Safety early warning method and device for new energy vehicle and storage medium

Abstract

The invention discloses a safety early warning method and device for a new energy vehicle and a storage medium. The safety early warning device can receive operation data of the new energy vehicle; wherein the operation data at least comprises insulation resistance information of the battery and state information of the new energy vehicle; determining a first threshold value according to the state information, and determining change rate information and change trend information of the insulation resistance value according to the insulation resistance value information; performing risk analysis processing based on the first threshold value, the change rate information and the change trend information to obtain a risk analysis result of the new energy vehicle; wherein the risk analysis result is used for determining whether the new energy vehicle has a risk and determining the type of the risk; when the risk analysis result shows that the new energy vehicle has the risk, risk early warning information of the new energy vehicle is generated according to the risk analysis result; based on the above scheme, the risk of the new energy vehicle can be effectively detected and early warning can be performed in time.

Description

Technical Field

[0001] This application relates to the field of vehicle alarm technology, and in particular to a safety early warning method, device and storage medium for new energy vehicles. Background Technology

[0002] New energy vehicles may experience chassis collisions during operation, causing deformation of the bottom tray of the battery pack. When the deformation is too large, it may lead to deformation of the battery cells or deformation and damage of the liquid cooling plate at the bottom of the battery pack, or water entering the battery pack after a collision, resulting in prolonged immersion; ultimately leading to thermal runaway of the battery pack.

[0003] Currently, thermal runaway alarms are triggered based on whether the vehicle's condition reaches an alarm threshold at a specific point in time. However, in most cases, new energy vehicles do not immediately reach the thermal runaway alarm threshold after a chassis collision, and may not even reach it after a period of use. This means that current methods can only trigger alarms when a fault occurs, and cannot dynamically detect, analyze, and warn of potential safety risks in advance. Therefore, how to detect and analyze potential safety risks in new energy vehicles and provide timely warnings is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a safety early warning method, device, and storage medium for new energy vehicles, which can effectively detect the risks present in new energy vehicles and provide timely early warnings.

[0005] The technical solution of this application embodiment is implemented as follows:

[0006] In a first aspect, embodiments of this application provide a safety warning method for new energy vehicles, the method comprising:

[0007] Receive operational data from new energy vehicles; the operational data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle.

[0008] The first threshold is determined based on the status information, and the rate of change and trend of change of the insulation resistance are determined based on the insulation resistance information.

[0009] Risk analysis is performed based on the first threshold, rate of change information, and trend of change information to obtain the risk analysis results for new energy vehicles; the risk analysis results are used to determine whether new energy vehicles have risks and the types of risks that exist.

[0010] If the risk analysis results indicate that new energy vehicles pose a risk, risk warning information for new energy vehicles will be generated based on the risk analysis results.

[0011] In the embodiments of this application, the safety warning device can receive the operating data sent by the new energy vehicle in real time, and then determine a matching first threshold based on the status information of the new energy vehicle in the operating data, and determine the rate of change and trend of change of insulation resistance in the operating data. By using the first threshold and the rate of change and trend of change of insulation resistance, the device can analyze whether there is a risk to the new energy vehicle and the type of risk. It can effectively detect the risks of the new energy vehicle in real time, and when it is determined that there is a risk to the new energy vehicle, it can generate risk warning information based on the risk analysis results, and provide timely warning of the risks to the new energy vehicle.

[0012] In some embodiments of this application, the status information includes charging status information and component status information; determining a first threshold based on the status information includes:

[0013] A first threshold is determined based on charging status information and / or component status information; wherein, charging status information is used to determine whether the new energy vehicle is in a charging state; and component status information represents whether the components in the new energy vehicle other than the battery are in an on state.

[0014] In this embodiment, the specific value of the first threshold can be determined based on whether the new energy vehicle is currently charging and whether the components in the new energy vehicle other than the battery are turned on. By using the first threshold for risk analysis, the risk can be measured more accurately for the operating status of the new energy vehicle, thereby improving the accuracy of risk analysis.

[0015] In some embodiments of this application, determining the rate of change and trend information of insulation resistance based on insulation resistance information includes:

[0016] The insulation resistance value information of new energy vehicles under the same working condition is divided and processed according to a preset time period to obtain multiple insulation resistance value sets.

[0017] The average value corresponding to each of the multiple sets of insulation resistance values ​​is determined to obtain multiple average values;

[0018] The rate of change and trend information are determined based on multiple average values.

[0019] In this embodiment, the insulation resistance information of new energy vehicles under the same operating conditions can be divided into multiple insulation resistance sets according to a preset time period. Then, the average value of each insulation resistance set is calculated, and the rate of change and trend of change of insulation resistance can be determined by using multiple average values. This enables effective analysis of the rate of change and trend of change of battery insulation resistance.

[0020] In some embodiments of this application, the rate of change information and the trend of change information are determined based on multiple average values, including:

[0021] Iquartile analysis is performed on multiple average values ​​to obtain information on trends.

[0022] The difference is calculated between any two adjacent averages from a set of multiple averages to obtain the difference result.

[0023] The rate of change is calculated based on the difference results, and the calculated rate of change is determined as the rate of change information.

[0024] In this embodiment, the safety warning device can determine the trend of change in insulation resistance by performing quartile analysis on multiple average values. At the same time, it can determine the rate of change by determining the difference between every two adjacent average values, thus accurately assessing the trend and rate of change of insulation resistance.

[0025] In some embodiments of this application, the risk analysis results include a first risk analysis result; the first risk analysis result is used to determine whether the new energy vehicle faces a chassis collision risk; risk analysis processing is performed based on a first threshold, change rate information, and change trend information to obtain the risk analysis results of the new energy vehicle, including:

[0026] If the trend information shows a gradual decrease and the rate of change is greater than the first threshold, the first risk analysis result is determined to be that new energy vehicles have a risk of chassis collision; otherwise, the first risk analysis result is determined to be that new energy vehicles do not have a risk of chassis collision.

[0027] In this embodiment, when performing risk analysis on new energy vehicles, the risk of chassis collision can be analyzed first. This includes using a first threshold to measure the rate of change and whether the trend of change is gradually decreasing. Only when the trend of change of insulation resistance is gradually decreasing and the rate of change is greater than the first threshold is it determined that the new energy vehicle has a risk of chassis collision. Otherwise, it is determined that the new energy vehicle does not have a risk of chassis collision. This allows for real-time and accurate detection of whether a new energy vehicle has a risk of chassis collision, improving the ability to detect risks in new energy vehicles.

[0028] In some embodiments of this application, the risk analysis results further include a second risk analysis result, which is used to determine whether the new energy vehicle has a risk of thermal runaway; the method further includes:

[0029] Given that the first risk analysis result indicates that new energy vehicles face a risk of chassis collision, a second risk analysis result is obtained by performing a thermal runaway risk analysis based on the battery temperature data in the operating data.

[0030] In this embodiment, if it is determined that there is a risk of chassis collision with the new energy vehicle, the battery temperature data of the new energy vehicle can be monitored and analyzed to detect whether there is a risk of thermal runaway in the new energy vehicle, thereby achieving effective detection of multiple risk types.

[0031] In some embodiments of this application, a risk analysis of thermal runaway is performed based on battery temperature data from the operational data to obtain a second risk analysis result, including at least one of the following:

[0032] The highest battery cell temperature in the battery temperature data is compared with the second threshold. If the highest battery cell temperature is greater than the second threshold, the second risk analysis result is determined to be that the new energy vehicle has a risk of thermal runaway.

[0033] The temperature difference information of the battery temperature data is determined, and the temperature difference information is compared with the third threshold. If the comparison result shows that the temperature difference information is greater than the third threshold, the second risk analysis result is determined to be that the new energy vehicle has the risk of thermal runaway.

[0034] The temperature rise rate information of the battery temperature data is determined, and the temperature rise rate information is compared with the fourth threshold. If the comparison result shows that the temperature rise rate information is greater than the fourth threshold, the second risk analysis result is determined to be that the new energy vehicle has a risk of thermal runaway. Among them, the temperature rise rate information represents the rate at which the battery temperature rises.

[0035] In this embodiment, when determining whether a battery has a risk of thermal runaway, the risk of thermal runaway in a new energy vehicle can be determined if the highest single cell temperature in the battery temperature data, and / or the temperature difference of the battery is greater than a third threshold, and / or the temperature rise rate of the battery is greater than a fourth threshold. This enables effective detection of whether a new energy vehicle has a risk of thermal runaway.

[0036] In some embodiments of this application, determining the temperature difference information of the battery temperature data includes:

[0037] Obtain the highest and lowest individual cell temperatures from the battery temperature data;

[0038] Determine the difference between the highest and lowest battery cell temperatures, and use this difference as temperature difference information.

[0039] In this embodiment, when determining the temperature difference information, the difference between the highest and lowest battery cell temperatures in the battery temperature data can be calculated to obtain the temperature difference information, thereby realizing the effective calculation of the temperature difference of the battery in new energy vehicles.

[0040] In some embodiments of this application, the method further includes:

[0041] If an insulation fault is determined to exist in a new energy vehicle based on the insulation fault identification information in the operating data, an insulation fault alarm message is generated; the insulation fault identification information is the identification information generated by the battery management system in the new energy vehicle after performing insulation detection on the battery.

[0042] In this embodiment, if it is determined that a new energy vehicle has an insulation fault based on the insulation fault identification information in the operating data, no risk analysis processing is required, and an insulation fault alarm information can be directly generated to promptly identify the current insulation fault in the new energy vehicle and improve the intelligence of fault detection.

[0043] Secondly, embodiments of this application provide a security early warning device, which includes a receiving unit, a determining unit, an analyzing unit, and a generating unit;

[0044] The receiving unit is used to receive the operating data of the new energy vehicle; wherein, the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle;

[0045] The determining unit is used to determine the first threshold based on the status information, and to determine the rate of change and trend information of the insulation resistance based on the insulation resistance information;

[0046] The analysis unit is used to perform risk analysis based on a first threshold, rate of change information, and trend of change information to obtain risk analysis results for new energy vehicles; the risk analysis results are used to determine whether new energy vehicles have risks and the types of risks that exist.

[0047] The generation unit is used to generate risk warning information for new energy vehicles based on the risk analysis results, when the risk analysis results indicate that new energy vehicles pose a risk.

[0048] In this embodiment, the safety warning device can receive the operating data sent by the new energy vehicle in real time. Then, it can determine a matching first threshold based on the status information of the new energy vehicle in the operating data, and determine the rate of change and trend of change of insulation resistance in the operating data. By using the first threshold and the rate and trend of change of insulation resistance, it can analyze whether there is a risk to the new energy vehicle and the type of risk. It can effectively detect the risks of the new energy vehicle in real time. When it is determined that there is a risk to the new energy vehicle, it can generate risk warning information based on the risk analysis results, and provide timely warning of the risks to the new energy vehicle.

[0049] Thirdly, embodiments of this application provide a safety warning device, including a processor and a memory storing processor-executable instructions; when the instructions are executed by the processor, the aforementioned safety warning method for new energy vehicles is implemented.

[0050] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned safety warning method for new energy vehicles. Attached Figure Description

[0051] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application.

[0052] Figure 1 This is a schematic diagram illustrating the implementation process of the safety early warning method for new energy vehicles proposed in this application. Figure 1 ;

[0053] Figure 2 This is a schematic diagram illustrating the implementation of the safety warning method for new energy vehicles proposed in this application embodiment;

[0054] Figure 3 This is a schematic diagram illustrating the implementation process of the safety early warning method for new energy vehicles proposed in this application. Figure 2 ;

[0055] Figure 4 This is a schematic diagram illustrating the implementation process of the safety early warning method for new energy vehicles proposed in this application. Figure 3 ;

[0056] Figure 5 This is a schematic diagram of the risk management method for new energy vehicles proposed in the embodiments of this application;

[0057] Figure 6 This is a schematic diagram of the composition of the safety early warning device proposed in the embodiments of this application. Figure 1 ;

[0058] Figure 7 This is a schematic diagram of the composition of the safety early warning device proposed in the embodiments of this application. Figure 2 . Detailed Implementation

[0059] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining the relevant application and not for limiting the application. Furthermore, it should be noted that, for ease of description, only the parts related to the relevant application are shown in the accompanying drawings.

[0060] For new energy vehicles, chassis impacts during driving can cause deformation of the battery pack's bottom tray. Excessive deformation may cause the bottom of the battery pack to contact the bottom of the cells, leading to cell deformation or damage to the liquid cooling plate which may penetrate the cells. Water ingress after an impact can also cause prolonged immersion. These situations can easily lead to thermal runaway. Even with minor deformation or no contact with the cell bottom, contact with the cells or deformation of the liquid cooling plate can block the main or secondary flow channels, causing the liquid cooling system to fail. Prolonged use under these conditions can lead to cell temperature control failure and thermal runaway. The national standard for Class 1 insulation resistance alarms requires a threshold of ≥100Ω / V. However, typical new energy vehicle chassis impacts do not immediately reach this standard, and may even persist for some time. Therefore, a chassis impact in a new energy vehicle puts it in a dangerous state, and continued use could lead to thermal runaway. In other words, current alarm methods only alert at the time of the fault and lack early warning capabilities, failing to adequately anticipate potential impacts or battery pack-related risks.

[0061] Furthermore, current methods for alerting to vehicle anomalies, such as judging insulation resistance, only determine whether the vehicle's condition reaches an alarm threshold at a specific point in time. These methods monitor the insulation resistance of the entire vehicle, including the power battery, vehicle components, and the charging pile connected in parallel. These alarm systems typically only issue warnings when the overall vehicle insulation resistance or temperature reaches a dangerous threshold, failing to predict potential battery problems in advance. This limits their effectiveness as an early warning mechanism. They cannot provide warnings for batteries where insulation resistance fluctuates within a reasonable range after a chassis impact leading to water ingress or internal condensation, but subsequently experiences internal or external short circuits due to deformation of the cell bottom or top of an inverted cell after a certain number of battery cycles, or where bottom deformation from an impact causes blockage of the liquid cooling plate, leading to abnormal temperatures and ultimately thermal runaway risks. Additionally, current methods may be limited by the Battery Management System (BMS). The data processing capabilities of a system (BMS) are insufficient to handle large amounts of complex data and cannot predict the risks that exist in a vehicle. These are all passive response mechanisms, meaning that they only respond after a risk or malfunction occurs, and cannot proactively prevent problems from happening.

[0062] To address the current problems in data transmission and interaction in power systems, this application provides a safety early warning method, device, and storage medium for new energy vehicles. The safety early warning device can receive operating data from new energy vehicles. The operating data includes at least battery insulation resistance information and new energy vehicle status information. A first threshold is determined based on the new energy vehicle status information, and the rate of change and trend information of the insulation resistance are determined based on the insulation resistance information. Risk analysis is performed based on the first threshold, the rate of change information, and the trend information to obtain a risk analysis result for the new energy vehicle. The risk analysis result is used to determine whether the new energy vehicle has a risk and the type of risk. If the risk analysis result indicates that the new energy vehicle has a risk, a risk early warning message is generated based on the risk analysis result, thereby effectively detecting the risks of the new energy vehicle and providing timely warnings.

[0063] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0064] One embodiment of this application provides a safety early warning method for new energy vehicles, such as... Figure 1 As shown, the safety warning method for new energy vehicles with a safety warning device may include the following steps:

[0065] Step 101: Receive the operating data of the new energy vehicle; the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle.

[0066] In the embodiments of this application, the safety warning device can receive the operating data of the new energy vehicle; wherein, the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle.

[0067] In some embodiments of this application, the safety warning device can simultaneously receive operating data uploaded by multiple new energy vehicles.

[0068] In some embodiments of this application, after receiving the operating data of a new energy vehicle, the safety warning device can process the operating data to obtain processed operating data. The data processing can include data cleaning and missing data completion. Data cleaning can be used to remove abnormal and duplicate data from the operating data, and missing data completion can be used to fill in the missing data in the operating data.

[0069] For example, suppose that after receiving the operating data of a new energy vehicle, the safety warning device finds that the individual battery temperature data only includes the temperature data of 95 batteries, while the new energy vehicle has a total of 96 batteries. In this case, the safety warning device can obtain the temperature data of the missing battery sent by the new energy vehicle to make up for the missing data. Alternatively, if the safety warning device determines that a certain type of information is missing, such as charging status information, it can instruct the new energy vehicle to send that type of information to make up for the missing data.

[0070] It is understood that, in the embodiments of this application, the data obtained after data processing of the running data is the processed running data.

[0071] In some embodiments of this application, the safety early warning device can store the processed operating data in a database after obtaining the processed operating data, and at the same time complete subsequent risk analysis processing based on the processed operating data.

[0072] For example, the data collection module in a new energy vehicle can upload the collected operating data to the safety warning device at an upload frequency of ≤30 seconds. The safety warning device can process the operating data and then store the processed operating data in a data warehouse. The length of the processed operating data can be more than one week.

[0073] It is understood that, in the embodiments of this application, the safety warning device can simultaneously receive operating data sent by multiple different new energy vehicles, thereby enabling the analysis of the risks or potential risks of each new energy vehicle.

[0074] In the embodiments of this application, the safety warning device can be a server, such as a cloud server, which can receive the operating data uploaded by new energy vehicles in real time and analyze in real time whether the new energy vehicles have various risks or potential risks.

[0075] In the embodiments of this application, the new energy vehicle can be a new energy vehicle equipped with a battery; the insulation resistance information of the battery can be the insulation resistance information of the battery in the new energy vehicle.

[0076] In the embodiments of this application, the operating data can be the relevant operating data of the new energy vehicle collected in real time by various sensors in the new energy vehicle, including the relevant operating data of the new energy vehicle's battery and / or components other than the battery.

[0077] In some embodiments of this application, in addition to battery data and / or data related to the operation of components other than the battery, the operating data may also include time information and identification information of the new energy vehicle. The time information may include the reporting time when the new energy vehicle reports the operating data to the safety warning device, and the identification information of the new energy vehicle may be the vehicle's identification information, such as the Vehicle Identification Number (VIN). Thus, when the safety warning device receives the operating data of the new energy vehicle, it can also generate the receiving time of the operating data and determine the new energy vehicle corresponding to the operating data based on the identification information of the new energy vehicle.

[0078] For example, new energy vehicles may include various sensors for detecting the insulation resistance, temperature, voltage, and current of the power battery in the new energy vehicle; new energy vehicles may also include a data collection module for receiving data collected by various sensors and summarizing this data to send the vehicle's operating data to a safety warning device.

[0079] For example, the operational data may include reporting time information, receiving time information, VIN code, charging status information, charging information, insulation resistance value, individual battery temperature, highest individual battery temperature, lowest individual battery temperature, total voltage, high-voltage insulation fault flag, high-voltage insulation detection circuit fault flag, power battery relay status, and component relay status. The charging status information can be used to determine whether the new energy vehicle is charging. The charging information may include information such as charging in progress, fast charging, slow charging, and charging complete. The insulation resistance value can be the insulation resistance value of the battery. The individual battery temperature is the current temperature of the individual battery; the highest individual battery temperature is the highest temperature among the currently received individual battery temperatures; the lowest individual battery temperature is the lowest temperature among the currently received individual battery temperatures; the total voltage can be the total voltage of all batteries; the high-voltage insulation fault flag can be used to determine whether an insulation fault exists; the high-voltage insulation detection circuit fault flag can be used to determine whether the detection circuit used to detect whether an insulation fault exists is faulty; the power battery relay status can be used to determine whether the battery is in a working state; and the component relay status can be used to determine whether components other than the power battery are in an on / off state.

[0080] In the embodiments of this application, the battery may be assembled from one or more cells; the battery may be a single battery cell. A single battery cell refers to a basic unit capable of converting chemical energy into electrical energy, and can be used to manufacture battery modules or battery packs for supplying power to electrical devices. A single battery cell may be a rechargeable battery, which is a battery cell that can be recharged after discharge to reactivate its active materials and continue to be used. A single battery cell may be a lithium-ion battery, sodium-ion battery, sodium-lithium-ion battery, lithium metal battery, sodium metal battery, lithium-sulfur battery, magnesium-ion battery, nickel-metal hydride battery, nickel-cadmium battery, lead-acid battery, etc., and the embodiments of this application are not limited to these types.

[0081] In embodiments of this application, the battery may also be a single physical module comprising one or more battery cells to provide higher voltage and capacity. When there are multiple battery cells, the multiple battery cells are connected in series, parallel, or mixed via a busbar.

[0082] In the embodiments of this application, the safety warning device can generate insulation fault alarm information when it is determined that there is an insulation fault in the new energy vehicle based on the insulation fault identification information in the operating data; wherein, the insulation fault identification information can be the identification information generated by the battery management system in the new energy vehicle after performing insulation detection on the battery.

[0083] For example, the insulation fault identification information can be a flag bit, such as a high-voltage insulation fault flag bit. When the high-voltage insulation fault flag bit is 1, it indicates that the new energy vehicle has an insulation fault, while when the high-voltage insulation fault flag bit is 0, it indicates that the new energy vehicle does not have an insulation fault. The BMS in the new energy vehicle can perform insulation fault detection on the battery. For example, it can use an insulation fault detection circuit to detect whether the battery has an insulation fault and generate insulation fault identification information.

[0084] Step 102: Determine the first threshold based on the status information, and determine the rate of change and trend information of the insulation resistance based on the insulation resistance information.

[0085] In the embodiments of this application, the safety warning device can determine a first threshold based on the status information after receiving the operating data of the new energy vehicle, and determine the rate of change information and trend information of the insulation resistance based on the insulation resistance information.

[0086] In the embodiments of this application, when the safety warning device determines the first threshold based on the status information of the new energy vehicle, it determines the first threshold based on the status information of the new energy vehicle in the processed operating data; and when it determines the rate of change information and trend information of the insulation resistance value based on the insulation resistance value information, it determines the rate of change information and trend information based on the insulation resistance value information in the processed operating data.

[0087] It is understood that, in the embodiments of this application, the insulation resistance information may include the insulation resistance of the power battery of the new energy vehicle.

[0088] In some embodiments of this application, the status information includes charging status information and component status information; when the safety warning device determines the first threshold based on the status information of the new energy vehicle, it can determine the first threshold based on the charging status information and / or component status information; wherein, the charging status information is used to determine whether the new energy vehicle is in a charging state; the component status information is used to determine whether the components in the new energy vehicle other than the battery are in an on state.

[0089] For example, the component status information can be the component relay status, so that the safety warning device can determine whether the component other than the power battery is in the on state based on the component relay status. For example, the component can be the air conditioner. When the air conditioner relay status is in the on state, it indicates that the air conditioner in the new energy vehicle is in the on state.

[0090] For example, the charging status information may include states such as charging, driving, and stationary; the safety warning device can determine whether the new energy vehicle is in a charging state based on the charging status information.

[0091] In the embodiments of this application, since the insulation resistance of a new energy vehicle is lower than that when it is not charging due to the influence of the charging pile when it is charging, and also when other components are turned on, the insulation resistance will also be affected and reduced. Therefore, if a uniform threshold or standard is used to perform risk analysis on the insulation resistance information of new energy vehicles, the accuracy of the analysis will be affected. Based on this, this application determines a matching first threshold based on the charging status information and / or component status information, and then uses the first threshold to perform risk analysis on the insulation resistance information, which can greatly improve the accuracy of risk analysis.

[0092] In some embodiments of this application, the first threshold may include a fifth threshold and a sixth threshold; when the safety warning device determines the first threshold based on the charging status information and / or component status information in the operating data, it may determine the first threshold as the fifth threshold if the charging status information is in the charging state; and determine the first threshold as the sixth threshold if the charging status information is not in the charging state; the fifth threshold is less than the sixth threshold.

[0093] In some embodiments of this application, the first threshold may further include a seventh threshold and an eighth threshold; the safety warning device may also determine the first threshold as the seventh threshold when the component status information is on, and determine the first threshold as the eighth threshold when the component status information is off, wherein the seventh threshold is less than the eighth threshold.

[0094] In some embodiments of this application, the first threshold may further include a ninth threshold; the safety warning device may also determine the first threshold as the ninth threshold when the charging status information is charging and the component status information is on, and the ninth threshold may be less than the fifth threshold and the seventh threshold.

[0095] In some embodiments of this application, in addition to determining the threshold based on whether the new energy vehicle is in a charging state, different thresholds can be set according to the states other than the charging state in the charging state information to achieve more accurate risk analysis. In some embodiments, the sixth threshold may also include the tenth threshold and the eleventh threshold. The safety warning device may also determine the sixth threshold as the tenth threshold when the charging state information is driving, and determine the sixth threshold as the eleventh threshold when the charging state information is stationary. The tenth threshold and the eleventh threshold may be different.

[0096] In the embodiments of this application, in addition to processing and analyzing the real-time operating data of new energy vehicles, the safety warning device can also analyze the historical data of new energy vehicles, such as data from a week, a month, or half a year, in order to assess their performance change trends.

[0097] In some embodiments of this application, when the safety warning device determines the rate of change information and trend information of insulation resistance based on the insulation resistance information, it can divide the insulation resistance information of new energy vehicles under the same working condition according to a preset time period to obtain multiple insulation resistance sets; then determine the average value corresponding to each of the multiple insulation resistance sets to obtain multiple average values; and thus determine the rate of change information and trend information based on the multiple average values.

[0098] In the embodiments of this application, the safety warning device needs to first organize the insulation resistance information, mainly organizing the insulation resistance information of new energy vehicles under different operating conditions, so as to distinguish the insulation resistance information according to the operating conditions; for example, the insulation resistance information during a single charging process is organized together, and the insulation resistance information during a single driving process is organized together, thereby obtaining the insulation resistance information under different operating conditions; then, the average value of the insulation resistance information under each operating condition is calculated and analyzed separately, which can eliminate other influences on the insulation resistance of the power battery and improve the accuracy of risk analysis.

[0099] In the embodiments of this application, the specific value of the preset duration is not limited. For example, the preset duration can be 1 hour, so that the insulation resistance information under the same working condition can be divided into hours to obtain the insulation resistance set corresponding to each hour. The insulation resistance set can include the insulation resistance value corresponding to each time point.

[0100] In the embodiments of this application, the average value of the insulation resistance value in each insulation resistance value set is calculated to obtain the average value of each insulation resistance value set. This can eliminate the error caused by the normal fluctuation of insulation resistance value and improve the accuracy of risk analysis.

[0101] In some embodiments of this application, when the safety warning device determines the rate of change information and trend of change information based on multiple average values, it can perform quartile analysis processing on the multiple average values ​​to obtain the trend of change information; it can also calculate the difference between every two adjacent average values ​​to obtain the difference result; and then calculate the rate of change based on the difference result, and determine the calculated rate of change as the rate of change information.

[0102] In the embodiments of this application, a quartile, also known as a quartile point, refers to a value located at one of the three dividing points when all values ​​are arranged from smallest to largest and divided into four equal parts in statistics.

[0103] For example, the quartiles of the multiple average values ​​determined by quartile analysis are Q1, Q2, and Q3. The changes in Q1, Q2, and Q3 can then be used to determine the trend of insulation resistance. For instance, if Q1, Q2, and Q3 all show a decreasing trend, it indicates that the overall insulation resistance is decreasing; if Q1, Q2, and Q3 remain stable, it indicates that the insulation resistance does not show a significant upward or downward trend; if Q1, Q2, and Q3 fluctuate, it indicates that the data may have periodic changes or be affected by external factors; if at a certain point in time, most of the data is concentrated around Q3, and over time the center of gravity gradually shifts towards Q1, it indicates that the insulation resistance has a decreasing trend.

[0104] In some embodiments of this application, when calculating the rate of change based on the difference results, the first difference between every two differences in the difference results can be obtained, and then the first difference and a preset duration can be divided to obtain the rate of change.

[0105] For example, the safety warning device can calculate the difference between every two adjacent average values ​​out of 10 average values, obtain the difference result, and then calculate the rate of change of the difference result, which can be in Ω / h. This rate of change is the information on the rate of change of insulation resistance.

[0106] For example, when determining the rate of change information based on the above method, the safety warning device can first divide the insulation resistance information under the same working condition into three sets of insulation resistance values, A, B, and C, according to the time interval of one hour. Then, it can calculate the average value of each insulation resistance value in each of the three sets of insulation resistance values, and obtain the average value of set A as 101Ω, the average value of set B as 102Ω, and the average value of set C as 105Ω. Then, it can calculate the difference based on each average value, and the difference results include: the difference a1 between the average value of set A and the average value of set B is 1Ω, and the difference a2 between the average value of set B and the average value of set C is 3Ω. Thus, it can be determined that the first difference between the difference a2 and the difference a1 is 2Ω, and the rate of change is 2Ω / h.

[0107] Step 103: Perform risk analysis based on the first threshold, rate of change information, and trend of change information to obtain the risk analysis results of new energy vehicles; wherein, the risk analysis results are used to determine whether new energy vehicles have risks and the types of risks that exist.

[0108] In the embodiments of this application, after determining a first threshold based on status information and determining the rate of change and trend information of insulation resistance based on insulation resistance information, the safety warning device can perform risk analysis processing based on the first threshold, the rate of change information, and the trend information to obtain the risk analysis result of the new energy vehicle; wherein, the risk analysis result is used to determine whether the new energy vehicle has any risk and the type of risk.

[0109] In some embodiments of this application, the risk analysis results may include a first risk analysis result, which is used to determine whether the new energy vehicle has a risk of chassis collision; wherein, the risk of chassis collision can be understood as the risk of chassis collision or water ingress.

[0110] In some embodiments of this application, when the safety warning device performs risk analysis processing based on a first threshold, change rate information, and change trend information to obtain the risk analysis result of the new energy vehicle, it can determine that the first risk analysis result indicates that the new energy vehicle has a chassis collision risk if the change trend information is gradually decreasing and the change rate information is greater than the first threshold; otherwise, it determines that the first risk analysis result indicates that the new energy vehicle does not have a chassis collision risk.

[0111] In some embodiments of this application, the risk analysis results may also include a second risk analysis result, which is used to determine whether the new energy vehicle is at risk of thermal runaway.

[0112] In some embodiments of this application, the safety warning device may also perform a risk analysis of thermal runaway based on battery temperature data in the operating data, and obtain a second risk analysis result, if the first risk analysis result indicates that the new energy vehicle has a risk of chassis collision.

[0113] In other words, in the embodiments of this application, after analyzing and marking new energy vehicles with chassis collision risks, the safety warning device can list these new energy vehicles as key monitoring targets, so as to further conduct intensive temperature monitoring of the batteries of these new energy vehicles and determine whether these new energy vehicles have thermal runaway risks.

[0114] In some embodiments of this application, when the safety warning device performs a risk analysis of thermal runaway based on battery temperature data in the operating data to obtain a second risk analysis result, it may include at least one of the following methods: comparing the highest battery cell temperature in the battery temperature data with a second threshold; if the comparison result shows that the highest battery cell temperature is greater than the second threshold, determining that the second risk analysis result indicates a risk of thermal runaway in the new energy vehicle; determining the temperature difference information in the battery temperature data, comparing the temperature difference information with a third threshold; if the comparison result shows that the temperature difference information is greater than the third threshold, determining that the second risk analysis result indicates a risk of thermal runaway in the new energy vehicle; determining the temperature rise rate information in the battery temperature data, comparing the temperature rise rate information with a fourth threshold; if the comparison result shows that the temperature rise rate information is greater than the fourth threshold, determining that the second risk analysis result indicates a risk of thermal runaway in the new energy vehicle; wherein, the temperature rise rate information represents the rate at which the battery temperature rises.

[0115] In the embodiments of this application, the specific values ​​of the second threshold, the third threshold and the fourth threshold are not limited in this application, and can be set accordingly according to different new energy vehicles or battery types; for example, the second threshold can be 55°C, the third threshold can be 15°C and the fourth threshold can be 2°C / min.

[0116] For example, if the battery temperature is too high, i.e., the highest battery cell temperature is greater than 55°C, a temperature anomaly can be determined; a temperature anomaly can also be determined when the temperature difference is too large, such as a temperature difference greater than 15°C; a temperature anomaly can also be determined when the temperature rise rate is too fast, such as a temperature rise rate greater than 2°C / min; thus, when a temperature anomaly is determined, it is determined that the new energy vehicle has a risk of thermal runaway, and the new energy vehicle is marked as a new energy vehicle with thermal runaway risk.

[0117] In some embodiments of this application, when determining the temperature difference information of battery temperature data, the safety warning device can obtain the highest and lowest battery cell temperatures in the battery temperature data; then determine the difference between the highest and lowest battery cell temperatures, and define the difference as temperature difference information.

[0118] In some embodiments of this application, when determining the temperature rise rate information of battery temperature data, the safety warning device can calculate the temperature rise rate information based on the individual cell temperature and time information at various time points.

[0119] Step 104: If the risk analysis results indicate that new energy vehicles pose a risk, generate risk warning information for new energy vehicles based on the risk analysis results.

[0120] In the embodiments of this application, the safety warning device can perform risk analysis processing based on a first threshold, rate of change information, and trend of change information to obtain the risk analysis result of the new energy vehicle. If the risk analysis result indicates that the new energy vehicle is at risk, the device can generate risk warning information for the new energy vehicle based on the risk analysis result.

[0121] In the embodiments of this application, the risk analysis results may include a first risk analysis result and a second risk analysis result. Accordingly, if it is determined that the new energy vehicle has a risk of chassis collision or thermal runaway, corresponding risk warning information can be generated to indicate the existence of the corresponding type of risk.

[0122] In the embodiments of this application, the safety warning device can also continue to receive the operating data sent by the new energy vehicle if the risk analysis result indicates that there is no risk to the new energy vehicle, so as to continue to analyze whether there are various risks to the new energy vehicle.

[0123] In the embodiments of this application, when the safety warning device generates risk warning information or insulation fault alarm information for a new energy vehicle, it can send the risk warning information or insulation fault alarm information to a first device or a new energy vehicle; wherein, the first device can be used to generate prompt information based on the risk warning information or insulation fault alarm information, and send the risk prompt information to the new energy vehicle.

[0124] For example, the first device can be the device corresponding to the maintenance center, which can be used to receive various alarm information and warning information sent by the safety warning device, and then generate corresponding prompt information, such as "Your new energy vehicle has XX risk", and send the prompt information to the new energy vehicle or the mobile device terminal of the new energy vehicle user.

[0125] In summary, this application utilizes cloud technology to integrate and analyze battery data from multiple electric vehicles, including key parameters such as insulation resistance and temperature. Through big data analysis, it can identify trends and patterns in battery performance, which is difficult to achieve with traditional methods. Furthermore, it enables real-time monitoring of the status of new energy vehicles and batteries, and can analyze and predict potential future risks. Additionally, it supports in-depth analysis of long-term historical data from new energy vehicles to identify potential fault risks and provide early warnings. Moreover, for new energy vehicles identified as having high-risk chassis impact-related risks, more intensive temperature monitoring can be implemented. Once abnormal temperature behavior is detected, a thermal runaway warning is triggered. This phased monitoring and early warning mechanism makes the response more timely and effective. It forms an advanced, proactive prevention and monitoring early warning system for electric vehicles and batteries, reducing the occurrence of thermal runaway events and significantly improving the safety and reliability of electric vehicles.

[0126] This application provides a safety early warning method for new energy vehicles. The safety early warning device receives operational data from the new energy vehicle. The operational data includes at least battery insulation resistance information and the vehicle's status information. A first threshold is determined based on the vehicle's status information, and the rate of change and trend of change of the insulation resistance are determined based on the insulation resistance information. Risk analysis is performed based on the first threshold, the rate of change, and the trend to obtain a risk analysis result for the new energy vehicle. This risk analysis result is used to determine whether the new energy vehicle faces a risk and the type of risk. If the risk analysis result indicates that the new energy vehicle faces a risk, a risk early warning message is generated based on the risk analysis result. Therefore, the safety early warning device can receive operational data from the new energy vehicle in real time, and then determine a matching first threshold based on the vehicle's status information in the operational data, as well as the rate of change and trend of change of the insulation resistance in the operational data. By using the first threshold and the rate and trend of change of the insulation resistance, the device can analyze whether the new energy vehicle currently faces a risk and the type of risk present. This allows for effective real-time detection of risks present in the new energy vehicle, and when a risk is determined, risk early warning information can be generated based on the risk analysis result, providing timely warnings of potential risks.

[0127] Based on the above embodiments, in another embodiment of this application, for example, the safety warning device is a cloud server, which is equipped with a cloud data center that can receive a large amount of operating data sent by new energy vehicles, and analyze the operating data to determine whether there are risks in the new energy vehicles and issue timely warnings.

[0128] For example, such as Figure 2As shown, the data acquisition module in a new energy vehicle can collect operational data and then send it to the cloud data center via the data transmission module or the vehicle networking system (Telematics Box, TBOX) gateway. The cloud data center processes and analyzes the operational data using its internal data processing and analysis unit. After generating risk warning information based on the risk analysis results, it can send the risk warning information to the internal warning system or work order system. The warning system or work order system can then send the risk warning information to the user service center, enabling the user service center to generate a prompt message based on the risk warning information and send it to the new energy vehicle user terminal to remind the user.

[0129] For example, new energy vehicles can collect data such as insulation resistance, temperature, voltage, and current of the power battery through onboard sensors and send it to a data acquisition module. The data acquisition module continuously collects the aforementioned operating parameters of the power battery and other data from the new energy vehicle, and then uploads the collected data to a cloud data center. The cloud data center can receive operating data from multiple electric vehicles. This operating data can include reporting time, VIN code, charging status information, charging information, insulation resistance, individual battery temperature, highest individual battery temperature, lowest individual battery temperature, total voltage, high-voltage insulation fault flag, high-voltage insulation detection circuit fault flag, power battery relay status, and component relay status. The cloud data center can clean the received data and complete any missing data, and then store the processed data in its database. New energy vehicles can upload data to the cloud data center at a frequency of ≤30 seconds.

[0130] In some embodiments, the cloud data center can receive data with a length of more than one week for risk analysis, such as risk analysis of data from one week, one month, or even half a year, so as to use the data during this period to assess the performance and risk trends of new energy vehicles.

[0131] For example, the charging status information can include three states: charging, driving, and stationary. In other words, the status of the vehicle can include charging status, high voltage connected status, and high voltage disconnected status. The charging status indicates that the vehicle is in the state of plugging in the charging gun while parked. The high voltage connected status indicates that the high voltage is connected when the vehicle is not parked for charging. The high voltage disconnected status indicates that the high voltage is not connected to the vehicle. The cloud data center can distinguish the status of new energy vehicles based on the charging status information.

[0132] In some embodiments, the cloud data center can also determine whether components other than the battery in a new energy vehicle are in an on state based on the status of component relays. For example, the components could be air conditioners and compressors.

[0133] In some embodiments, the cloud data center can remove data from the operational data where the high-voltage insulation fault flag indicates the presence of an insulation fault, or the high-voltage insulation detection circuit fault flag indicates the presence of a fault in the detection circuit. For example, if the cloud data center receives operational data of a new energy vehicle at time t2, and the high-voltage insulation fault flag indicates the presence of an insulation fault, then the operational data of the new energy vehicle at time t2 can be removed. This indicates that it can be determined that the new energy vehicle has an insulation fault at time t2, and risk analysis processing is no longer required for the operational data at time t2. However, the cloud data center can still continue to receive subsequent operational data of the new energy vehicle to determine in real time whether there is a risk in the new energy vehicle during its subsequent operation.

[0134] In some embodiments, since the insulation resistance of the vehicle is lower in the charging state due to the influence of the charging pile, it can be analyzed separately for the charging and non-charging states. For example, a cloud data center can differentiate data according to charging status information, including charging, driving, and stationary states, and process and analyze the data separately. Furthermore, the insulation resistance of new energy vehicles is also affected by the status of other components during use. If conditions permit, the cloud data center can also receive the status of component relays, such as the status of air conditioning relays and compressor relays, and further analyze the insulation resistance based on the status of these relays, thereby improving the accuracy of risk analysis.

[0135] For example, such as Figure 3 As shown, the cloud data center can first clean the received data (step 201), and then determine whether there is an insulation fault (step 202). This can be done by the BMS in the new energy vehicle to determine if an insulation fault exists. If so, it is marked as an insulation fault alarm vehicle (step 203). If not, a first threshold can be determined based on charging status information and / or component relay status (step 204). Then, the data is segmented according to operating conditions to obtain data segments for each operating condition (step 205). The data segments under each operating condition are then processed... The insulation resistance value is analyzed for its rate of change and trend (step 206). It is determined whether the trend is decreasing and the rate of change is greater than the first threshold (step 207). If so, the vehicle is marked as having a risk of chassis collision or water ingress (step 208). If not, it is marked as a risk-free vehicle (step 209). After step 208, the temperature of the vehicle can be monitored, and it is determined whether the temperature is greater than the second threshold, the temperature difference is greater than the third threshold, or the temperature rise is greater than the fourth threshold (step 210). If so, the vehicle is marked as having a risk of thermal runaway (step 211).

[0136] For example, such as Figure 4As shown, after receiving data sent by a new energy vehicle, the cloud data center can determine whether the data is from a new energy vehicle in a charging state (step 301). If so, it can be marked as a charging data segment (step 302); if not, it can be marked as a discharging data segment (step 303). Simultaneously, it can also determine whether the component relay is in an open state (step 304). If not, it is marked as a component not open data segment (step 305); if so, it is marked as a component open data segment (step 306). Furthermore, it can analyze the changing trend and rate of change of the insulation resistance value in the data segment (step 307). Specifically, when analyzing the rate of change for different types of data segments, for the charging segment data, it can determine... For the charging segment, we can determine whether the rate of change of insulation resistance in the data exceeds the fifth threshold (e.g., the fifth threshold is 10Ω / h). For the discharging segment, we can determine whether the rate of change of insulation resistance in the data exceeds the sixth threshold (e.g., the sixth threshold is 20Ω / h). For the data segment where components are not opened, we can determine whether the rate of change of insulation resistance in the data segment where components are opened exceeds the eighth threshold (e.g., the eighth threshold is 15Ω / h). For the data segment where components are opened, we can determine whether the rate of change of insulation resistance in the data segment where components are opened exceeds the seventh threshold (e.g., the seventh threshold is 13Ω / h). Therefore, if the rate of change exceeds the corresponding threshold and the trend is gradually decreasing, the new energy vehicle corresponding to that data segment can be marked as a vehicle with a risk of chassis collision or water ingress.

[0137] For example, such as Figure 5 As shown, after the cloud data center performs risk analysis, it can also generate information on different handling methods for vehicles marked with different risk analysis results to instruct them to take appropriate actions. For example, for vehicles marked with insulation fault alarms, it can instruct them to be handled in accordance with the national standard alarm handling method; for vehicles marked with no risk, there is no handling opinion; for vehicles marked with chassis collision or water ingress risk, it can instruct them to be recalled in time and have their chassis inspected; for vehicles marked with thermal runaway risk, it can instruct them to be recalled immediately and have their battery pack inspected.

[0138] In some embodiments, the cloud data center can output corresponding risk warning information according to the tags to notify vehicle users and relevant maintenance personnel to take appropriate safety measures, which not only improves the safety of new energy vehicles, but also helps to optimize the maintenance and upkeep process.

[0139] In summary, this application, through real-time monitoring and historical data analysis of key parameters such as battery insulation resistance and temperature, can provide timely warnings of potential thermal runaway risks, thereby reducing the occurrence of safety accidents. Predictive monitoring helps to promptly identify and correct problems in battery use, avoiding damage to the battery under extreme operating conditions, thus extending battery life. Personalized battery performance evaluation and health status monitoring allow for more effective scheduling of maintenance work, avoiding unnecessary repairs or replacements and saving operating costs. Timely notifications and warnings enhance the intelligence of vehicle use. By providing accurate risk warning information, potential damage and loss to the vehicle can be reduced. Utilizing big data analytics, real-time monitoring and warnings of new energy vehicles and batteries can be achieved, thereby improving the performance and safety of new energy vehicles on multiple levels.

[0140] This application provides a safety early warning method for new energy vehicles. The safety early warning device receives operational data from the new energy vehicle. The operational data includes at least battery insulation resistance information and the vehicle's status information. A first threshold is determined based on the status information, and the rate of change and trend of the insulation resistance are determined based on the insulation resistance information. Risk analysis is performed based on the first threshold, the rate of change, and the trend to obtain a risk analysis result for the new energy vehicle. The risk analysis result is used to determine whether the new energy vehicle has a risk and the type of risk. If the risk analysis result indicates that the new energy vehicle has a risk, a risk early warning message is generated based on the risk analysis result. Therefore, the safety early warning device can receive operational data from the new energy vehicle in real time, and then determine a matching first threshold based on the vehicle's status information in the operational data, as well as the rate of change and trend of the insulation resistance in the operational data. By using the first threshold and the rate and trend of the insulation resistance, the device can analyze whether the new energy vehicle currently has a risk and the type of risk present. This allows for effective real-time detection of risks present in new energy vehicles, and when a risk is determined, risk early warning information can be generated based on the risk analysis result, providing timely warnings of potential risks.

[0141] Based on the above embodiments, in another embodiment of this application, a safety warning device is provided, such as... Figure 6 As shown, the safety warning device 1 may include a receiving unit 11, a determining unit 12, an analyzing unit 13, and a generating unit 14.

[0142] The receiving unit 11 is used to receive the operating data of the new energy vehicle; wherein the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle.

[0143] The determining unit 12 is used to determine the first threshold based on the status information, and to determine the rate of change information and trend information of the insulation resistance based on the insulation resistance information.

[0144] Analysis unit 13 is used to perform risk analysis processing based on the first threshold, rate of change information and trend information to obtain risk analysis results for new energy vehicles; wherein, the risk analysis results are used to determine whether new energy vehicles have risks and the types of risks that exist.

[0145] The generation unit 14 is used to generate risk warning information for new energy vehicles based on the risk analysis results when the risk analysis results indicate that there are risks associated with new energy vehicles.

[0146] In some embodiments of this application, the status information includes charging status information and component status information; the determining unit 12 can also be used to determine a first threshold based on the charging status information and / or component status information; wherein, the charging status information is used to determine whether the new energy vehicle is in a charging state; the component status information is used to determine whether the components in the new energy vehicle other than the battery are in an on state.

[0147] In some embodiments of this application, the determining unit 12 can also be used to divide the insulation resistance information of new energy vehicles under the same working condition according to a preset time period to obtain multiple insulation resistance sets; and to determine the average value corresponding to each of the multiple insulation resistance sets to obtain multiple average values; and to determine the rate of change information and trend of change information based on the multiple average values.

[0148] In some embodiments of this application, the determining unit 12 can also be used to perform quartile analysis processing based on multiple average values ​​to obtain trend information; and to calculate the difference between every two adjacent average values ​​among the multiple average values ​​to obtain the difference result; to calculate the rate of change based on the difference result, and to determine the calculated rate of change as the rate of change information.

[0149] In some embodiments of this application, the risk analysis result includes a first risk analysis result; the first risk analysis result is used to determine whether the new energy vehicle has a chassis collision risk; the analysis unit 13 can also be used to determine that the first risk analysis result indicates that the new energy vehicle has a chassis collision risk when the trend information is gradually decreasing and the rate of change is greater than a first threshold; otherwise, it is determined that the first risk analysis result indicates that the new energy vehicle does not have a chassis collision risk.

[0150] In some embodiments of this application, the risk analysis results also include a second risk analysis result, which is used to determine whether the new energy vehicle has a risk of thermal runaway. The analysis unit 13 can also be used to perform thermal runaway risk analysis processing based on the battery temperature data in the operating data when the first risk analysis result indicates that the new energy vehicle has a risk of chassis collision, in order to obtain the second risk analysis result.

[0151] In some embodiments of this application, the analysis unit 13 can also be used to compare the highest battery cell temperature in the battery temperature data with a second threshold. If the comparison result shows that the highest battery cell temperature is greater than the second threshold, the second risk analysis result is determined to be a risk of thermal runaway in the new energy vehicle. It can also determine the temperature difference information in the battery temperature data, compare the temperature difference information with a third threshold, and if the comparison result shows that the temperature difference information is greater than the third threshold, the second risk analysis result is determined to be a risk of thermal runaway in the new energy vehicle. Furthermore, it can determine the temperature rise rate information in the battery temperature data, compare the temperature rise rate information with a fourth threshold, and if the comparison result shows that the temperature rise rate information is greater than the fourth threshold, the second risk analysis result is determined to be a risk of thermal runaway in the new energy vehicle. The temperature rise rate information represents the rate at which the battery temperature increases.

[0152] In some embodiments of this application, the analysis unit 13 can also be used to obtain the highest and lowest battery cell temperatures in the battery temperature data; and to determine the difference between the highest and lowest battery cell temperatures, and to determine the difference as temperature difference information.

[0153] In some embodiments of this application, the generation unit 14 can also be used to generate insulation fault alarm information when it is determined that there is an insulation fault in the new energy vehicle based on the insulation fault identification information in the operating data; wherein, the insulation fault identification information is the identification information generated by the battery management system in the new energy vehicle after performing insulation detection on the battery.

[0154] In the embodiments of this application, such as Figure 7 As shown, the safety warning device may further include a processor 15 and a memory 16 storing instructions executable by the processor 15; furthermore, the safety warning device may further include a communication interface 17 and a bus 18 for connecting the processor 15, the memory 16 and the communication interface 17.

[0155] In the embodiments of this application, the processor 15 can be at least one of the following: Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), FPGA, Central Processing Unit (CPU), controller, microcontroller, and microprocessor. It is understood that for different devices, the electronic device used to implement the above-mentioned processor function can also be other types, and this application embodiment does not specifically limit the specific types. The safety warning device 1 may also include a memory 16, which can be connected to the processor 15. The memory 16 is used to store executable program code, which includes computer operation instructions. The memory 16 may include high-speed RAM memory and may also include non-volatile memory.

[0156] In embodiments of this application, bus 18 is used to connect communication interface 17, processor 15, and memory 16, as well as the mutual communication between these devices.

[0157] In embodiments of this application, memory 16 is used to store instructions and data.

[0158] Furthermore, in an embodiment of this application, the processor 15 is configured to receive operating data of the new energy vehicle; wherein the operating data includes at least battery insulation resistance information and new energy vehicle status information; a first threshold is determined based on the status information, and the rate of change and trend information of the insulation resistance are determined based on the insulation resistance information; risk analysis processing is performed based on the first threshold, the rate of change information, and the trend information to obtain a risk analysis result for the new energy vehicle; wherein the risk analysis result is used to determine whether the new energy vehicle has a risk and the type of risk; if the risk analysis result indicates that the new energy vehicle has a risk, a risk warning information for the new energy vehicle is generated based on the risk analysis result.

[0159] In practical applications, the aforementioned memory 16 can be volatile memory, such as random-access memory (RAM); or non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); or a combination of the above types of memory, and provide instructions and data to the processor 15.

[0160] Furthermore, in this embodiment, the functional modules can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module.

[0161] If the integrated unit is implemented as a software functional module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the method of this embodiment. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0162] This application provides a safety early warning method for new energy vehicles. The safety early warning device receives operational data from the new energy vehicle. The operational data includes at least battery insulation resistance information and the vehicle's status information. A first threshold is determined based on the status information, and the rate of change and trend of the insulation resistance are determined based on the insulation resistance information. Risk analysis is performed based on the first threshold, the rate of change, and the trend to obtain a risk analysis result for the new energy vehicle. The risk analysis result is used to determine whether the new energy vehicle has a risk and the type of risk. If the risk analysis result indicates that the new energy vehicle has a risk, a risk early warning message is generated based on the risk analysis result. Therefore, the safety early warning device can receive operational data from the new energy vehicle in real time, and then determine a matching first threshold based on the vehicle's status information in the operational data, and determine the rate of change and trend of the insulation resistance based on the insulation resistance information in the operational data. By using the first threshold and the rate and trend of the insulation resistance change, the device can analyze whether the new energy vehicle currently has a risk and the type of risk. This allows for effective real-time detection of risks in new energy vehicles, and when a risk is determined, risk early warning information can be generated based on the risk analysis result, providing timely warnings of potential risks.

[0163] Specifically, the program instructions corresponding to a software performance bottleneck handling method in this embodiment can be stored on storage media such as optical discs, hard disks, and USB flash drives. When the program instructions corresponding to a software performance bottleneck handling method in the storage media are read or executed by a security warning device, the following steps are included:

[0164] Receive operational data from new energy vehicles; the operational data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle.

[0165] The first threshold is determined based on the status information, and the rate of change and trend of change of the insulation resistance are determined based on the insulation resistance information.

[0166] Risk analysis is performed based on the first threshold, rate of change information, and trend of change information to obtain the risk analysis results for new energy vehicles; the risk analysis results are used to determine whether new energy vehicles have risks and the types of risks that exist.

[0167] If the risk analysis results indicate that new energy vehicles pose a risk, risk warning information for new energy vehicles will be generated based on the risk analysis results.

[0168] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0169] This application is described with reference to schematic and / or block diagrams of implementations of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block of the schematic and / or block diagrams can be implemented by computer program instructions, and combinations of blocks in the schematic and / or block diagrams can be implemented. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the schematic and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0170] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in the implementation flow diagram. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0171] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0172] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

Claims

1. A safety early warning method for new energy vehicles, characterized in that, The method includes: Receive operating data from new energy vehicles; wherein the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle; A first threshold is determined based on the state information, and the rate of change and trend of change of the insulation resistance are determined based on the insulation resistance information. Risk analysis is performed based on the first threshold, the rate of change information, and the trend of change information to obtain the risk analysis results of the new energy vehicle; wherein, the risk analysis results are used to determine whether the new energy vehicle has any risks and the types of risks that exist. If the risk analysis results indicate that the new energy vehicle poses a risk, a risk warning message for the new energy vehicle is generated based on the risk analysis results.

2. The safety early warning method for new energy vehicles according to claim 1, characterized in that, The status information includes charging status information and component status information; determining the first threshold based on the status information includes: The first threshold is determined based on the charging status information and / or the component status information; wherein the charging status information is used to determine whether the new energy vehicle is in a charging state; and the component status information is used to determine whether the components in the new energy vehicle other than the battery are in an on state.

3. The safety early warning method for new energy vehicles according to claim 2, characterized in that, The step of determining the rate of change information and trend information of the insulation resistance value based on the insulation resistance value information includes: The insulation resistance value information of the new energy vehicle under the same working condition is divided and processed according to a preset time period to obtain multiple insulation resistance value sets. The average value corresponding to each of the multiple sets of insulation resistance values ​​is determined to obtain multiple average values; The rate of change information and the trend of change information are determined based on the multiple average values.

4. The safety early warning method for new energy vehicles according to claim 3, characterized in that, The process of determining the rate of change information and the trend of change information based on the multiple average values ​​includes: The trend information is obtained by performing quartile analysis on the multiple average values. The difference between any two adjacent average values ​​among the plurality of average values ​​is calculated to obtain the difference result; The rate of change is calculated based on the difference result, and the calculated rate of change is determined as the rate of change information.

5. The safety early warning method for new energy vehicles according to claim 4, characterized in that, The risk analysis results include a first risk analysis result; the first risk analysis result is used to determine whether the new energy vehicle has a risk of chassis collision; the risk analysis processing based on the first threshold, the rate of change information, and the trend of change information to obtain the risk analysis results of the new energy vehicle includes: If the trend information shows a gradual decrease and the rate of change is greater than the first threshold, the first risk analysis result is determined to indicate that the new energy vehicle has a risk of chassis collision; otherwise, the first risk analysis result is determined to indicate that the new energy vehicle does not have a risk of chassis collision.

6. The safety early warning method for new energy vehicles according to any one of claims 1 to 5, characterized in that, The risk analysis results also include a second risk analysis result, which is used to determine whether the new energy vehicle has a risk of thermal runaway; the method further includes: If the first risk analysis result indicates that the new energy vehicle has a risk of chassis collision, then the risk analysis of thermal runaway is performed based on the battery temperature data in the operating data to obtain the second risk analysis result.

7. The safety early warning method for new energy vehicles according to claim 6, characterized in that, The risk analysis of thermal runaway based on the battery temperature data in the operational data, to obtain the second risk analysis result, includes at least one of the following: The highest battery cell temperature in the battery temperature data is compared with a second threshold. If the highest battery cell temperature is greater than the second threshold, the second risk analysis result is determined to be that the new energy vehicle has a risk of thermal runaway. The temperature difference information of the battery temperature data is determined, and the temperature difference information is compared with a third threshold. If the comparison result shows that the temperature difference information is greater than the third threshold, the second risk analysis result is determined to be that the new energy vehicle has a risk of thermal runaway. The temperature rise rate information of the battery temperature data is determined, and the temperature rise rate information is compared with a fourth threshold. If the comparison result shows that the temperature rise rate information is greater than the fourth threshold, the second risk analysis result is determined to be that the new energy vehicle has a risk of thermal runaway. The temperature rise rate information represents the rate at which the battery temperature rises.

8. The safety early warning method for new energy vehicles according to claim 7, characterized in that, The temperature difference information for determining the battery temperature data includes: Obtain the highest and lowest battery cell temperatures from the battery temperature data; The difference between the highest and lowest battery cell temperatures is determined, and this difference is defined as the temperature difference information.

9. The safety early warning method for new energy vehicles according to claim 1, characterized in that, The method further includes: If an insulation fault is determined to exist in the new energy vehicle based on the insulation fault identification information in the operating data, an insulation fault alarm information is generated; wherein, the insulation fault identification information is the identification information generated by the battery management system in the new energy vehicle after performing insulation detection on the battery.

10. A safety early warning device, characterized in that, The safety early warning device includes a receiving unit, a determining unit, an analyzing unit, and a generating unit; The receiving unit is used to receive operating data of the new energy vehicle; wherein the operating data includes at least the insulation resistance information of the battery and the status information of the new energy vehicle. The determining unit is used to determine a first threshold based on the state information, and to determine the rate of change and trend information of the insulation resistance based on the insulation resistance information; The analysis unit is used to perform risk analysis processing based on the first threshold, the rate of change information, and the trend of change information to obtain the risk analysis result of the new energy vehicle; wherein, the risk analysis result is used to determine whether the new energy vehicle has any risk and the type of risk. The generation unit is used to generate risk warning information for the new energy vehicle based on the risk analysis result when the risk analysis result indicates that the new energy vehicle poses a risk.

11. A safety early warning device, characterized in that, The safety warning device includes a processor and a memory storing processor-executable instructions; when the instructions are executed by the processor, the method described in any one of claims 1 to 9 is implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 9.

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