CN120914289A - Hydrogen energy vehicle safety pre-warning system supported by Internet of vehicles big data - Google Patents

Hydrogen energy vehicle safety pre-warning system supported by Internet of vehicles big data

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Publication number
CN120914289A
CN120914289A CN202511439313.1A CN202511439313A CN120914289A CN 120914289 A CN120914289 A CN 120914289A CN 202511439313 A CN202511439313 A CN 202511439313A CN 120914289 A CN120914289 A CN 120914289A
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China
Prior art keywords
data
hydrogen
value
leakage
preset
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Granted
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CN202511439313.1A
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Chinese (zh)
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CN120914289B (en
Inventor
刘国柱
路遥
朱久春
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Hydrogen Power Beijing Technology Service Co ltd
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Hydrogen Power Beijing Technology Service Co ltd
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Priority to CN202511439313.1A priority Critical patent/CN120914289B/en
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Publication of CN120914289B publication Critical patent/CN120914289B/en
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/04664—Failure or abnormal function
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B60L3/0023—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train
    • B60L3/0053—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train relating to fuel cells
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B60L3/12—Recording operating variables ; Monitoring of operating variables
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
    • B60L58/30—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling fuel cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0036—General constructional details of gas analysers, e.g. portable test equipment concerning the detector specially adapted to detect a particular component
    • G01N33/005—H2
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
    • G08B29/18—Prevention or correction of operating errors
    • G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
    • G08B29/188—Data fusion; cooperative systems, e.g. voting among different detectors
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0432—Temperature; Ambient temperature
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
    • H01M8/0438—Pressure; Ambient pressure; Flow
    • H01M8/04425—Pressure; Ambient pressure; Flow at auxiliary devices, e.g. reformers, compressors, burners
    • H—ELECTRICITY
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    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
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    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
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    • H01M8/04313—Processes for controlling fuel cells or fuel cell systems characterised by the detection or assessment of variables; characterised by the detection or assessment of failure or abnormal function
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    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M8/00—Fuel cells; Manufacture thereof
    • H01M8/04—Auxiliary arrangements, e.g. for control of pressure or for circulation of fluids
    • H01M8/04298—Processes for controlling fuel cells or fuel cell systems
    • H01M8/04992—Processes for controlling fuel cells or fuel cell systems characterised by the implementation of mathematical or computational algorithms, e.g. feedback control loops, fuzzy logic, neural networks or artificial intelligence
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    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M2250/00—Fuel cells for particular applications; Specific features of fuel cell system
    • H01M2250/20—Fuel cells in motive systems, e.g. vehicle, ship, plane

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Abstract

本发明涉及车辆泄漏检测技术领域，尤其涉及一种车联网大数据支持的氢能车辆安全预警系统，包括：数据采集模块；用以根据目标氢能车辆的运行数据对应的比对数据数量与预设比对数据数量的数量比对值确定根据匹配系数以及运行参数比对值直接选取分析数据或根据高频影响参数匹配度补充选取分析数据的数据选取模块；用以根据比对数据数量确定根据泄漏车辆数据占比或泄漏车辆数据比对值确定氢气传感器数量的数量分析模块；用以根据高频泄漏位置数量与氢气传感器数量的数量差值以及覆盖距离阈值确定根据关联位置组合或泄漏频次参考值确定氢气传感器安装位置的位置分析模块；泄漏预警模块。本发明能够提高氢泄漏预警的准确程度。

This invention relates to the field of vehicle leak detection technology, and more particularly to a hydrogen fuel cell vehicle safety early warning system supported by vehicle-to-everything (V2X) big data. The system includes: a data acquisition module; a data selection module for determining the number of analysis data based on the number of comparison data corresponding to the target hydrogen fuel cell vehicle's operating data and a preset number of comparison data, either by directly selecting analysis data based on a matching coefficient and the comparison value of operating parameters, or by supplementing the selection of analysis data based on the matching degree of high-frequency influence parameters; a quantity analysis module for determining the number of hydrogen sensors based on the number of comparison data, the proportion of leaking vehicle data, or the comparison value of leaking vehicle data; a location analysis module for determining the installation location of hydrogen sensors based on the difference between the number of high-frequency leak locations and the number of hydrogen sensors, and a coverage distance threshold, as well as a combination of associated locations or a leak frequency reference value; and a leak early warning module. This invention can improve the accuracy of hydrogen leak early warning.

Description

Hydrogen energy vehicle safety pre-warning system supported by Internet of vehicles big data
Technical Field
The invention relates to the technical field of vehicle leakage detection, in particular to a hydrogen energy vehicle safety early warning system supported by Internet of vehicles big data.
Background
Because serious consequences may be caused after hydrogen leaks and burns, hydrogen energy safety becomes a bottleneck restricting the development of hydrogen energy automobiles more and more, the existing vehicle-mounted monitoring means generally adopts hydrogen sensors with fixed quantity and fixed positions for monitoring, and the hydrogen sensors cannot be dynamically optimized according to vehicle working condition differences by combining with the big data of the internet of vehicles, so that the accuracy of hydrogen leakage early warning is poor, and therefore, how to improve the accuracy of hydrogen leakage early warning based on the big data of the internet of vehicles is a problem to be solved urgently by technicians in the field.
The Chinese patent publication No. CN117638143A discloses a vehicle fuel cell hydrogen safety system based on cloud diagnosis, which comprises a hydrogen safety management strategy and a hydrogen safety device connected with a hydrogen supply system, wherein the hydrogen safety device comprises a sensor for collecting data of the hydrogen supply system, a hydrogen system controller connected with the sensor and a vehicle-mounted TThe system comprises a BOX system, a hydrogen system controller, a hydrogen safety management strategy and a vehicle-mounted T, wherein the BOX system is used for judging whether an emergency fault and a corresponding emergency fault type exist based on a sensor, the hydrogen safety management strategy outputs corresponding emergency control instructions according to a fault code and a fault grade corresponding to the emergency fault type, the emergency control instructions comprise emergency stop, fault stop or warning, and the vehicle-mounted TThe BOX system transmits the sensor signal to the cloud platform through the CAN communication circuit, the cloud platform pushes the analyzed non-emergency fault information to the user side equipment, and the user side equipment sends out early warning and alarm signals to control the hydrogen inlet electromagnetic valve of the vehicle so as to cut off the hydrogen supply of the fuel cell. However, the scheme has the following problems that the data acquisition is carried out only by depending on fixed sensors, the number, the positions and the acquisition period of the sensors cannot be dynamically optimized according to actual application scenes, and the accuracy of leakage early warning is poor.
Disclosure of Invention
Therefore, the invention provides a hydrogen energy vehicle safety early warning system supported by Internet of vehicles big data, which is used for solving the problem that in the prior art, the number, the position and the acquisition period of sensors cannot be dynamically optimized according to actual application scenes by only relying on fixed sensors to acquire data, so that the accuracy of leakage early warning is poor.
In order to achieve the above purpose, the present invention provides a hydrogen energy vehicle safety pre-warning system supported by internet of vehicles big data, comprising:
the data acquisition module is used for acquiring the operation data of the target hydrogen energy vehicle and the vehicle data of the Internet of vehicles;
The data selection module is connected with the data acquisition module and used for determining the quantity comparison value of the quantity of the comparison data corresponding to the operation data of the target hydrogen energy vehicle and the quantity of the preset comparison data and directly selecting the analysis data according to the matching coefficient and the operation parameter comparison value or supplementing and selecting the analysis data according to the matching degree of the high-frequency influence parameters;
The quantity analysis module is respectively connected with the data acquisition module and the data selection module and is used for determining the quantity of the hydrogen sensors according to the ratio of the leaked vehicle data or the comparison value of the leaked vehicle data according to the comparison data quantity;
the position analysis module is respectively connected with the data acquisition module and the number analysis module and is used for determining the installation position of the hydrogen sensor according to the number difference value between the number of high-frequency leakage positions and the number of the hydrogen sensors and the coverage distance threshold value;
the leakage early warning module is respectively connected with the data acquisition module and the data selection module and is used for determining whether to directly send leakage early warning to a user according to the hydrogen concentration threshold value determined by each hydrogen sensor or determining whether to send early warning to the user according to the risk evaluation value of analysis data corresponding to the operation data of the target hydrogen energy vehicle.
Further, the data selection module responds to the quantity comparison value of the quantity of comparison data corresponding to the running data of the target hydrogen energy vehicle and the quantity of preset comparison data, wherein the quantity comparison value is larger than or equal to the preset quantity comparison value, and the comparison data is directly used as analysis data;
The comparison data is vehicle data, wherein a matching reference value corresponding to the operation data of the target hydrogen energy vehicle is larger than a preset matching reference value, and an operation parameter comparison value is smaller than a preset operation parameter comparison value.
Further, the data selection module responds to the comparison value that the comparison data quantity corresponding to the operation data of the target hydrogen energy vehicle is smaller than the preset comparison value, and the analysis data is selected in a complementary mode according to the high-frequency influence parameter matching degree.
Further, the quantity analysis module responds to the comparison data quantity being greater than or equal to the preset comparison data quantity, and determines the quantity of hydrogen sensors according to the ratio of the leaked vehicle data;
the number of hydrogen sensors is in positive correlation with the leaky vehicle data duty cycle.
Further, the quantity analysis module responds to the operation parameter comparison value being smaller than a preset operation parameter comparison value, and the quantity of the hydrogen sensors is determined according to the leakage vehicle data comparison value;
The number of the hydrogen sensors is in positive correlation with the comparison value of the leaked vehicle data.
Further, the position analysis module responds that the difference between the number of the high-frequency leakage positions and the number of the hydrogen sensors is smaller than or equal to the standard number, and the coverage distance threshold is larger than or equal to the preset coverage distance threshold, and then the hydrogen sensor installation position is determined according to the leakage frequency reference value.
Further, the position analysis module responds to the fact that the difference value between the number of the high-frequency leakage positions and the number of the hydrogen sensors is larger than the standard number or the coverage distance threshold value is smaller than the preset coverage distance threshold value, and then the hydrogen sensor installation position is determined according to the associated position combination.
Further, the confirmation method of the association position combination includes:
if the height identity of the leakage position is greater than or equal to the preset height identity of the leakage position, determining an associated position combination according to the shortest distance;
If the height identity of the leakage positions is smaller than the preset height identity of the leakage positions, determining the associated position combination according to the height difference and the height influence distance.
Further, the leakage early warning module responds that the hydrogen concentration threshold value is larger than or equal to a preset hydrogen concentration threshold value, and then leakage early warning is directly sent to a user.
Further, the leakage early warning module responds to the fact that the hydrogen concentration threshold value is smaller than a preset hydrogen concentration threshold value, and whether early warning is sent to a user is determined according to the risk assessment value of analysis data corresponding to the operation data of the target hydrogen energy vehicle;
If the risk assessment value is greater than or equal to the preset risk assessment value, an early warning is sent to the user;
if the risk assessment value is smaller than the preset risk assessment value, an early warning is not required to be sent to the user.
Compared with the prior art, the method has the beneficial effects that in the technical scheme, the sufficient degree of the comparison data is effectively reflected by the quantity comparison value of the comparison data corresponding to the running data of the target hydrogen energy vehicle and the preset comparison data quantity, so that different analysis data selection modes are adaptively selected according to the quantity comparison value, the selection of the analysis data is more in line with the actual application scene, the comparison data is directly used as the analysis data when the comparison data quantity is sufficient, the analysis data is ensured to be highly consistent with the running state of the target vehicle, and when the comparison data is insufficient, the analysis data is selected through the supplement of the high-frequency influence parameter matching degree, so that the reliability when the comparison data is scarce can be remarkably improved, and the accuracy degree of leakage early warning is improved.
Furthermore, the leakage risk of the target hydrogen energy vehicle is effectively reflected by the comparison data quantity, and the quantity of the hydrogen sensors is adaptively determined according to the comparison data quantity and the ratio of the leakage vehicle data or the comparison value of the leakage vehicle data, so that the quantity of the hydrogen sensors is dynamically matched with the actual leakage risk of the vehicle, the cost waste caused by excessive arrangement is avoided, the monitoring blind area is eliminated, and the accurate and economic early warning of hydrogen leakage is realized.
Further, the invention effectively reflects the deviation condition of the number of the high-frequency leakage positions and the number of the hydrogen sensors and the coverage effectiveness degree of the high-frequency leakage positions through the number difference value of the number of the high-frequency leakage positions and the number of the hydrogen sensors and the coverage distance threshold value, thereby adaptively selecting different mounting modes of the positions of the hydrogen sensors, leading the mounting of the hydrogen sensors to be more in line with the actual application scene, and improving the early warning precision and the system economy
Further, the response time of hydrogen leakage can be improved by arranging a plurality of hydrogen sensors and directly sending the leakage early warning to the user according to the hydrogen concentration threshold value, whether the early warning is sent to the user or not is determined according to the danger evaluation value of the analysis data corresponding to the operation data of the target hydrogen energy vehicle, the early warning of the pre-leakage can be sent to the user in advance before the hydrogen leakage, the expansion of accidents is avoided, and the reliability and the accuracy of the early warning are further effectively improved.
Drawings
FIG. 1 is a block diagram of a hydrogen energy vehicle safety pre-warning system supported by Internet of vehicles big data;
FIG. 2 is a flow chart of determining a number comparison value of the number of comparison data corresponding to the operation data of the target hydrogen energy vehicle and the number of preset comparison data according to the matching coefficient and the operation parameter comparison value to directly select analysis data or to supplement and select analysis data according to the matching degree of the high-frequency influence parameters;
FIG. 3 is a flow chart of determining the number of hydrogen sensors based on the comparison data number and the leak vehicle data duty cycle or leak vehicle data comparison value in accordance with the present invention;
Fig. 4 is a flowchart of the present invention for determining the installation position of the hydrogen sensor based on the combination of the associated positions or the reference value of the leakage frequency according to the number difference between the number of high-frequency leakage positions and the number of hydrogen sensors and the coverage distance threshold.
Detailed Description
The invention will be further described with reference to examples for the purpose of making the objects and advantages of the invention more apparent, it being understood that the specific examples described herein are given by way of illustration only and are not intended to be limiting.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Referring to fig. 1 to 4, the present invention provides a hydrogen energy vehicle safety pre-warning system supported by internet of vehicles big data, comprising:
the data acquisition module is used for acquiring the operation data of the target hydrogen energy vehicle and the vehicle data of the Internet of vehicles;
The data selection module is connected with the data acquisition module and used for determining the quantity comparison value of the quantity of the comparison data corresponding to the operation data of the target hydrogen energy vehicle and the quantity of the preset comparison data and directly selecting the analysis data according to the matching coefficient and the operation parameter comparison value or supplementing and selecting the analysis data according to the matching degree of the high-frequency influence parameters;
The quantity analysis module is respectively connected with the data acquisition module and the data selection module and is used for determining the quantity of the hydrogen sensors according to the ratio of the leaked vehicle data or the comparison value of the leaked vehicle data according to the comparison data quantity;
the position analysis module is respectively connected with the data acquisition module and the number analysis module and is used for determining the installation position of the hydrogen sensor according to the number difference value between the number of high-frequency leakage positions and the number of the hydrogen sensors and the coverage distance threshold value;
the leakage early warning module is respectively connected with the data acquisition module and the data selection module and is used for determining whether to directly send leakage early warning to a user according to the hydrogen concentration threshold value determined by each hydrogen sensor or determining whether to send early warning to the user according to the risk evaluation value of analysis data corresponding to the operation data of the target hydrogen energy vehicle.
The application scene of the invention is hydrogen leakage early warning of the hydrogen energy automobile, and the target hydrogen energy automobile is a hydrogen fuel cell automobile needing safety early warning;
the invention also comprises a plurality of hydrogen sensors which are respectively connected with the quantity analysis module, the position analysis module and the leakage early warning module and are used for collecting the hydrogen concentration in real time;
The invention is provided with a continuous cycle monitoring period, the time length of the monitoring period can be set according to the requirement of a user, the larger the requirement of the user on the monitoring precision is, the smaller the time length of the monitoring period is, the value of the monitoring period is provided, the monitoring period is 30min, the current monitoring period before the hydrogen sensor is installed is recorded as the monitoring period before the hydrogen sensor is installed, the current monitoring period after the hydrogen sensor is installed is recorded as the monitoring period after the hydrogen sensor is installed, and the running data related to the quantity analysis module and the position analysis module are running data corresponding to the monitoring period before the hydrogen sensor is installed, and the running data related to the leakage early warning module is running data corresponding to the monitoring period after the hydrogen sensor is installed;
The operation data are values of operation parameters corresponding to each time point in a single monitoring period, the operation parameters comprise, but are not limited to, hydrogen fuel cell temperature, hydrogen fuel cell voltage, hydrogen storage tank pressure and hydrogen supply pipeline pressure, each operation parameter is monitored by an NTC thermistor, an isolated voltage sensor, a piezoresistive pressure sensor and a diaphragm pressure sensor respectively, the position of each sensor can be set by a user according to actual requirements, details are not repeated, the time point in the operation data is set by taking the starting time of the single monitoring period as a starting point, setting an interval point every 1min in time sequence, and recording the starting point and each interval point as time points;
The vehicle network is a platform for storing a plurality of vehicle data, the type of the vehicle data comprises leaked vehicle data and non-leaked vehicle data, the single leaked vehicle data comprises operation use data corresponding to a single hydrogen fuel battery vehicle with hydrogen leakage and a leakage position, the leakage position comprises but not limited to a hydrogen storage tank body, a tank body valve, a pressure reducing valve and an exhaust pipeline, the non-leaked vehicle data comprises operation use data corresponding to a single hydrogen fuel battery vehicle without hydrogen leakage, the operation use data corresponding to the single hydrogen fuel battery vehicle is the value of an operation parameter corresponding to each time point in the running time of the hydrogen fuel battery monitored in real time along with the use time, the setting method of the time point in the operation use data corresponding to the single hydrogen fuel battery vehicle is that the time point at which the monitoring starts is taken as a starting point, and the last interval point is set every 1min in time sequence, and the starting point and each interval point are all time points;
the invention is correspondingly provided with a plurality of historical records, wherein any one historical record is recorded with the comparison data quantity, the matching reference value, the operation parameter comparison value, the parameter anomaly degree, the abnormal emergence coefficient and the like in the historical process of the hydrogen leakage early warning of the hydrogen energy automobile, each historical record is correspondingly provided with a qualified mark, the qualified mark records whether the process of the hydrogen leakage early warning of the hydrogen energy automobile meets the requirement of a user or not, the qualified mark can be recorded manually, the user can determine whether the process of the hydrogen leakage early warning of the hydrogen energy automobile meets the requirement according to the self-set index, the self-set index can be but is not limited to the number of errors, and the number of errors is not repeated herein, wherein the number of errors is the number of times of no early warning when the hydrogen leakage occurs.
Specifically, the data selection module responds to the quantity comparison value of the quantity of comparison data corresponding to the running data of the target hydrogen energy vehicle and the quantity of preset comparison data, wherein the quantity comparison value is larger than or equal to the preset quantity comparison value, and the comparison data is directly used as analysis data;
The comparison data is vehicle data, wherein a matching reference value corresponding to the operation data of the target hydrogen energy vehicle is larger than a preset matching reference value, and an operation parameter comparison value is smaller than a preset operation parameter comparison value.
The method comprises the steps of carrying out paragraph analysis on all time points of vehicle data according to a sequence from early to late according to time aiming at running data of a target hydrogen energy vehicle and any vehicle data, sequentially selecting the time point and enabling all time points after the time point to be the same as the number of the time points in the running data of the target hydrogen energy vehicle aiming at a single time point, marking all the selected time points as a time paragraph, and continuing to carry out paragraph analysis on all the time points which are not subjected to paragraph analysis until the number of the selected time points cannot reach the number of the time points in the running data of the target hydrogen energy vehicle, and stopping paragraph analysis;
The matching reference value is the maximum value in the matching coefficient corresponding to each time paragraph in the operation data of the target hydrogen energy vehicle and the single vehicle data;
The matching coefficient corresponding to the single time section in the operation data of the target hydrogen energy vehicle and the single vehicle data is the average value of the sub matching coefficients corresponding to the operation parameters;
For a single operation parameter, the operation parameter is recorded as a target operation parameter, and a calculation formula of a sub-matching coefficient r corresponding to the target operation parameter is as follows:
,
wherein m is the number of time points in the operation data of the target hydrogen energy vehicle; And The target hydrogen energy vehicle's operation data and the value of the target operation parameter corresponding to the kth time point in a single time section in the single vehicle data,Is an average value of values of the target operation parameters corresponding to each time point in the operation data of the target hydrogen energy vehicle,K=1, 2,3, an average of values of the target operating parameter corresponding to each time point in a single time segment in the single vehicle data;
quantity comparison value = comparison data quantity-preset comparison data quantity;
Aiming at the running data of the target hydrogen energy vehicle and any vehicle data, the running parameter comparison value is the maximum value in the sub comparison values corresponding to all the running parameters, the running parameter is recorded as a target running parameter for a single running parameter, the average value of the values of the target running parameters corresponding to all the time points of the target running parameter in the running data of the target hydrogen energy vehicle is recorded as a1, the average value of the values of the target running parameters corresponding to all the time points of the target running parameter in the vehicle data is recorded as a2, and the sub comparison value corresponding to the target running parameter is the larger value in the values of the sub comparison values of the target running parameter of the 1-a 2I/a 1 and a 2;
the method comprises the steps that a preset comparison data quantity and a preset quantity comparison value are obtained, a user can determine according to an actual application scene, the larger the user needs to improve selection precision, the larger the preset comparison data quantity and the preset quantity comparison value are, the preset comparison data quantity and the preset quantity comparison value are provided, the preset comparison data quantity is an average value of comparison data quantity corresponding to a historical record which takes the comparison data directly as analysis data and can meet the user needs, and the preset quantity comparison value is 0;
The method comprises the steps that a preset matching reference value and a preset operation parameter comparison value are obtained, a user can determine according to an actual application scene, the larger the user needs for improving early warning accuracy, the larger the preset matching reference value is, the smaller the preset operation parameter comparison value is, the method for obtaining the preset matching reference value and the preset operation parameter comparison value is provided, the comparison data are detected to be directly used as historical records of analysis data, and the average value of the matching reference value and the average value of the operation parameter comparison value, which correspond to the historical records capable of meeting the user needs, are respectively recorded as the preset matching reference value and the preset operation parameter comparison value.
Specifically, the data selection module responds to the comparison value that the comparison data quantity corresponding to the operation data of the target hydrogen energy vehicle and the preset comparison data quantity are smaller than the preset quantity comparison value, and the analysis data are selected in a complementary mode according to the high-frequency influence parameter matching degree.
The method comprises the steps of taking each pair of data as analysis data, recording operation parameters with abnormal emerging coefficients larger than preset abnormal emerging coefficients as high-frequency influence parameters, and taking vehicle data with high-frequency influence parameter matching degree larger than or equal to preset high-frequency influence parameter matching degree as analysis data;
The matching degree of the high-frequency influence parameters corresponding to the operation data of the target hydrogen energy vehicle and the single vehicle data is the maximum value of the high-frequency matching coefficients corresponding to each time period in the operation data of the target hydrogen energy vehicle and the single vehicle data;
The method comprises the steps that the value of the preset high-frequency influence parameter matching degree is provided, a user can determine according to an actual application scene, and the larger the user needs for improving early warning precision is, the larger the value of the preset high-frequency influence parameter matching degree is, and the value of the preset high-frequency influence parameter matching degree is provided, wherein the preset high-frequency influence parameter matching degree is 0.85;
Aiming at a single operation parameter, the operation parameter is marked as a target operation parameter, the parameter mean value corresponding to the target operation parameter is the mean value of the values of the target operation parameters corresponding to the time points in the vehicle data, and the parameter fluctuation value corresponding to the target operation parameter is the standard deviation of the values of the target operation parameters corresponding to the time points in the vehicle data;
Parameter anomaly degree corresponding to the target operation parameter = parameter mean value corresponding to the target operation parameter/mean value of parameter mean value corresponding to the target operation parameter in each vehicle data + parameter fluctuation value corresponding to the target operation parameter/mean value of parameter fluctuation value corresponding to the target operation parameter in each vehicle data; aiming at a single operation parameter in single leakage vehicle data, if the parameter anomaly degree corresponding to the operation parameter is larger than the preset parameter anomaly degree, the operation parameter is recorded as an influence parameter corresponding to the leakage vehicle data;
Detecting influence parameters corresponding to the data of each leaked vehicle, and recording operation parameters with abnormal emergence coefficients larger than preset abnormal emergence coefficients as high-frequency influence parameters;
Abnormal emergence coefficient corresponding to a single operating parameter = the number of leaky vehicle data acquired from the internet of vehicles taking the operating parameter as an influencing parameter/the total amount of leaky vehicle data acquired from the internet of vehicles;
The method for taking the values of the preset parameter anomaly degree and the preset abnormal emerging coefficient is provided, the average value of the parameter anomaly degree corresponding to each influence parameter in a history record capable of meeting the user requirement is recorded as the preset parameter anomaly degree, and the average value of the abnormal emerging coefficient corresponding to each high-frequency influence parameter in the history record capable of meeting the user requirement is recorded as the preset abnormal emerging coefficient.
It can be understood that the sufficiency of the comparison data is effectively reflected through the quantity comparison value, when the quantity comparison value is larger than or equal to the preset quantity comparison value, the comparison data is sufficient, the comparison data can be directly used as analysis data, when the quantity comparison value is smaller than the preset quantity comparison value, the comparison data is insufficient, and the analysis data is selected in a complementary mode according to the high-frequency influence parameter matching degree, so that the representativeness of the analysis data and the reliability of an early warning result can be improved.
Specifically, the quantity analysis module responds to the comparison data quantity being greater than or equal to the preset comparison data quantity, and determines the quantity of hydrogen sensors according to the ratio of the leaked vehicle data;
the number of hydrogen sensors is in positive correlation with the leaky vehicle data duty cycle.
The comparison data quantity is the total quantity of the comparison data acquired from the Internet of vehicles;
The leak vehicle data duty ratio=the number of leak vehicle data in the comparison data/the comparison data number;
the number of the hydrogen sensors is the total number of the hydrogen sensors arranged in the target hydrogen energy vehicle;
Detecting historical records which are used for determining the number of hydrogen sensors according to the ratio of the leaked vehicle data and can meet the demands of users, and recording the historical records as first reference historical records, wherein the number of the hydrogen sensors is a minimum integer which is more than or equal to w0, and w0=the ratio of the leaked vehicle data to the ratio of the leaked vehicle data corresponding to each first reference historical record is multiplied by the average value of the number of the hydrogen sensors corresponding to each first reference historical record.
Specifically, the quantity analysis module responds to the fact that the operation parameter comparison value is smaller than a preset operation parameter comparison value, and the quantity of the hydrogen sensors is determined according to the leakage vehicle data comparison value;
The number of the hydrogen sensors is in positive correlation with the comparison value of the leaked vehicle data.
The comparison value of the leaked vehicle data is the maximum value of the leakage matching degree corresponding to the operation data of the target hydrogen energy vehicle and each piece of leaked vehicle data in the comparison data;
Leak match = match reference/preset match reference + (1-operating parameter comparison/preset operating parameter comparison);
Detecting historical records which are determined according to the leakage vehicle data comparison value, can meet the requirement of a user, and are recorded as second reference historical records, wherein the number of the hydrogen sensors is a minimum integer which is more than or equal to w1, and w1=the leakage vehicle data comparison value/the average value of the leakage vehicle data comparison value corresponding to each second reference historical record is multiplied by the average value of the number of the hydrogen sensors corresponding to each second reference historical record.
It can be understood that by effectively reflecting the sufficiency of data available for risk quantification by comparing the number of data, when the number of data is greater than or equal to the preset comparison number of data, the data is sufficient, and the leakage risk level of the current hydrogen energy vehicle group is directly reflected, and the higher the ratio of the leakage vehicle data is, the higher the occurrence probability of the leakage event of the hydrogen energy vehicle is, so that more hydrogen sensors are required to be deployed to improve the monitoring density and the response speed;
when the comparison data quantity is smaller than the preset comparison data quantity, the fact that the comparison data quantity is insufficient to support direct risk quantification is indicated, the leakage vehicle data comparison value is used as a dynamic adjustment basis, and the higher the leakage vehicle data comparison value is, the higher the leakage risk is, and a hydrogen sensor is required to be increased in a targeted mode.
Specifically, the position analysis module responds that the difference between the number of high-frequency leakage positions and the number of hydrogen sensors is smaller than or equal to the standard number and the coverage distance threshold is larger than or equal to the preset coverage distance threshold, and then the hydrogen sensor installation position is determined according to the leakage frequency reference value.
Wherein the number difference = the number of high-frequency leakage positions-the number of hydrogen sensors, the number of high-frequency leakage positions being the total number of high-frequency leakage positions in different leakage positions corresponding to each leakage vehicle data, the standard number being 0;
Other leak positions than the high-frequency leak position among the different leak positions corresponding to the respective pieces of leak vehicle data are noted as low-frequency leak positions;
the coverage distance threshold is the maximum value in the distance reference values corresponding to the low-frequency leakage positions, and the distance reference value corresponding to the single low-frequency leakage position is the maximum value in the shortest distance corresponding to the low-frequency leakage position to the high-frequency leakage position;
The method comprises the steps that a user can determine the value of a preset coverage distance threshold according to an actual application scene, if the value of the preset coverage distance threshold is larger, the user determines that the requirement of the installation position of the hydrogen sensor is larger according to a leakage frequency reference value, the method for determining the value of the preset coverage distance threshold is provided, the history of the installation position of the hydrogen sensor is determined according to the leakage frequency reference value by the user, and the average value of the coverage distance thresholds corresponding to the history of the requirement of the user is recorded as the preset coverage distance threshold;
Acquiring leakage positions corresponding to various pieces of leakage vehicle data, recording the leakage positions with the leakage frequency reference value larger than a preset leakage frequency reference value as high-frequency leakage positions, wherein the leakage frequency reference value corresponding to a single leakage position = the number of pieces of leakage vehicle data with the leakage position acquired from the Internet of vehicles/the total number of pieces of leakage vehicle data acquired from the Internet of vehicles;
The method comprises the steps of selecting the leakage positions according to the sequence from the large leakage frequency reference value to the small leakage frequency reference value until the number of the selected leakage positions reaches the number of the hydrogen sensors, and installing the hydrogen sensors at the selected leakage positions;
It should be noted that the types of the hydrogen sensors installed at the respective positions are not limited, and the user can select the hydrogen sensors according to actual demands.
Specifically, the position analysis module responds to the fact that the difference between the number of the high-frequency leakage positions and the number of the hydrogen sensors is larger than the standard number or the coverage distance threshold is smaller than the preset coverage distance threshold, and then the hydrogen sensor installation position is determined according to the associated position combination.
Wherein determining the hydrogen sensor mounting location according to the associated location combination comprises:
if the number of the associated position combinations is greater than or equal to the number of the hydrogen sensors, selecting the associated position combinations according to the sequence from large to small of the combination influence coefficients until the number of the hydrogen sensors is reached, wherein the sensor installation position corresponding to the single associated combination is the leakage position with the largest leakage frequency reference value in the associated combination;
a combination influence coefficient corresponding to a single associated position combination=the sum of leakage frequency reference values corresponding to leakage positions in the associated position combination/the number of leakage positions in the associated position combination;
If the number of the associated position combinations is smaller than the number of the hydrogen sensors, installing the hydrogen sensors in each associated position combination, wherein the number of the hydrogen sensors installed in each associated position combination is k, k1 analysis associated combination are selected according to the sequence from the high frequency leakage position influence coefficient to the low frequency leakage position influence coefficient, and the hydrogen sensors are installed in each associated combination according to the sequence from the high frequency leakage frequency reference value to the low frequency leakage position;
k is a maximum integer less than or equal to k0, k0=number of hydrogen sensors/number of associated position combinations, k1=number of hydrogen sensors-number of associated position combinations x k;
the analysis association is an association position combination with a reference difference value greater than 0, the reference difference value=the number of leakage positions-k.
It can be understood that when the difference between the number of the high-frequency leakage positions and the number of the hydrogen sensors is smaller than or equal to the standard number and the coverage distance threshold is larger than or equal to the preset coverage distance threshold, the existing sensor network is indicated to be capable of covering the main risk source, and at the moment, the installation position of the hydrogen sensor is determined according to the reference value of the leakage frequency, so that the highest risk point can be directly locked, and excessive calculation is avoided;
When the number difference between the number of the high-frequency leakage positions and the number of the hydrogen sensors is larger than the standard number or the coverage distance threshold is smaller than the preset coverage distance threshold, the existing sensor network has coverage dead zones, cannot cover all potential risk sources comprehensively, and the installation positions of the hydrogen sensors are determined according to the association position combination, so that the maximization of risk coverage can be realized.
Specifically, the method for confirming the association position combination includes:
if the height identity of the leakage position is greater than or equal to the preset height identity of the leakage position, determining an associated position combination according to the shortest distance;
If the height identity of the leakage positions is smaller than the preset height identity of the leakage positions, determining the associated position combination according to the height difference and the height influence distance.
The height of each leakage position is equal to 1/(the standard deviation of the height of the leakage position corresponding to each leakage position is +1), and the height of the leakage position corresponding to a single leakage position is the shortest distance between the leakage position and the ground when the target hydrogen energy vehicle is horizontally placed on the ground;
The method comprises the steps that a user can determine the value of the preset leakage position height identity according to an actual application scene, if the value of the preset leakage position height identity is smaller, the user determines that the requirement of the association combination is larger according to the interval distance, a value method for the preset leakage position height identity is provided, the history record of the association combination is determined according to the interval distance by a detection user, and the average value of the leakage position height identity corresponding to the history record capable of meeting the requirement of the user is recorded as the preset leakage position height identity;
Determining a relevant position combination according to the shortest distance, wherein the relevant analysis is carried out on each leakage position, when the relevant analysis is carried out on a single leakage position, the leakage position is marked as a target leakage position, the leakage position which is not marked with the relevant position combination and is outside the target leakage position is marked as a reference leakage position, each reference leakage position with the shortest distance of the target leakage position smaller than the preset shortest distance and the target leakage position are marked with a relevant position combination, the relevant analysis is carried out on the leakage position which is not marked with the relevant position combination, and the relevant analysis is stopped until each leakage position is marked with the relevant position combination;
Determining a relevant position combination according to the height difference and the height influence distance, wherein the relevant position combination comprises the steps of carrying out relevant analysis on each leakage position, recording the leakage position as a target leakage position when carrying out relevant analysis on a single leakage position, recording the leakage position which is not recorded in the relevant position combination outside the target leakage position as a reference leakage position, recording each reference leakage position and each target leakage position which are smaller than the preset height difference and are positioned in the influence range corresponding to the target leakage position in the height difference and are positioned in the relevant position combination, continuing carrying out relevant analysis on the leakage position which is not recorded in the relevant position combination until each leakage position is recorded in the relevant position combination, and stopping relevant analysis;
The value of the preset shortest distance and the preset height difference is smaller as the accuracy requirement of the user for improving the similarity degree of the leakage positions in the associated position combination is larger, the value of the preset shortest distance and the preset height difference is provided, the preset shortest distance is 0.3m, and the preset height difference is 0.25m;
The height difference corresponding to any two leakage positions is the absolute value of the difference value of the height of the leakage positions corresponding to the two leakage positions;
the influence range corresponding to the target leakage position is a sphere with the target leakage position as a sphere center and the height influence distance corresponding to the target leakage position as a radius;
the height influence distance corresponding to the target leakage position and the height of the leakage position corresponding to the target leakage position are in positive correlation, wherein the height influence distance corresponding to the target leakage position = the height of the leakage position corresponding to the target leakage position multiplied by the weight coefficient, and the weight coefficient is 0.5;
It can be understood that the height identity of the leakage position effectively reflects the concentration degree of the height of the leakage point, when the height of the leakage point is concentrated, the relevant position combination is determined according to the shortest distance, the overlapping area can be ensured to be covered by a single sensor, redundant deployment is avoided, when the height of the leakage point is scattered, as the hydrogen leakage diffusion characteristic shows obvious height dependence, when the height of the leakage position is smaller, the hydrogen is easy to form local aggregation around an obstacle due to the limitation of a chassis structure of a vehicle, the horizontal diffusion distance is limited, the hydrogen is rapidly diffused in a jet flow mode when the height of the leakage position is higher, the diffusion distance is far, and the relevant position combination is determined according to the height difference and the height influence distance, so that the differential combination coverage of high-low leakage can be realized by setting a vertical spacing threshold and a dynamic influence radius.
Specifically, the leakage early warning module responds that the hydrogen concentration threshold value is larger than or equal to a preset hydrogen concentration threshold value, and then leakage early warning is directly sent to a user.
The hydrogen concentration threshold is the maximum value of the hydrogen concentration monitored by each hydrogen sensor in the monitoring period after installation;
The method comprises the steps that a preset hydrogen concentration threshold value is obtained, a user can determine according to an actual application scene, the greater the accuracy requirement of the user for ensuring the safety of a vehicle is, the smaller the preset hydrogen concentration threshold value is, the method for obtaining the preset hydrogen concentration threshold value is provided, a history record of leakage early warning is detected and sent to the user directly, and the average value of the hydrogen concentration threshold values corresponding to the history record capable of meeting the requirement of the user is recorded as the preset hydrogen concentration threshold value;
when the leakage early warning is directly sent to the user, the leakage early warning is sent to the user when the hydrogen concentration monitored by the hydrogen sensor is larger than or equal to the preset hydrogen concentration threshold value.
Specifically, the leakage early warning module responds to the fact that the hydrogen concentration threshold value is smaller than a preset hydrogen concentration threshold value, and whether early warning is sent to a user is determined according to a risk evaluation value of analysis data corresponding to the operation data of the target hydrogen energy vehicle;
If the risk assessment value is greater than or equal to the preset risk assessment value, an early warning is sent to the user;
if the risk assessment value is smaller than the preset risk assessment value, an early warning is not required to be sent to the user.
When an early warning is sent to a user, the early warning is sent to the user at the end time of the monitoring period after installation;
The calculation formula of the risk assessment value is as follows:
,
wherein, the For risk assessment, j is 1,2,3,4,For the value of the j-th token,The method comprises the steps that a j-th characterization value is preset, and the j-th characterization value is preset as an average value of j-th characterization values corresponding to historical records capable of meeting user requirements;
1 st characterization value = amount of leaky vehicle data in the analysis data/total amount of analysis data;
The 2 nd characterization value is the maximum value of paragraph reference values corresponding to time periods of the leaked vehicle data in the analysis data, wherein the paragraph reference value corresponding to a single time paragraph=the matching coefficient corresponding to the operation data of the target hydrogen energy vehicle of the time paragraph/the average value of the matching coefficients corresponding to the operation data of the target hydrogen energy vehicle of the time paragraphs + (1-the time reference value corresponding to the time period/the average value of the time reference values corresponding to the time periods);
the 3 rd characterization value is the maximum value in the matching degree of the high-frequency influence parameters corresponding to the running data of the target hydrogen energy vehicle and the data of each leaked vehicle;
4 th characterization value=1/minimum value of the operation parameter comparison values of the operation data of the target hydrogen energy vehicle and the corresponding leakage vehicle data;
the method comprises the steps of detecting a history record of sending early warning to a user according to the risk evaluation value determination of analysis data, and recording an average value of the risk evaluation values corresponding to the history record capable of meeting the user requirements as a preset risk evaluation value.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.

Claims (10)

1. The utility model provides a hydrogen energy vehicle safety precaution system that big data of car networking supported which characterized in that includes:
the data acquisition module is used for acquiring the operation data of the target hydrogen energy vehicle and the vehicle data of the Internet of vehicles;
The data selection module is connected with the data acquisition module and used for determining the quantity comparison value of the quantity of the comparison data corresponding to the operation data of the target hydrogen energy vehicle and the quantity of the preset comparison data and directly selecting the analysis data according to the matching coefficient and the operation parameter comparison value or supplementing and selecting the analysis data according to the matching degree of the high-frequency influence parameters;
The quantity analysis module is respectively connected with the data acquisition module and the data selection module and is used for determining the quantity of the hydrogen sensors according to the ratio of the leaked vehicle data or the comparison value of the leaked vehicle data according to the comparison data quantity;
the position analysis module is respectively connected with the data acquisition module and the number analysis module and is used for determining the installation position of the hydrogen sensor according to the number difference value between the number of high-frequency leakage positions and the number of the hydrogen sensors and the coverage distance threshold value;
the leakage early warning module is respectively connected with the data acquisition module and the data selection module and is used for determining whether to directly send leakage early warning to a user according to the hydrogen concentration threshold value determined by each hydrogen sensor or determining whether to send early warning to the user according to the risk evaluation value of analysis data corresponding to the operation data of the target hydrogen energy vehicle.
2. The hydrogen energy vehicle safety pre-warning system supported by the internet of vehicles big data according to claim 1, wherein the data selection module responds to the comparison value of the number of comparison data corresponding to the operation data of the target hydrogen energy vehicle and the number of preset comparison data, which is larger than or equal to the preset number comparison value, and the comparison data is directly used as analysis data;
The comparison data is vehicle data, wherein a matching reference value corresponding to the operation data of the target hydrogen energy vehicle is larger than a preset matching reference value, and an operation parameter comparison value is smaller than a preset operation parameter comparison value.
3. The system of claim 2, wherein the data selection module responds to the comparison data quantity corresponding to the operation data of the target hydrogen energy vehicle and the preset comparison data quantity smaller than the preset quantity comparison value, and additionally selects the analysis data according to the high-frequency influence parameter matching degree.
4. The internet of vehicles big data supported hydrogen energy vehicle safety pre-warning system of claim 1, wherein the number analysis module responds to the comparison data number being greater than or equal to a preset comparison data number, and determines the number of hydrogen sensors according to the leaky vehicle data ratio;
the number of hydrogen sensors is in positive correlation with the leaky vehicle data duty cycle.
5. The internet of vehicles big data supported hydrogen energy vehicle safety pre-warning system of claim 4, wherein the quantity analysis module responds to the operation parameter comparison value being smaller than the preset operation parameter comparison value, and determines the quantity of hydrogen sensors according to the leaked vehicle data comparison value;
The number of the hydrogen sensors is in positive correlation with the comparison value of the leaked vehicle data.
6. The internet of vehicles big data supported hydrogen energy vehicle safety pre-warning system of claim 1, wherein the position analysis module determines the hydrogen sensor installation position according to the leakage frequency reference value in response to the difference between the number of high-frequency leakage positions and the number of hydrogen sensors being less than or equal to a standard number and the coverage distance threshold being greater than or equal to a preset coverage distance threshold.
7. The internet of vehicles big data supported hydrogen energy vehicle safety precaution system of claim 6, wherein the position analysis module determines the hydrogen sensor installation position according to the associated position combination in response to the difference between the number of high frequency leakage positions and the number of hydrogen sensors being greater than the standard number or the coverage distance threshold being less than the preset coverage distance threshold.
8. The internet of vehicles big data supported hydrogen energy vehicle safety precaution system of claim 7, wherein the means for confirming the associated location combination comprises:
if the height identity of the leakage position is greater than or equal to the preset height identity of the leakage position, determining an associated position combination according to the shortest distance;
If the height identity of the leakage positions is smaller than the preset height identity of the leakage positions, determining the associated position combination according to the height difference and the height influence distance.
9. The internet of vehicles big data supported hydrogen energy vehicle safety pre-warning system of claim 1, wherein the leakage pre-warning module responds to the hydrogen concentration threshold value being greater than or equal to a preset hydrogen concentration threshold value, and then directly sends the leakage pre-warning to the user.
10. The system of claim 9, wherein the leakage pre-warning module is configured to determine whether to send a pre-warning to a user according to a risk assessment value of analysis data corresponding to the operation data of the target hydrogen energy vehicle in response to the hydrogen concentration threshold being less than a preset hydrogen concentration threshold;
If the risk assessment value is greater than or equal to the preset risk assessment value, an early warning is sent to the user;
if the risk assessment value is smaller than the preset risk assessment value, an early warning is not required to be sent to the user.
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