Vehicle safety risk assessment and early warning method and device for hydrogen fuel cell vehicle

Abstract

The present application relates to the field of automobile safety technology, and discloses a hydrogen fuel cell vehicle safety risk assessment and early warning method and device, wherein, on the basis of voltage and temperature, the application innovatively combines gas pressure and smoke data for analysis, and can realize safety risk assessment of the power battery system in the hydrogen fuel cell vehicle to be evaluated. Meanwhile, according to the hydrogen system data set, safety risk assessment of the hydrogen system in the hydrogen fuel cell vehicle to be evaluated can be realized. Further, the three safety risk assessment scores obtained are combined to perform safety risk assessment on the hydrogen fuel cell vehicle to be evaluated, which improves the comprehensiveness of the safety risk assessment of the vehicle compared with the traditional assessment method. Further, according to the assessment result, early warning information is sent to the corresponding client in real time, and real-time safety early warning of the hydrogen fuel cell vehicle to be evaluated can be realized.

Description

Technical Field

[0001] This invention relates to the field of automotive safety technology, specifically to a method and apparatus for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles. Background Technology

[0002] Current on-board terminals for safety risk assessment and early warning of hydrogen fuel cell vehicles have a drawback: they lack real-time, accurate, and effective risk assessment and early warning methods for the vehicle's power battery system and hydrogen system. Existing on-board terminals often only collect voltage and temperature values ​​for analysis of the hydrogen fuel cell vehicle's power battery system, making it difficult to accurately assess and warn of thermal runaway conditions. Furthermore, safety assessments of the vehicle's hydrogen system are often conducted through periodic on-site manual inspections, which is insufficient to meet the need for timely and accurate detection of safety risks in the vehicle's battery and hydrogen system, creating potential vehicle safety hazards and resulting in an incomplete assessment of vehicle safety risks by existing terminals. Summary of the Invention

[0003] In view of this, the present invention provides a method and apparatus for assessing and warning of vehicle safety risks of hydrogen fuel cell vehicles, in order to solve the problem that the current assessment of thermal runaway of the power battery system of hydrogen fuel cell vehicles and the safety risks of hydrogen system are difficult to meet the requirements of timeliness and accuracy.

[0004] In a first aspect, the present invention provides a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles, used in an intelligent vehicle terminal, wherein the intelligent vehicle terminal is connected to a client; the method includes:

[0005] The system acquires the fault code dataset, initial individual cell voltage dataset, initial individual cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset of the hydrogen fuel cell vehicle to be evaluated. The fault code dataset is processed using a pre-defined judgment method and risk quantification method to obtain a first safety risk assessment score. Based on the initial individual cell voltage dataset, initial individual cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, a safety risk assessment is performed on the power battery system of the hydrogen fuel cell vehicle to be evaluated, resulting in a second safety risk assessment score. Based on the initial hydrogen system dataset, a safety risk assessment is performed on the hydrogen system of the hydrogen fuel cell vehicle to be evaluated, resulting in a third safety risk assessment score. Based on the first, second, and third safety risk assessment scores, the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated is determined, and a warning message is sent to the client based on the safety risk assessment result.

[0006] This invention provides a method for assessing and warning the safety risks of hydrogen fuel cell vehicles. Based on voltage and temperature data, it innovatively combines air pressure and smoke data for analysis, enabling a safety risk assessment of the power battery system within the hydrogen fuel cell vehicle under evaluation. Simultaneously, it can assess the safety risks of the hydrogen system within the vehicle based on a hydrogen system dataset. Furthermore, by combining three safety risk assessment scores, the method enhances the comprehensiveness of the safety risk assessment compared to traditional methods. Moreover, by sending real-time warning information to the corresponding client based on the assessment results, it enables real-time safety warnings for the hydrogen fuel cell vehicle under evaluation.

[0007] In one optional implementation, the fault code dataset is processed using a preset judgment method and a risk quantification method to obtain a first safety risk assessment score, including:

[0008] The fault code dataset is processed using a preset judgment method to obtain the total number of fault alarm events of the hydrogen fuel cell vehicle to be evaluated; the target fault item data corresponding to each fault alarm event is quantified using a risk quantification method to obtain multiple quantified values; based on the total number of fault alarm events of the hydrogen fuel cell vehicle to be evaluated and the multiple quantified values, the first safety risk assessment score is calculated.

[0009] This invention evaluates and quantifies strongly correlated fault items to obtain corresponding safety risk assessment scores, providing data support for subsequent vehicle safety risk assessments.

[0010] In one optional implementation, the fault code dataset is processed using a preset judgment method to obtain the total number of fault alarm events occurring in the hydrogen fuel cell vehicle to be evaluated, including:

[0011] Determine whether there is at least one consecutive target frame number of target fault item data in the fault code dataset; when there is at least one consecutive target frame number of target fault item data in the fault code dataset, determine whether each target fault item data meets the preset alarm level; when each target fault item data meets the preset alarm level, determine the total number of fault item alarm events occurring in the hydrogen fuel cell vehicle to be evaluated.

[0012] This invention assesses target fault data and combines it with alarm levels to determine the total number of fault alarm events occurring in the hydrogen fuel cell vehicle to be evaluated, providing data support for subsequent vehicle safety risk assessment.

[0013] In one optional implementation, a safety risk assessment is performed on the power battery system of the hydrogen fuel cell vehicle to be evaluated based on the initial individual cell voltage dataset, the initial individual cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, to obtain a second safety risk assessment score, including:

[0014] The initial single-cell voltage dataset and the initial single-cell temperature dataset are processed separately to obtain the target single-cell voltage dataset and the target single-cell temperature dataset. Based on the target single-cell voltage dataset, the target single-cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, thermal runaway detection is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated to obtain the target thermal runaway detection results. Based on the thermal runaway detection results, a second safety risk assessment score is determined.

[0015] This invention innovatively combines air pressure and smoke data with voltage and temperature data to detect thermal runaway in power battery systems, thereby enabling safety risk assessment of the power battery systems in hydrogen fuel cell vehicles under evaluation.

[0016] In one optional implementation, based on the target single-cell voltage dataset, the target single-cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, thermal runaway detection is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and the target thermal runaway detection results are obtained, including:

[0017] Based on the target single-cell voltage dataset and the target single-cell temperature dataset, thermal runaway detection is performed on the power battery system of the hydrogen fuel cell vehicle under evaluation to obtain the first thermal runaway detection result; based on the battery pack pressure dataset, thermal runaway detection is performed on the power battery system of the hydrogen fuel cell vehicle under evaluation to obtain the second thermal runaway detection result; based on the smoke concentration dataset, thermal runaway detection is performed on the power battery system of the hydrogen fuel cell vehicle under evaluation to obtain the third thermal runaway detection result; based on the first thermal runaway detection result, the second thermal runaway detection result, and the third thermal runaway detection result, the target thermal runaway detection result is determined.

[0018] In one alternative implementation, a safety risk assessment is performed on the hydrogen system within the hydrogen fuel cell vehicle to be evaluated based on an initial hydrogen system dataset, resulting in a third safety risk assessment score, including:

[0019] The initial hydrogen system dataset is filtered and preprocessed to obtain the target hydrogen system dataset. Based on the target hydrogen system dataset, a safety analysis is performed on the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and the hydrogen system safety analysis results are obtained. Based on the hydrogen system safety analysis results, the third safety risk assessment score is determined.

[0020] This invention enables a safety risk assessment of the hydrogen system within a hydrogen fuel cell vehicle to be evaluated, based on a hydrogen system dataset, thus providing support for a more comprehensive safety risk assessment of the vehicle in the future.

[0021] In one optional implementation, a safety analysis is performed on the hydrogen system within the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, yielding hydrogen system safety analysis results, including:

[0022] Based on the target hydrogen system dataset, hydrogen gas in the hydrogen system of the hydrogen fuel cell vehicle under evaluation was monitored to obtain hydrogen leakage analysis results; hydrogen storage tank pressure in the hydrogen fuel cell vehicle under evaluation was monitored based on the target hydrogen system dataset to obtain hydrogen storage tank overpressure results; hydrogen system temperature was monitored based on the target hydrogen system dataset to obtain hydrogen system temperature monitoring results; based on the hydrogen leakage analysis results, hydrogen storage tank overpressure results, and hydrogen system temperature monitoring results, the hydrogen system safety analysis results were determined.

[0023] Secondly, the present invention provides a vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles, used in an intelligent vehicle terminal, the intelligent vehicle terminal being connected to a client; the device includes:

[0024] The system comprises the following modules: an acquisition module for acquiring fault code datasets, initial individual cell voltage datasets, initial individual cell temperature datasets, battery pack pressure datasets, smoke concentration datasets, and initial hydrogen system datasets for the hydrogen fuel cell vehicle to be evaluated; a processing module for processing the fault code datasets using preset judgment and risk quantification methods to obtain a first safety risk assessment score; a first assessment module for conducting a safety risk assessment of the power battery system within the hydrogen fuel cell vehicle to be evaluated based on the initial individual cell voltage dataset, initial individual cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset to obtain a second safety risk assessment score; a second assessment module for conducting a safety risk assessment of the hydrogen system within the hydrogen fuel cell vehicle to be evaluated based on the initial hydrogen system dataset to obtain a third safety risk assessment score; and a determination module for determining the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated based on the first, second, and third safety risk assessment scores, and sending a warning message to the client based on the safety risk assessment result.

[0025] Thirdly, the present invention provides a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles described in the first aspect or any corresponding embodiment.

[0026] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a flowchart illustrating a method for assessing and warning of vehicle safety risks in a hydrogen fuel cell vehicle according to an embodiment of the present invention.

[0029] Figure 2 This is a flowchart illustrating another method for assessing and warning the safety risks of a hydrogen fuel cell vehicle according to an embodiment of the present invention.

[0030] Figure 3 This is a flowchart illustrating another method for assessing and warning the safety risks of a hydrogen fuel cell vehicle according to an embodiment of the present invention.

[0031] Figure 4 This is a flowchart illustrating a method for assessing and warning of vehicle safety risks in a hydrogen fuel cell vehicle according to an embodiment of the present invention.

[0032] Figure 5A This is a flowchart of the safety risk assessment process for the fault code data assessment model according to an embodiment of the present invention;

[0033] Figure 5B This is a flowchart of the safety risk assessment of the thermal runaway risk early warning model according to an embodiment of the present invention;

[0034] Figure 5C This is a flowchart illustrating the construction process of a thermal runaway risk early warning model according to an embodiment of the present invention;

[0035] Figure 5D This is a flowchart of the safety risk assessment process for the hydrogen system safety analysis and early warning model according to an embodiment of the present invention;

[0036] Figure 6A This is a flowchart of hydrogen leak detection in a hydrogen system according to an embodiment of the present invention;

[0037] Figure 6B This is a flowchart of the hydrogen storage cylinder overpressure judgment process according to an embodiment of the present invention;

[0038] Figure 6C This is a flowchart of the hydrogen system temperature determination according to an embodiment of the present invention;

[0039] Figure 7 This is a structural block diagram of a vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles according to an embodiment of the present invention;

[0040] Figure 8 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Currently, it is difficult to meet the needs for timely and accurate assessment of the thermal runaway of the power battery system of hydrogen fuel cell vehicles and the safety risks of hydrogen systems.

[0043] This invention provides a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles for use in intelligent vehicle terminals. By combining three safety risk assessment scores, a comprehensive safety risk assessment of the hydrogen fuel cell vehicle to be assessed is achieved.

[0044] According to an embodiment of the present invention, a method for assessing and warning the safety risks of a hydrogen fuel cell vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0045] This embodiment provides a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles, which can be used in an intelligent vehicle terminal connected to a client. Figure 1 This is a flowchart of a method for assessing and warning the safety risks of hydrogen fuel cell vehicles according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0046] Step S101: Obtain the fault code dataset, initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset of the hydrogen fuel cell vehicle to be evaluated.

[0047] The fault code dataset represents multiple fault alarm data of the hydrogen fuel cell vehicle to be evaluated.

[0048] Specifically, the fault code dataset of the hydrogen fuel cell vehicle to be evaluated can be collected and stored through the intelligent vehicle terminal.

[0049] Furthermore, an initial single-cell voltage dataset V = {V1, V2, ..., V} can be collected. n} and the initial single-cell temperature dataset T = {T1, T2, ..., T n The data is processed and stored in timestamp order. The initial individual cell temperature dataset can be obtained using temperature probes.

[0050] Furthermore, data sets on battery pack pressure and smoke concentration can be collected within the hydrogen fuel cell vehicle to be evaluated. The smoke concentration dataset can be obtained from smoke sensors within the vehicle.

[0051] Furthermore, an initial hydrogen system dataset corresponding to the hydrogen system in the hydrogen fuel cell vehicle to be evaluated can be collected, which may include data such as hydrogen concentration, hydrogen storage tank pressure, and hydrogen tank temperature.

[0052] Step S102: The fault code dataset is processed by a preset judgment method and a risk quantification method to obtain the first safety risk assessment score.

[0053] Specifically, by using a fault code dataset to assess and quantify the safety risks of the hydrogen fuel cell vehicle under evaluation, a corresponding first safety risk assessment score can be obtained.

[0054] Step S103: Based on the initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, a safety risk assessment is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and a second safety risk assessment score is obtained.

[0055] Specifically, based on the traditionally collected initial single-cell voltage and temperature datasets, and combined with the battery pack pressure and smoke concentration datasets, a safety risk assessment of the power battery system in the hydrogen fuel cell vehicle to be evaluated can be achieved, and a corresponding safety risk assessment score can be obtained.

[0056] Step S104: Based on the initial hydrogen system dataset, conduct a safety risk assessment of the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and obtain a third safety risk assessment score.

[0057] Specifically, the initial hydrogen system data collected can be used to assess the safety risks of the hydrogen system in the hydrogen fuel cell vehicle being evaluated, and obtain the corresponding safety risk assessment score.

[0058] Step S105: Based on the first safety risk assessment score, the second safety risk assessment score, and the third safety risk assessment score, determine the safety risk assessment result of the hydrogen fuel cell vehicle to be assessed, and send a warning message to the client based on the safety risk assessment result.

[0059] Specifically, combining the three safety risk assessment scores obtained to conduct a safety risk assessment of the hydrogen fuel cell vehicle under evaluation can improve the comprehensiveness of the vehicle's safety risk assessment compared to traditional assessment methods.

[0060] The total safety risk assessment score of the hydrogen fuel cell vehicle to be evaluated is calculated using the following relationship (1):

[0061]

[0062] In the formula: P represents the total safety risk assessment score of the hydrogen fuel cell vehicle to be evaluated; X i This represents the weight value assigned to each security risk assessment score; p i This represents the i-th security risk assessment score (i.e., the first security risk assessment score, the second security risk assessment score, and the third security risk assessment score).

[0063] Furthermore, the intelligent vehicle terminal connects to the corresponding client.

[0064] Furthermore, the intelligent vehicle terminal can send corresponding early warning information to the client in real time based on the obtained safety risk assessment results.

[0065] The vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles provided in this embodiment innovatively combines air pressure and smoke data analysis with voltage and temperature data to achieve safety risk assessment of the power battery system within the hydrogen fuel cell vehicle under evaluation. Simultaneously, based on the hydrogen system dataset, it can achieve safety risk assessment of the hydrogen system within the vehicle under evaluation. Furthermore, by combining the obtained three safety risk assessment scores, the safety risk assessment of the hydrogen fuel cell vehicle under evaluation is improved compared to traditional assessment methods, resulting in a more comprehensive assessment of vehicle safety risks. Furthermore, by sending early warning information to the corresponding client in real time based on the assessment results, real-time safety warnings for the hydrogen fuel cell vehicle under evaluation can be achieved.

[0066] This embodiment provides a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles, which can be used in intelligent vehicle terminals connected to client terminals. Figure 2This is a flowchart of a method for assessing and warning the safety risks of hydrogen fuel cell vehicles according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0067] Step S201: Obtain the fault code dataset, initial single-cell voltage dataset, initial single-cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset for the hydrogen fuel cell vehicle to be evaluated. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0068] Step S202: The fault code dataset is processed by a preset judgment method and a risk quantification method to obtain the first safety risk assessment score.

[0069] Specifically, step S202 includes:

[0070] Step S2021: Process the fault code dataset using a preset judgment method to obtain the total number of fault alarm events occurring in the hydrogen fuel cell vehicle to be evaluated.

[0071] Specifically, by using the fault code dataset for judgment and evaluation, the total number of fault alarm events occurring in the hydrogen fuel cell vehicle to be evaluated can be obtained.

[0072] In some optional implementations, step S2021 above includes:

[0073] Step a1: Determine whether there is at least one target fault item data with a consecutive target frame number in the fault code dataset.

[0074] Step a2: When there are at least one consecutive target frame number of target fault item data in the fault code dataset, determine whether each target fault item data meets the preset alarm level.

[0075] Step a3: When the data for each target fault item meets the preset alarm level, determine the total number of fault item alarm events occurring in the hydrogen fuel cell vehicle to be evaluated.

[0076] Specifically, it is determined whether there are one or more strongly correlated fault items (such as total temperature difference alarm, drive motor and engine fault alarm, total voltage alarm, insulation alarm, on-board energy storage device type overcharge, etc.) in the fault code dataset of the hydrogen fuel cell vehicle to be evaluated, and whether they are three consecutive frames of data, i.e., the target fault item data.

[0077] Furthermore, if such a fault exists, it is then determined whether the corresponding target fault item data reaches a Level 3 alarm. If it does, the corresponding fault item alarm event is output, and the total number of fault item alarm events occurring in the hydrogen fuel cell vehicle to be evaluated can be obtained.

[0078] Step S2022: Use the risk quantification method to quantify the target fault item data corresponding to each fault item alarm event to obtain multiple quantified values.

[0079] Specifically, by quantifying the safety risk of each target fault item using a percentage-based approach according to the fault code data risk assessment risk quantification table shown in Table 1 below, the corresponding quantified value can be obtained:

[0080] Table 1. Fault Code Data Assessment Risk Quantification Table

[0081]

[0082] Step S2023: Calculate the first safety risk assessment score based on the total number of alarm events for fault items in the hydrogen fuel cell vehicle to be evaluated and multiple quantified values.

[0083] Specifically, the first safety risk assessment score P1 can be calculated using the following relationship (2):

[0084]

[0085] In the formula: n represents the total number of alarm events for fault items in the hydrogen fuel cell vehicle to be evaluated; p i This represents the quantized value corresponding to each fault item alarm event.

[0086] The total score is 100, minus the sum of the quantitative percentage scores for each warning event. If the score is negative, the score is 0.

[0087] In one instance, if a vehicle experiences an insulation failure once within a week (quantified as 10%) and a total voltage overvoltage occurs once within 30 days (quantified as 2%), then the risk assessment score is 88.

[0088] Step S203: Based on the initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, a safety risk assessment is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and a second safety risk assessment score is obtained.

[0089] Specifically, step S203 includes:

[0090] Step S2031: Process the initial single-cell voltage dataset and the initial single-cell temperature dataset respectively to obtain the target single-cell voltage dataset and the target single-cell temperature dataset.

[0091] Specifically, for the initial single-cell voltage dataset V={V1,V2,…,V n} and the initial single-cell temperature dataset T = {T1, T2, ..., Tn Moving average filtering is applied to smooth the data and remove short-term outliers. Assume the filter window size is ω (the window size varies depending on the actual situation). The filtered voltage data is τV, and the filtered temperature data is τT.

[0092] The moving average formula (for each data point i) is shown in the following equations (3) and (4):

[0093]

[0094]

[0095] Furthermore, the deviation between each data point and its corresponding filtered value is calculated. The specific deviation calculation formulas are shown in the following relationships (5) and (6):

[0096] DVi=Vi-τVi (5)

[0097] DTi=Ti-τTi (6)

[0098] Furthermore, the standard deviation of the deviation dataset is calculated to measure the dispersion of the deviation. The standard deviation of the voltage data is σV, and the standard deviation of the temperature data is σT, as shown in the following equations (7) and (8):

[0099]

[0100]

[0101] Furthermore, the outlier detection criteria are as follows: the threshold is determined using the three-standard-deviation rule, and deviations exceeding three standard deviations are considered occasional outliers, as shown in the following equations (9) and (10):

[0102] Threshold_V=3*σV (9)

[0103] Threshold_T = 3 * σT (10)

[0104] Specifically, if DVi>Threshold_V or DTi>Threshold_T is detected, the detected outlier is removed from the original dataset, resulting in the voltage dataset τV and temperature dataset τT after removing the outliers.

[0105] Step S2032: Based on the target single cell voltage dataset, target single cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, thermal runaway detection is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and the target thermal runaway detection results are obtained.

[0106] Specifically, by combining the target cell voltage dataset and the target cell temperature dataset with the battery pack pressure dataset and the smoke concentration dataset to perform thermal runaway detection on the power battery system in the hydrogen fuel cell vehicle to be evaluated, the comprehensiveness of the detection can be improved.

[0107] In some optional implementations, step S2032 above includes:

[0108] Step b1: Based on the target cell voltage dataset and the target cell temperature dataset, perform thermal runaway detection on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and obtain the first thermal runaway detection result.

[0109] First, based on the target single cell temperature dataset, determine whether ΔT≥20℃ and the abnormality lasts for more than 5 frames. If it is satisfied, an alarm is triggered for excessive temperature difference.

[0110] Secondly, determine whether Tmax≥70℃ and 5 consecutive frames are triggered. If so, output an overheat alarm. (ΔT>15℃ and Tmax>60℃ are usually used as the failure threshold of the battery thermal management system. Considering thermal safety scenarios, ΔT(15+5℃) and Tmax(60+10℃) are set as overheat boundaries).

[0111] Then, based on the target single cell voltage dataset, the single cell voltage is judged to determine whether the minimum single cell voltage value is less than or equal to 2V. If it is satisfied, an alarm for low voltage is output.

[0112] Finally, determine whether the voltage difference of the individual unit is greater than 150mV and the number of abnormal frames is greater than or equal to 20 frames. If these conditions are met, output an alarm for excessive voltage difference.

[0113] Step b2: Based on the battery pack pressure dataset, perform thermal runaway detection on the power battery system inside the hydrogen fuel cell vehicle to be evaluated, and obtain the second thermal runaway detection result.

[0114] Specifically, the internal pressure of a normally functioning battery pack should be the same as the external atmospheric pressure, which is 101 kPa. When a single cell experiences thermal runaway and releases a large amount of high-temperature gas, the internal pressure of the battery pack rises rapidly, typically exceeding 120 kPa. This triggers the battery pack's pressure relief valve (explosion-proof valve), causing the pressure to drop rapidly. Subsequently, if a second cell experiences thermal runaway, the pressure will rise again. The pressure triggering conditions and recommended thresholds are shown in Table 2 below. If the triggering conditions are met, an output signal indicating excessively high or rapidly rising pressure will be generated.

[0115] Table 2. Barometric Pressure Triggering Conditions and Recommended Thresholds

[0116] signal source Triggering conditions Triggering conditions air pressure value High air pressure The air pressure value should be greater than or equal to a certain value (120 kPa recommended). Rate of change of air pressure The air pressure rises too quickly The rate of change in air pressure exceeds a certain value (10 kPa / s recommended).

[0117] Specifically, by conducting the tests as shown in Table 2 above, the corresponding second thermal runaway detection results can be obtained.

[0118] Step b3: Based on the smoke concentration dataset, perform thermal runaway detection on the power battery system inside the hydrogen fuel cell vehicle to be evaluated, and obtain the third thermal runaway detection result.

[0119] Specifically, the dust concentration in the air generally does not exceed 1000. To avoid false alarms of thermal runaway, it is determined whether the smoke concentration exceeds 5000 and persists for 1 second. If the trigger condition is met, a signal indicating excessively high smoke concentration is output. The smoke trigger conditions and recommended thresholds are shown in Table 3 below:

[0120] Table 3. Smoke Triggering Conditions and Recommended Thresholds

[0121]

[0122] Specifically, by conducting the tests as shown in Table 3 above, the corresponding third thermal runaway test results can be obtained.

[0123] Step b4: Based on the first thermal runaway detection result, the second thermal runaway detection result, and the third thermal runaway detection result, determine the target thermal runaway detection result.

[0124] Specifically, by combining the first, second, and third thermal runaway detection results and evaluating the power battery system inside the hydrogen fuel cell vehicle to be evaluated, the corresponding target thermal runaway detection result can be obtained.

[0125] According to the description of steps b1 to b3 above, the target thermal runaway detection results may include: single cell voltage overvoltage, single cell voltage undervoltage, single cell voltage difference too large, single cell temperature difference too large, single cell temperature too high, battery pack internal air pressure warning, smoke and dust concentration warning, etc.

[0126] Step S2033: Based on the thermal runaway detection results, determine the second safety risk assessment score.

[0127] Specifically, the second safety risk assessment score can be determined according to the power battery system scoring reference table shown in Table 4 below:

[0128] Table 4. Reference Table for Power Battery System Evaluation

[0129]

[0130] Step S204: Based on the initial hydrogen system dataset, a safety risk assessment is performed on the hydrogen system within the hydrogen fuel cell vehicle to be evaluated, resulting in a third safety risk assessment score. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0131] Step S205: Based on the first safety risk assessment score, the second safety risk assessment score, and the third safety risk assessment score, determine the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated, and send a warning message to the client based on the safety risk assessment result. For details, please refer to [link to relevant documentation]. Figure 1 Step S105 of the illustrated embodiment will not be described again here.

[0132] The vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles provided in this embodiment determines the total number of alarm events for fault items in the hydrogen fuel cell vehicle under assessment by evaluating target fault item data and combining alarm levels. Simultaneously, by combining the quantified values ​​of the target fault item data, a corresponding first safety risk assessment score can be obtained. Furthermore, based on voltage and temperature, it innovatively combines air pressure and smoke data to perform thermal runaway detection on the power battery system, thereby enabling a safety risk assessment of the power battery system within the hydrogen fuel cell vehicle under assessment. Simultaneously, based on the hydrogen system dataset, a safety risk assessment of the hydrogen system within the hydrogen fuel cell vehicle under assessment can be achieved. Furthermore, by combining the obtained three safety risk assessment scores to conduct a safety risk assessment of the hydrogen fuel cell vehicle under assessment, the comprehensiveness of the vehicle's safety risk assessment is improved compared to traditional assessment methods. Furthermore, by sending early warning information to the corresponding client in real time based on the assessment results, real-time safety early warnings for the hydrogen fuel cell vehicle under assessment can be achieved.

[0133] This embodiment provides a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles, which can be used in intelligent vehicle terminals connected to client terminals. Figure 1 This is a flowchart of a method for assessing and warning the safety risks of hydrogen fuel cell vehicles according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0134] Step S301: Obtain the fault code dataset, initial single-cell voltage dataset, initial single-cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset for the hydrogen fuel cell vehicle to be evaluated. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0135] Step S302: The fault code dataset is processed using a preset judgment method and risk quantification method to obtain the first safety risk assessment score. For details, please refer to [link to relevant documentation]. Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0136] Step S303: Based on the initial individual cell voltage dataset, initial individual cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, a safety risk assessment is performed on the power battery system within the hydrogen fuel cell vehicle to be evaluated, yielding a second safety risk assessment score. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0137] Step S304: Based on the initial hydrogen system dataset, conduct a safety risk assessment of the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and obtain a third safety risk assessment score.

[0138] Specifically, step S304 includes:

[0139] Step S3041: Perform filtering preprocessing on the initial hydrogen system dataset to obtain the target hydrogen system dataset.

[0140] Specifically, filtering the initial hydrogen system dataset yields the corresponding filtered target hydrogen system dataset. The filtering preprocessing can be referenced from the moving average filtering process in step S2031 above, and will not be elaborated upon here.

[0141] Step S3042: Based on the target hydrogen system dataset, perform a safety analysis on the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and obtain the hydrogen system safety analysis results.

[0142] In some optional implementations, step S3042 above includes:

[0143] Step c1 involves monitoring the hydrogen in the hydrogen system of the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset to obtain hydrogen leakage analysis results.

[0144] Step c2 involves monitoring the pressure of the hydrogen storage tank in the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, and obtaining the overpressure result of the hydrogen storage tank.

[0145] Step c3: Based on the target hydrogen system dataset, monitor the temperature of the hydrogen system inside the hydrogen fuel cell vehicle to be evaluated, and obtain the hydrogen system temperature monitoring results.

[0146] Step c4: Based on the hydrogen leak analysis results, hydrogen storage cylinder overpressure results, and hydrogen system temperature monitoring results, determine the hydrogen system safety analysis results.

[0147] First, assess the hydrogen leak situation:

[0148] (1) Monitor the hydrogen concentration and determine whether it exceeds the preset alarm value;

[0149] (2) Determine whether the pressure value of the hydrogen storage cylinder is decreasing.

[0150] Secondly, determine the overpressure status of the hydrogen storage cylinder: based on the hydrogen storage cylinder pressure data contained in the collected target hydrogen system dataset, it can be determined whether the pressure exceeds the preset nominal pressure threshold.

[0151] Finally, determine the temperature of the hydrogen system: based on the hydrogen cylinder temperature data contained in the collected target hydrogen system dataset, determine whether the hydrogen cylinder temperature exceeds the preset nominal temperature value or is less than -20℃.

[0152] Specifically, the threshold values ​​for the graded alarms involved in the above judgment process can be set by the user through remote configuration, as shown in Table 5 below:

[0153] Table 5. Alarm Value Thresholds for Hydrogen System Safety Analysis and Classification

[0154]

[0155] Specifically, by judging the hydrogen leakage, hydrogen storage cylinder overpressure, and hydrogen system temperature conditions in Table 5 above, the corresponding hydrogen system safety analysis results can be obtained.

[0156] According to Table 5 above, the safety analysis results of the hydrogen system may include: hydrogen pressure level 1 alarm, hydrogen pressure level 2 alarm, hydrogen pressure level 3 alarm, hydrogen system temperature level 1 alarm, hydrogen system temperature level 2 alarm, hydrogen system temperature level 3 alarm, hydrogen leakage level 1 alarm, hydrogen leakage level 2 alarm, and hydrogen leakage level 3 alarm.

[0157] Step S3043: Based on the results of the hydrogen system safety analysis, determine the third safety risk assessment score.

[0158] Specifically, the second safety risk assessment score can be determined according to the hydrogen system scoring reference table shown in Table 6 below:

[0159] Table 6. Hydrogen System Scoring Reference Table

[0160]

[0161] Step S305: Based on the first safety risk assessment score, the second safety risk assessment score, and the third safety risk assessment score, determine the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated, and send a warning message to the client based on the safety risk assessment result. For details, please refer to [link to relevant documentation]. Figure 1 Step S105 of the illustrated embodiment will not be described again here.

[0162] The vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles provided in this embodiment innovatively combines air pressure and smoke data analysis with voltage and temperature data to achieve safety risk assessment of the power battery system within the hydrogen fuel cell vehicle under evaluation. Simultaneously, based on the hydrogen system dataset, it can achieve safety risk assessment of the hydrogen system within the vehicle under evaluation. Furthermore, by combining the obtained three safety risk assessment scores, the safety risk assessment of the hydrogen fuel cell vehicle under evaluation is improved compared to traditional assessment methods, resulting in a more comprehensive assessment of vehicle safety risks. Furthermore, by sending early warning information to the corresponding client in real time based on the assessment results, real-time safety warnings for the hydrogen fuel cell vehicle under evaluation can be achieved.

[0163] In one instance, such as Figure 4 As shown, a method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles is provided, including:

[0164] (a) such as Figure 5A As shown, a safety risk assessment is conducted using a fault code data evaluation model, including:

[0165] Step 1: The intelligent vehicle terminal collects and stores the vehicle's fault code data.

[0166] Step 2: The terminal determines whether the vehicle fault alarm data has one or more strongly correlated fault items (fault items include total temperature difference alarm, drive motor and engine fault alarm, total voltage alarm, insulation alarm, and overcharge of on-board energy storage device) and whether they are three consecutive frames; whether they reach level three alarm; if all the above conditions are met, the corresponding fault item alarm is output.

[0167] Step 3: The fault code data evaluation model analyzes the collected fault code data. Based on fault code data collected within the past 90 days, the model quantifies the safety risk of strongly related vehicle faults on a percentage basis, as shown in Table 1 above.

[0168] Step 4: The fault code data evaluation model calculates the safety assessment score using the above formula (2), which is obtained by quantifying the number of each warning event. The total score is 100, minus the sum of the quantified percentage scores of each warning event. If the score is negative, the score is 0.

[0169] (ii) Figure 5B As shown, a thermal runaway risk early warning model is used to conduct a safety assessment of the power battery system, including:

[0170] Step 1: The terminal collects the individual battery voltage dataset V = {V1, V2, ..., V...} n} and temperature probe temperature dataset T={T1,T2,…,T n} and store them in timestamp order.

[0171] Step 2: The terminal preprocesses the data. For details, please refer to the description of step S2031 above.

[0172] Step 3: Refer to step b1.

[0173] Step 4: The terminal collects the air pressure data inside the battery pack and performs thermal runaway detection. For details, refer to step b2 above.

[0174] Step 5: The terminal uses the smoke alarm value output by the smoke sensor to perform thermal runaway detection. For details, refer to step b3 above.

[0175] Step 6: Referring to Table 4 above, the terminal evaluates and scores the power battery system. Compared to the traditional method of analyzing only the temperature and voltage of individual cells, the assessment combining temperature, voltage, air pressure, and smoke ensures detection speed while effectively reducing the probability of missed thermal runaway risks, greatly improving the accuracy of power battery safety risk assessment. The thermal runaway risk assessment and early warning output by the terminal are promptly sent to the platform, ensuring real-time performance.

[0176] Among them, the construction of the thermal runaway risk early warning model is as follows: Figure 5C As shown.

[0177] (III) Figure 5D As shown, a hydrogen system safety analysis and early warning model is used to conduct risk assessment and early warning for the hydrogen system:

[0178] Step 1: The terminal collects hydrogen system data, performs preprocessing and filtering, and uses it for subsequent combined analysis and early warning judgment.

[0179] Step Two: As Figure 6A As shown, to determine the hydrogen leak situation, refer to the description of S3042 above.

[0180] Step 3: As Figure 6B As shown, to determine the overpressure status of the hydrogen storage cylinder, refer to the description of S3042 above.

[0181] Step Four: As Figure 6C As shown, to determine the temperature of the hydrogen system, refer to the description of S3042 above.

[0182] Step 5: Evaluate and score the hydrogen system according to Table 6 above, generate risk assessment results, and enable the vehicle terminal to assess the safety of the hydrogen system.

[0183] (iv) Conduct a comprehensive safety risk assessment of the entire vehicle by integrating the three models:

[0184] The calculation results of the three models are combined, and linear weighting can be used. The weight allocation is determined according to the requirements of different vehicle models and manufacturers. The final risk assessment is reported to the platform in a timely manner. The scoring formula for the comprehensive safety risk assessment of the whole vehicle using linear weighting is shown in the above relationship (1).

[0185] This example provides a vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles. It establishes a thermal runaway risk assessment and early warning model for the battery system and a hydrogen system analysis and early warning model on the onboard terminal, enabling the terminal to conduct timely and accurate risk assessments and early warnings for both the battery and hydrogen systems of the hydrogen fuel cell vehicle. Compared to traditional terminals, this method combines assessments of vehicle fault codes, battery systems, and hydrogen systems, resulting in a more comprehensive risk assessment and early warning system. Recording the time, location, and type of vehicle safety risks and promptly alerting and reporting to the platform plays a positive role in timely handling of vehicle safety malfunctions, mitigating property damage, and ensuring the safety of drivers and passengers.

[0186] This embodiment also provides a vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0187] This embodiment provides a vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles, used in an intelligent vehicle terminal, which is connected to a client; such as Figure 7 As shown, it includes:

[0188] The acquisition module 701 is used to acquire the fault code dataset, initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset of the hydrogen fuel cell vehicle to be evaluated.

[0189] The processing module 702 is used to process the fault code dataset through a preset judgment method and a risk quantification method to obtain a first safety risk assessment score.

[0190] The first evaluation module 703 is used to conduct a safety risk assessment of the power battery system in the hydrogen fuel cell vehicle to be evaluated based on the initial single cell voltage dataset, the initial single cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, and obtain a second safety risk assessment score.

[0191] The second assessment module 704 is used to conduct a safety risk assessment of the hydrogen system in the hydrogen fuel cell vehicle to be assessed based on the initial hydrogen system dataset, and obtain a third safety risk assessment score.

[0192] The determination module 705 is used to determine the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated based on the first safety risk assessment score, the second safety risk assessment score, and the third safety risk assessment score, and to send early warning information to the client based on the safety risk assessment result.

[0193] In some alternative implementations, the processing module 702 includes:

[0194] The first processing submodule is used to process the fault code dataset through a preset judgment method to obtain the total number of fault alarm events of the hydrogen fuel cell vehicle to be evaluated.

[0195] The second processing submodule is used to quantify the target fault item data corresponding to each fault item alarm event using the risk quantification method, and obtain multiple quantified values.

[0196] The calculation submodule is used to calculate the first safety risk assessment score based on the total number of alarm events for fault items in the hydrogen fuel cell vehicle to be evaluated and multiple quantified values.

[0197] In some alternative implementations, the first processing submodule includes:

[0198] The first judgment unit is used to determine whether there is at least one target fault item data with a consecutive target frame number in the fault code dataset.

[0199] The second judgment unit is used to determine whether each target fault item data meets the preset alarm level when there are at least one consecutive target frame number of target fault item data in the fault code dataset.

[0200] The first determining unit is used to determine the total number of alarm events for fault items in the hydrogen fuel cell vehicle to be evaluated when the data of each target fault item meets the preset alarm level.

[0201] In some alternative implementations, the first evaluation module 703 includes:

[0202] The third processing submodule is used to process the initial single-cell voltage dataset and the initial single-cell temperature dataset respectively to obtain the target single-cell voltage dataset and the target single-cell temperature dataset.

[0203] The detection submodule is used to perform thermal runaway detection on the power battery system in the hydrogen fuel cell vehicle to be evaluated based on the target single cell voltage dataset, target single cell temperature dataset, battery pack pressure dataset, and smoke concentration dataset, and obtain the target thermal runaway detection results.

[0204] The first determination submodule is used to determine the second safety risk assessment score based on the thermal runaway detection results.

[0205] In some optional implementations, the detection submodule includes:

[0206] The first detection unit is used to perform thermal runaway detection on the power battery system in the hydrogen fuel cell vehicle to be evaluated based on the target single cell voltage dataset and the target single cell temperature dataset, and obtain the first thermal runaway detection result.

[0207] The second detection unit is used to perform thermal runaway detection on the power battery system inside the hydrogen fuel cell vehicle to be evaluated based on the battery pack pressure dataset, and obtain the second thermal runaway detection result.

[0208] The third detection unit is used to perform thermal runaway detection on the power battery system inside the hydrogen fuel cell vehicle to be evaluated based on the smoke concentration dataset, and obtain the third thermal runaway detection result.

[0209] The second determining unit is used to determine the target thermal runaway detection result based on the first thermal runaway detection result, the second thermal runaway detection result, and the third thermal runaway detection result.

[0210] In some alternative implementations, the second evaluation module 704 includes:

[0211] The fourth processing submodule is used to perform filtering preprocessing on the initial hydrogen system dataset to obtain the target hydrogen system dataset.

[0212] The analysis submodule is used to perform a safety analysis of the hydrogen system in the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, and obtain the hydrogen system safety analysis results.

[0213] The second determination submodule is used to determine the third safety risk assessment score based on the results of the hydrogen system safety analysis.

[0214] In some optional implementations, the intelligent vehicle terminal connects to a client; the analysis submodule includes:

[0215] The first monitoring unit is used to monitor the hydrogen in the hydrogen system of the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, and obtain hydrogen leakage analysis results.

[0216] The second monitoring unit is used to monitor the pressure of the hydrogen storage tank in the hydrogen system of the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, and to obtain the overpressure result of the hydrogen storage tank.

[0217] The third monitoring unit is used to monitor the temperature of the hydrogen system inside the hydrogen fuel cell vehicle to be evaluated based on the target hydrogen system dataset, and obtain the hydrogen system temperature monitoring results.

[0218] The third determining unit is used to determine the safety analysis results of the hydrogen system based on the hydrogen leakage analysis results, the hydrogen storage cylinder overpressure results, and the hydrogen system temperature monitoring results.

[0219] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0220] In this embodiment, the vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0221] This invention also provides a computer device having the above-described features. Figure 7 The device shown is a vehicle safety risk assessment and early warning system for hydrogen fuel cell vehicles.

[0222] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 8 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 8 Take a processor 10 as an example.

[0223] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0224] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0225] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0226] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0227] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0228] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0229] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for assessing and warning of vehicle safety risks in hydrogen fuel cell vehicles, characterized in that, For use in intelligent vehicle terminals, the intelligent vehicle terminals being connected to a client; the method includes: Obtain the fault code dataset, initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset of the hydrogen fuel cell vehicle to be evaluated; The fault code dataset is processed using a preset judgment method and a risk quantification method to obtain a first safety risk assessment score; Based on the initial individual cell voltage dataset, the initial individual cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, a safety risk assessment is performed on the power battery system inside the hydrogen fuel cell vehicle to be evaluated, and a second safety risk assessment score is obtained. Based on the initial hydrogen system dataset, a safety risk assessment is performed on the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and a third safety risk assessment score is obtained. Based on the first safety risk assessment score, the second safety risk assessment score, and the third safety risk assessment score, the safety risk assessment result of the hydrogen fuel cell vehicle to be assessed is determined, and a warning message is sent to the client based on the safety risk assessment result; The fault code dataset is processed using a preset judgment method and a risk quantification method to obtain a first safety risk assessment score, including: The fault code dataset is processed by a preset judgment method to obtain the total number of fault alarm events of the hydrogen fuel cell vehicle to be evaluated. The risk quantification method is used to quantify the target fault item data corresponding to each fault item alarm event to obtain multiple quantified values; The first safety risk assessment score is calculated based on the total number of alarm events for fault items of the hydrogen fuel cell vehicle to be evaluated and the multiple quantitative values. The first security risk assessment score is expressed as the following formula: In the formula: This indicates the first safety risk assessment score; This indicates the total number of alarm events related to malfunctions in the hydrogen fuel cell vehicle to be evaluated. This represents the quantized value corresponding to each fault item alarm event.

2. The method according to claim 1, characterized in that, The fault code dataset is processed using a preset judgment method to obtain the total number of fault alarm events occurring in the hydrogen fuel cell vehicle to be evaluated, including: Determine whether there is at least one target fault item data with a consecutive target frame number in the fault code dataset; When there are at least one consecutive target frame number of target fault item data in the fault code dataset, determine whether each target fault item data meets the preset alarm level; When the data for each target fault item meets the preset alarm level, the total number of fault item alarm events of the hydrogen fuel cell vehicle to be evaluated is determined.

3. The method according to claim 1, characterized in that, Based on the initial individual cell voltage dataset, the initial individual cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, a safety risk assessment is performed on the power battery system of the hydrogen fuel cell vehicle to be evaluated, resulting in a second safety risk assessment score, including: The initial single-cell voltage dataset and the initial single-cell temperature dataset are processed respectively to obtain the target single-cell voltage dataset and the target single-cell temperature dataset; Based on the target single cell voltage dataset, the target single cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, thermal runaway detection is performed on the power battery system inside the hydrogen fuel cell vehicle to be evaluated, and the target thermal runaway detection result is obtained. Based on the thermal runaway detection results, the second safety risk assessment score is determined.

4. The method according to claim 3, characterized in that, Based on the target single-cell voltage dataset, the target single-cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, thermal runaway detection is performed on the power battery system of the hydrogen fuel cell vehicle to be evaluated, and the target thermal runaway detection results are obtained, including: Based on the target single cell voltage dataset and the target single cell temperature dataset, thermal runaway detection is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated, and a first thermal runaway detection result is obtained. Based on the battery pack pressure dataset, thermal runaway detection is performed on the power battery system in the hydrogen fuel cell vehicle to be evaluated to obtain a second thermal runaway detection result. Based on the smoke concentration dataset, thermal runaway detection is performed on the power battery system inside the hydrogen fuel cell vehicle to be evaluated, and a third thermal runaway detection result is obtained. Based on the first thermal runaway detection result, the second thermal runaway detection result, and the third thermal runaway detection result, the target thermal runaway detection result is determined.

5. The method according to claim 1, characterized in that, Based on the initial hydrogen system dataset, a safety risk assessment is performed on the hydrogen system within the hydrogen fuel cell vehicle to be evaluated, resulting in a third safety risk assessment score, including: The initial hydrogen system dataset is filtered and preprocessed to obtain the target hydrogen system dataset; Based on the target hydrogen system dataset, a safety analysis of the hydrogen system in the hydrogen fuel cell vehicle to be evaluated is performed to obtain the hydrogen system safety analysis results. Based on the results of the hydrogen system safety analysis, the third safety risk assessment score is determined.

6. The method according to claim 5, characterized in that, Based on the target hydrogen system dataset, a safety analysis is performed on the hydrogen system in the hydrogen fuel cell vehicle to be evaluated, and the hydrogen system safety analysis results are obtained, including: Based on the target hydrogen system dataset, the hydrogen in the hydrogen system of the hydrogen fuel cell vehicle to be evaluated is monitored to obtain hydrogen leakage analysis results. Based on the target hydrogen system dataset, the pressure of the hydrogen storage tank in the hydrogen fuel cell vehicle to be evaluated is monitored to obtain the overpressure result of the hydrogen storage tank. Based on the target hydrogen system dataset, the temperature of the hydrogen system inside the hydrogen fuel cell vehicle to be evaluated is monitored to obtain the hydrogen system temperature monitoring results. Based on the hydrogen leakage analysis results, the hydrogen storage cylinder overpressure results, and the hydrogen system temperature monitoring results, the hydrogen system safety analysis results are determined.

7. A vehicle safety risk assessment and early warning device for hydrogen fuel cell vehicles, characterized in that, For use in intelligent vehicle terminals, the intelligent vehicle terminals being connected to a client; the device includes: The acquisition module is used to acquire the fault code dataset, initial single cell voltage dataset, initial single cell temperature dataset, battery pack pressure dataset, smoke concentration dataset, and initial hydrogen system dataset of the hydrogen fuel cell vehicle to be evaluated. The processing module is used to process the fault code dataset through a preset judgment method and a risk quantification method to obtain a first safety risk assessment score; The first evaluation module is used to conduct a safety risk assessment of the power battery system in the hydrogen fuel cell vehicle to be evaluated based on the initial single cell voltage dataset, the initial single cell temperature dataset, the battery pack pressure dataset, and the smoke concentration dataset, and obtain a second safety risk assessment score. The second assessment module is used to conduct a safety risk assessment of the hydrogen system in the hydrogen fuel cell vehicle to be assessed based on the initial hydrogen system dataset, and obtain a third safety risk assessment score. The determination module is used to determine the safety risk assessment result of the hydrogen fuel cell vehicle to be evaluated based on the first safety risk assessment score, the second safety risk assessment score and the third safety risk assessment score, and to send a warning message to the client based on the safety risk assessment result; The processing module includes: The first processing submodule is used to process the fault code dataset through a preset judgment method to obtain the total number of fault alarm events of the hydrogen fuel cell vehicle to be evaluated. The second processing submodule is used to quantify the target fault item data corresponding to each fault item alarm event using the risk quantification method to obtain multiple quantified values. The calculation submodule is used to calculate the first safety risk assessment score based on the total number of alarm events for fault items of the hydrogen fuel cell vehicle to be evaluated and the multiple quantified values. The first security risk assessment score is expressed as follows: In the formula: This indicates the first safety risk assessment score; This indicates the total number of alarm events related to malfunctions in the hydrogen fuel cell vehicle to be evaluated. This represents the quantized value corresponding to each fault item alarm event.

8. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the vehicle safety risk assessment and early warning method for hydrogen fuel cell vehicles according to any one of claims 1 to 6.

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