method comprises the steps of, wherein, Is the pressure of the hydrogen gas and,Is the volume of the hydrogen gas and,Is the mass of the hydrogen gas,Is the constant of the gas which is used to produce the gas,Is the temperature of the hydrogen. And generating hydrogen compression density data according to the hydrogen density data obtained by compression analysis. And ensuring the accuracy and reliability of the data. And calculating the thermal expansion coefficient of the hydrogen by using a thermal expansion analysis formula of the hydrogen. The coefficient of thermal expansion is typically calculated by the following formula: Here, the number of the first and second electrodes, here, Is the coefficient of thermal expansion of the material,Is the volume of the hydrogen gas and,Is the temperature of the hydrogen gas and,Representing the partial derivative of temperature at constant pressure.

In the embodiment of the present invention, the value of the thermal expansion coefficient of hydrogen obtained in the previous step is used. And setting a preset standard thermal expansion threshold according to the system requirements and safety standards. This threshold may be a predetermined constant or dynamically adjusted according to certain conditions. The thermal expansion coefficient of the hydrogen is compared with a preset standard thermal expansion threshold. If the thermal expansion coefficient of the hydrogen is greater than or equal to the preset standard thermal expansion threshold, the hydrogen expansion is beyond the safety range. And generating a hydrogen danger signal when the thermal expansion coefficient of the hydrogen is larger than or equal to a preset standard thermal expansion threshold value. This may be done by a system alarm, display screen information, or other suitable means. And when the thermal expansion coefficient of the hydrogen is smaller than a preset standard thermal expansion threshold value, generating a hydrogen normal signal to indicate that the system is in a normal running state.

In the embodiment of the invention, the hydrogen adding station abnormality detection is started when the hydrogen danger signal is received. This may be achieved by a sensor, monitoring system or other suitable means. Relevant parameters of the hydrogen, such as pressure, temperature, flow, etc., are monitored in real time. Anomaly detection is performed using set safety criteria and thresholds to determine whether the hydrogen addition station is in a dangerous state. Recording the abnormality detection result and the related data to form the abnormality detection data of the hydrogen addition station. This may include information such as a time stamp, the type of anomaly detected, the value of the hydrogen parameter, etc. When a hydrogen normal signal is received, hydrogenation efficiency analysis is started. This may involve monitoring efficiency indicators during the hydrogen filling process, such as hydrogen absorption rate, pressure changes, etc. Data during normal operation of the hydro-station is collected for efficiency analysis. And recording the result of the hydrogenation efficiency analysis to form hydrogenation efficiency data. This may include information on efficiency indicators, hydrogen flow rates, temperature changes, etc. over various time periods. And according to the hydrogenation efficiency data, implementing forward hydrogenation speed regulation. This may include adjusting parameters such as hydrogen injection rate, temperature control, etc. to optimize the hydrogenation process and increase efficiency. And recording the strategy of forward hydrogenation speed regulation to form a hydrogenation forward speed control strategy. This may be used as a reference in future hydrogenation processes to ensure that an efficient hydrogenation rate is maintained during normal operation.

In the embodiment of the invention, the negative hydrogenation signal is identified by utilizing the abnormal detection data of the hydrogen addition station generated in the previous step. This may include detecting conditions of excessive pressure, abnormal temperature, etc. And setting a negative hydrogenation speed regulation threshold and algorithm to ensure timely response when an abnormal condition is detected. And forming a hydrogenation negative speed control strategy according to the negative hydrogenation speed regulation result. This may include slowing the hydrogen injection rate, adjusting temperature control, etc., to ensure that the hydrogenation process is slowed in abnormal situations. Combining the hydrogenation positive speed control strategy and the hydrogenation negative speed control strategy. This may involve defining merge rules to ensure smooth switching and adaptation under different conditions. And recording the combined strategies to form a final hydrogenation control strategy. This may include parameters such as hydrogen injection rate, temperature control, flow regulation, etc. during normal operation and abnormal conditions.

Preferably, the hydrogen compression expansion analysis formula in step S232 is specifically as follows:

in the method, in the process of the invention, Expressed as the coefficient of thermal expansion of hydrogen,Expressed as the volume of hydrogen gas before compression,Expressed as the volume of hydrogen gas after compression,Expressed as the temperature of the hydrogen gas,Expressed as the pressure of the hydrogen gas,Expressed as the pressure in hydrogenThe partial derivative of the volume with respect to hydrogen with respect to temperature under fixed conditions,Represented as an initial value of the pressure,Expressed as the final value of the pressure,Represented as an infinitely small pressure change,Expressed as the ratio of pressure changes.

The invention analyzes and integrates a hydrogen compression expansion analysis formula, wherein the thermal expansion coefficient in the formula is a scale factor for describing the volume change of a substance under the temperature change. By calculating the thermal expansion coefficient, the effect of temperature change of hydrogen at different pressures on the volume can be understood. The initial volume refers to the volume of hydrogen prior to compression. It is an important parameter in the formula for calculating the coefficient of thermal expansion. The volume after compression refers to the final volume of hydrogen during compression. By comparing the initial volume to the compressed volume, the change in volume of hydrogen during compression can be determined. The temperature is a physical quantity of hydrogen, and changing it can affect the volume of hydrogen. The coefficient of thermal expansion in the equation is calculated from the temperature change. The pressure is a physical quantity of hydrogen, and changing it also affects the volume of hydrogen. The integration in the formula is performed at different pressures to take into account the effect of pressure on volume. The ratio of pressure change is the ratio of the minute pressure change in the integral to the pressure. It ensures that integration is based on proportional changes in pressure. When the hydrogen compression expansion analysis formula conventional in the art is used, the thermal expansion coefficient of hydrogen can be obtained, and the thermal expansion coefficient of hydrogen can be calculated more accurately by applying the hydrogen compression expansion analysis formula provided by the invention. The thermal expansion coefficient of the hydrogen in the compression process can be obtained by analyzing and calculating parameters and variables in the formula, so that the response of the hydrogen volume to the temperature and the pressure can be known. This facilitates optimization and control of the hydrogen compression system in engineering and industrial applications.

Preferably, step S3 comprises the steps of: step S31: carrying out communication security verification on the real-time hydrogenation state monitoring control data based on a preset security protocol to obtain communication security verification data; the communication security verification data is utilized to carry out communication key exchange on the hydrogen adding station and the vehicle, and communication key exchange data is generated;

Step S32: constructing a communication channel according to the communication security verification data, and generating a security information communication channel; performing bandwidth allocation on the secure information communication channel through the communication key exchange data to generate communication bandwidth allocation data;

Step S33: carrying out signal transmission data size analysis on the communication bandwidth allocation data to obtain transmission data size capacity data; carrying out data compression on communication bandwidth allocation data according to transmission data volume capacity data to generate communication transmission optimization data;

Step S34: carrying out communication protocol evolution on a preset safety protocol based on communication transmission optimization data to generate adaptive communication protocol data; and carrying out information interaction on the real-time hydrogenation state monitoring control data according to the adaptive communication protocol data to generate hydrogenation interaction information data.

According to the invention, communication security verification is carried out on the real-time hydrogenation state monitoring control data based on the preset security protocol, so that the communication security is ensured. The key exchange with the communication security verification data helps to generate a secure communication key, enhancing confidentiality and integrity of the communication. And constructing a safety information communication channel by using the communication safety verification data, thereby being beneficial to improving the communication efficiency. And bandwidth allocation is carried out on the communication channel through communication key exchange data, so that reasonable utilization of resources is ensured, and communication performance is optimized. And the transmission data volume capacity data is obtained by carrying out signal transmission data volume analysis on the communication bandwidth allocation data, so that the resource allocation is optimized. The data compression is helpful to reduce the transmission data quantity, reduce the communication burden and improve the transmission efficiency. And the communication protocol evolution is carried out on the preset safety protocol based on the communication transmission optimization data, so that the adaptability is improved. Generating the adaptive communication protocol data may ensure that the system is still able to communicate efficiently under different circumstances and requirements.

In the embodiment of the invention, the safety verification is carried out on the real-time hydrogenation state monitoring control data by adopting an advanced encryption algorithm. And according to a preset safety protocol specification, realizing the communication safety verification of the data. The appropriate key exchange protocol is selected to ensure that the kiosk and vehicle are able to securely generate the communication key. And constructing a safety information communication channel based on the communication safety verification data, and ensuring the safety of the communication channel. And the communication key exchange data is utilized to carry out bandwidth allocation on the communication channel, so that reasonable utilization of resources is ensured. The communication bandwidth allocation data is subjected to signal transmission data quantity analysis using an appropriate analysis tool to obtain transmission data quantity capacity data. And selecting a proper data compression algorithm to compress the communication bandwidth allocation data according to the transmission data volume capacity data. Evolution is carried out on a preset safety protocol based on communication transmission optimization data, so that the protocol can be ensured to adapt to new communication requirements. According to the evolved protocol, an adaptive communication protocol is implemented to provide better communication performance in different situations. And formulating an information interaction protocol according to the adaptive communication protocol data to ensure effective interaction of the real-time hydrogenation state monitoring control data. And generating hydrogenation interaction information data by utilizing the adaptive communication protocol data so as to meet the requirements of real-time monitoring and control.

Preferably, step S4 comprises the steps of: step S41: carrying out real-time traffic condition sensing analysis through the environment sensing fusion data to generate traffic condition information data;

Step S42: performing hydrogenation path planning based on traffic condition information data, vehicle accurate positioning data and real-time hydrogenation state monitoring control data to generate hydrogenation path planning data; intelligent path selection is carried out on hydrogenation path planning data according to a decision tree algorithm, and path selection data is generated;

Step S43: according to the hydrogenation energy consumption analysis formula, carrying out energy consumption analysis on the vehicle accurate positioning data, the real-time hydrogenation state monitoring control data and the path selection data to generate energy consumption analysis data; dynamic hydrogenation path adjustment is carried out on the path selection data by utilizing the energy consumption analysis data, so as to generate hydrogenation path adjustment data;

Step S44: and performing autonomous hydrogenation butt joint on the hydrogenation station and the vehicle through the hydrogenation path adjustment data so as to execute an automatic unmanned hydrogenation instruction.

According to the invention, through real-time traffic condition sensing, the system can generate more accurate traffic condition information, so that the vehicle hydrogenation path planning is optimized, and congestion and delay are avoided. The hydrogenation path planning is intelligently selected by utilizing a decision tree algorithm, and the system can make more intelligent decisions according to a plurality of factors (traffic conditions, vehicle positioning and the like) so as to improve hydrogenation efficiency. Through energy consumption analysis, the system can more effectively utilize energy, considering vehicle states and path selection, to reduce energy consumption. According to the energy consumption analysis data, the system can adjust the hydrogenation path in real time, so that the optimal energy utilization efficiency of the vehicle in the running process is ensured. The system can realize autonomous hydrogenation butt joint of the hydrogenation station and the vehicle through the hydrogenation path adjustment data, execute unmanned hydrogenation instructions and improve the automation degree of the hydrogenation process.

As an example of the present invention, referring to fig. 4, the step S4 includes, in this example: step S41: carrying out real-time traffic condition sensing analysis through the environment sensing fusion data to generate traffic condition information data;

In the embodiment of the invention, various environment sensing sensors, such as cameras, radars, lidars, vehicle-mounted sensors and the like, are deployed in the traffic related area to acquire real-time traffic environment data. The data obtained from the different sensors may be diverse, including images, radar signals, vehicle positioning, and the like. And (3) data fusion is carried out, and the data of different sensors are integrated into a comprehensive data set. And processing and analyzing the fused data by utilizing a real-time data processing technology. This may include target detection, vehicle tracking, road condition analysis, etc. Traffic conditions, including road congestion, intersection status, accident conditions, etc., are identified by analyzing real-time data by developing or adopting traffic condition sensing algorithms. Based on the result of the perception algorithm, data containing real-time traffic condition information is generated. Such data may include traffic flow, vehicle speed, congestion level, etc. The generated traffic condition information data is transmitted to other parts of the system for subsequent path planning and decision-making. At the same time, the data may need to be stored for later analysis and history. The implementation of S41 is integrated with the whole hydrogenation system, so that the real-time traffic condition information can be ensured to effectively provide support for the subsequent steps.

In the embodiment of the present invention, by acquiring real-time traffic condition information data, this may be the data generated by step S41. The accurate positioning data of the vehicle can be obtained by using Global Positioning System (GPS) and other technologies. And acquiring real-time hydrogenation state monitoring control data, including information such as the state and availability of the hydrogenation station. And designing a path planning algorithm by utilizing the traffic condition information data and the vehicle accurate positioning data, and generating hydrogenation path planning data by considering factors such as road conditions, real-time traffic conditions, vehicle positions and the like. Considering the location of the docking station, it is ensured that the planned path contains the appropriate docking station to meet the docking requirements of the vehicle. And performing intelligent path selection on the generated hydrogenation path planning data by using a decision tree algorithm. The decision tree may take into account a number of factors such as traffic conditions, availability of the docking station, current state of the vehicle, etc. The decision tree model is trained, taking into account historical data and optimization objectives, to enable the model to make intelligent path selection. And generating final path selection data according to the output of the decision tree algorithm. This may include information about the road through which the selection was made, the order of the hydrogen stations, etc. Optimization objectives, such as shortest time, shortest distance, least traffic congestion, etc., are considered to meet user demand and system performance. The path selection data is updated periodically to reflect changes in traffic conditions and other real-time information, taking real-time into account. Path feedback is provided to the vehicle driver or vehicle control system to ensure that the driver is able to follow the planned path. And the implementation of the S42 is integrated with the whole hydrogenation system, so that hydrogenation path planning and path selection can be cooperated with other systems, and comprehensive hydrogenation service is realized.

In the embodiment of the invention, key factors in vehicle accurate positioning data, real-time hydrogenation state monitoring control data and path selection data are considered by formulating an energy consumption analysis formula. This may include vehicle type, speed, load, hydrogenation status, routing, etc. The accurate positioning data, the real-time hydrogenation state monitoring control data and the path selection data of the vehicle are preprocessed, and the consistency and the accuracy of the data are ensured. The data is normalized or normalized for better comparison and processing in the energy expenditure analysis. And analyzing the preprocessed data by using a designed energy consumption analysis formula, and calculating the energy consumption of the vehicle on a specific path. Factors such as actual driving conditions, vehicle performance parameters, and hydrogenation efficiency of the hydrogenation station are considered. Based on the result of the energy consumption analysis, energy consumption analysis data is generated. This may include information on the energy consumption per path segment or the entire trip, the number of hydrogenations expected, etc. And dynamically adjusting the path selection data by utilizing the energy consumption analysis data. This may include adjusting the path to reduce energy consumption, selecting a more economical hydrogenation station for hydrogenation, etc. Taking into account real-time traffic conditions, vehicle conditions and availability of the docking station, it is ensured that the adjusted path still meets user requirements and system performance. And generating hydrogenation path adjustment data according to the dynamic hydrogenation path adjustment result. This may include updated routing, adjusted docking station order, etc. Feedback of the path adjustment is provided to the vehicle driver or vehicle control system to ensure that the adjusted path can be performed in a timely manner. The implementation of S43 is integrated with the whole hydrogenation system, so that the energy consumption analysis and the dynamic path adjustment can work cooperatively with other systems, and more intelligent hydrogenation service is provided.

In an embodiment of the present invention, the communication protocol between the docking station and the vehicle is determined so that they can exchange data and instructions. Common communication protocols include internet of things protocol, CAN bus protocol, and the like. The safe transmission of the hydrogenation path adjustment data is realized, and the reliable transmission of information between the hydrogenation station and the vehicle is ensured. This may include using encryption techniques and authentication mechanisms to protect the integrity and confidentiality of the data. An autonomous hydrogenation protocol is formulated defining the operating steps and command formats between the hydrogenation station and the vehicle. Ensuring that the protocol contains the necessary instructions to initiate hydrogenation, stop hydrogenation, adjust hydrogenation rate, etc. Sensors and actuators on the vehicle are integrated to achieve autonomous hydrogenation. This may include actuators, hydrogenation sensors, etc. involving the vehicle hydrogenation ports. An unmanned hydrogenation control system is designed, and the system can execute corresponding autonomous hydrogenation instructions according to hydrogenation path adjustment data. This may include controlling movement of the vehicle, controlling operation of the docking station apparatus, and so forth. In view of safety issues, measures are taken to cope with emergency situations such as emergency stops, hydrogenation failures, etc. Ensuring that the system has a safe emergency shutdown and communication mechanism. Remote monitoring and management functions are integrated so that operators can monitor and manage the autonomous hydrogenation process. This may include remote diagnostics, remote start-stop control, etc. And (3) performing system tests to verify the reliability and stability of the autonomous hydrogenation system in different scenes. Ensuring that the system can normally operate and meet the safety requirement in practical application.

Preferably, step S42 includes the steps of: step S421: carrying out vehicle speed statistics on the vehicle accurate positioning data by utilizing the traffic condition information data to obtain vehicle speed data; converting the waveform diagram of the vehicle speed data to generate a waveform diagram of the vehicle speed;

Step S422: waveform curvature analysis is carried out on the vehicle speed waveform diagram, and vehicle motion fluctuation data are generated; carrying out data fusion according to the vehicle motion fluctuation data and the real-time hydrogenation state monitoring control data to generate road condition data; dividing the road condition data into data sets to generate a model training set and a model testing set;

Step S423: model training is carried out on the model training set through a support vector machine algorithm, and a hydrogenation path planning pre-model is generated; performing model test on the hydrogenation path planning pre-model by using a model test set to generate a hydrogenation path planning model; importing the road condition data into a hydrogenation path planning model to carry out path planning, and generating hydrogenation path planning data;

Step S424: carrying out path selection on hydrogenation path planning data according to a decision tree algorithm to generate hydrogenation path data; performing efficiency evaluation on the hydrogenation path data to generate path efficiency evaluation data; and performing intelligent path sorting on the hydrogenation path data through the path efficiency evaluation data to generate path selection data.

According to the invention, through the steps of vehicle speed statistics, waveform diagram conversion, waveform curvature analysis and the like, the system can accurately monitor and analyze the motion state of the vehicle, so that accurate road condition data is generated. This helps to achieve a more accurate hydrogenation path planning. And fusing the vehicle motion fluctuation data with the real-time hydrogenation state monitoring control data to generate more comprehensive road condition data. The data fusion can improve the understanding and predicting ability of the system to road conditions. And training the model training set through a support vector machine algorithm to generate a hydrogenation path planning pre-model. The machine learning model can improve the prediction accuracy of future road conditions by learning historical data, thereby improving the effect of hydrogenation path planning. And the decision tree algorithm is utilized to carry out path selection on the hydrogenation path planning data, and then the paths are intelligently ordered through the efficiency evaluation data, so that the selected paths can be ensured to be balanced in efficiency and performance. This helps to increase the efficiency of the overall hydrogenation process. Because the system utilizes the real-time data to carry out path planning and selection in S42, the system has real-time adaptability, can make instant adjustment according to the actual condition of the vehicle and the road condition, and improves the flexibility and the strain capacity of the whole system.

In the embodiment of the invention, the accurate positioning data of the vehicle is obtained by using the traffic condition information data. The vehicle speed per hour is calculated based on the positioning data, and GPS data or other sensor data may be used. And converting the waveform diagram of the vehicle speed data. The time rate data may be converted to a time rate waveform map using signal processing techniques such as fourier transforms. Waveform curvature analysis is performed on the vehicle speed waveform diagram. The curvature of the waveform can be calculated using a mathematical algorithm to learn the wave characteristics of the vehicle motion. And fusing the vehicle motion fluctuation data with the real-time hydrogenation state monitoring control data. And combining the fused data to generate road condition data, wherein the vehicle motion and the hydrogenation state can be comprehensively considered by adopting an algorithm. And carrying out data set division on the road condition data. The method is divided into a model training set and a model testing set, and the model is ensured to have generalization capability. Model training is performed on the model training set using a support vector machine algorithm. The model parameters are adjusted to achieve optimal performance. And testing the hydrogenation path planning pre-model by using a model test set. The accuracy and generalization ability of the model were evaluated. And importing the road condition data into a hydrogenation path planning model to carry out path planning. Optimization algorithms can be used, e.g.And (5) an algorithm, namely generating hydrogenation path planning data. And carrying out path selection on the hydrogenation path planning data according to a decision tree algorithm. The decision tree may take into account a number of factors, such as road conditions, vehicle performance, etc. And performing performance evaluation on the generated hydrogenation path data. The indexes such as time efficiency, energy consumption and the like can be considered. And intelligently sequencing hydrogenation path data through path efficiency evaluation data. The use of a sorting algorithm ensures that the selected path has advantages in both efficiency and performance.

Preferably, the hydrogenation energy consumption analysis formula in step S43 is specifically as follows:

in the method, in the process of the invention, Expressed as the amount of energy consumed by the vehicle over a period of time,Represented as a starting point of time,Indicated as the end point of the time,Expressed as the energy consumption coefficient of the path,Represented as the speed of the vehicle,Represented as the distance travelled by the vehicle,Represented as the mass of the vehicle,Expressed as the fuel consumption rate of the vehicle,Expressed as the density of the fuel in question,Represented as the point in time when the vehicle is running.

The invention analyzes and integrates a hydrogenation energy consumption analysis formula, and kinetic energy consumption items in the formulaRepresents the energy consumed by the vehicle during travel due to the change in kinetic energy. Wherein,The energy consumption coefficient of the path reflects the influence of the characteristics of the path on the energy consumption. By adjustingCan optimize path selection to reduce energy consumption. Friction and drag consumption termRepresents the energy consumed by the vehicle during running due to friction and drag. Wherein,Is the mass of the vehicle and,Is the speed of the vehicle and,Is the fuel consumption rate of the vehicle. By controlling the mass, speed and fuel consumption of the vehicle, the energy loss due to friction and drag can be reduced. Fuel mass consumption termRepresenting the energy consumed by the vehicle due to the reduced fuel mass. Wherein,Is a coefficient for adjusting the influence of fuel quality on energy consumption,Is the point in time at which the vehicle is running,Is the density of the fuel. By controlling the density of the fuel and the running time of the vehicle, the use efficiency of the fuel can be optimized, and the energy consumption can be reduced. When the conventional hydrogenated energy consumption analysis formula in the field is used, the energy consumed by the vehicle in a period of time can be obtained, and the energy consumed by the vehicle in a period of time can be more accurately calculated by applying the hydrogenated energy consumption analysis formula provided by the invention. By comprehensively considering the three energy consumption items and adjusting according to specific parameter values and weights, the energy consumption of the vehicle can be analyzed and optimized. The energy-saving and emission-reducing vehicle has the beneficial effects of improving the energy utilization efficiency of the vehicle, reducing the energy consumption and emission and realizing energy conservation and emission reduction.

The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An automated unmanned hydrogenation process for operating on a hydrogenation station and a vehicle comprising the steps of:

Step S1: acquiring initial data of a vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;

2. The automated unmanned hydrogenation process of claim 1, wherein step S1 comprises the steps of:

Step S11: acquiring vehicle initial data by using a vehicle-mounted sensor;

3. The automated unmanned hydrogenation process of claim 1, wherein step S2 comprises the steps of:

Step S21: obtaining initial transmission data of a hydrotreater by using a hydrotreater sensor;

4. The automated unmanned hydrogenation process of claim 3, wherein step S23 comprises the steps of:

step S231: the method comprises the steps of monitoring the state of a hydrotreater according to standard transmission data of the hydrotreater to generate monitoring data of the state of the hydrotreater, wherein the monitoring data of the state of the hydrotreater comprise hydrogen pressure data and hydrogen temperature data;

5. The automated unmanned hydrogenation process of claim 4, wherein the hydrogen compression expansion analysis formula in step S232 is as follows:

in the method, in the process of the invention, Expressed as the coefficient of thermal expansion of hydrogen,/>Expressed as hydrogen volume before compression,/>Expressed as volume of hydrogen after compression,/>Expressed as the temperature of hydrogen,/>Expressed as the pressure of hydrogen,/>Expressed as pressure at hydrogen/>Partial derivative of the volume of hydrogen with respect to temperature under fixed conditions,/>Expressed as an initial value of pressure,/>Expressed as the final value of the pressure,Expressed as infinitesimal pressure change,/>Expressed as the ratio of pressure changes.

6. The automated unmanned hydrogenation process of claim 1, wherein step S3 comprises the steps of:

step S31: carrying out communication security verification on the real-time hydrogenation state monitoring control data based on a preset security protocol to obtain communication security verification data; the communication security verification data is utilized to carry out communication key exchange on the hydrogen adding station and the vehicle, and communication key exchange data is generated;

step S33: analyzing the signal transmission data quantity to obtain transmission data quantity capacity data; carrying out data compression on communication bandwidth allocation data according to transmission data volume capacity data to generate communication transmission optimization data;

7. The automated unmanned hydrogenation process of claim 1, wherein step S4 comprises the steps of:

Step S41: carrying out real-time traffic condition sensing analysis through the environment sensing fusion data to generate traffic condition information data;

8. The automated unmanned hydrogenation process of claim 7, wherein step S42 comprises the steps of:

step S421: carrying out vehicle speed statistics on the vehicle accurate positioning data by utilizing the traffic condition information data to obtain vehicle speed data; converting the waveform diagram of the vehicle speed data to generate a waveform diagram of the vehicle speed;

9. The automated unmanned hydrogenation process of claim 7, wherein the analysis formula for the energy consumption of hydrogenation in step S43 is as follows:

in the method, in the process of the invention, Expressed as the amount of energy consumed by the vehicle over a period of time,/>Expressed as starting point of time,/>Expressed as the ending point of time,/>Expressed as energy consumption coefficient of the path,/>Expressed as speed of the vehicle,/>Represented as the distance travelled by the vehicle,Expressed as mass of the vehicle,/>Expressed as fuel consumption of the vehicle,/>Expressed as density of fuel,/>Represented as the point in time when the vehicle is running.

10. An automated unmanned hydrogenation system for performing the automated unmanned hydrogenation method of claim 1, the automated unmanned hydrogenation system comprising:

The environment sensing module is used for acquiring initial data of the vehicle; extracting vehicle position information from the vehicle initial data to generate vehicle position information data; carrying out real-time environment map construction based on vehicle position information data and vehicle standard data to generate a real-time environment map; performing target object identification tracking on the real-time environment map to generate object identification tracking data; performing environment perception fusion on vehicle position information data, a real-time environment map and object identification tracking data to generate environment perception fusion data;