A method, device and medium for detecting abnormal conduction of a new energy device

Abstract

The application discloses a new energy equipment electric conduction anomaly detection method and device and medium, and relates to the technical field of new energy. The method comprises the following steps: comparing actual maximum temperature data with a first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, comparing actual starting temperature with a preset starting temperature threshold; if the actual starting temperature is lower than the preset starting temperature threshold, determining that the actual maximum temperature data of the new energy equipment to be detected is abnormal, and taking the actual maximum temperature data as the basis for evaluating the electric conduction anomaly of the new energy equipment to be detected. Since the maximum temperature safety threshold is obtained according to reference electric conduction process data, and the reference electric conduction process data is real data, compared with a fixed threshold, the method can improve the accuracy of electric conduction anomaly detection. In addition, the starting temperature is considered, which can exclude the misjudgment of the maximum temperature anomaly of the new energy equipment with a high starting electric conduction temperature, so that the electric conduction anomaly of the new energy equipment is more accurately identified.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a method, apparatus and medium for detecting electrical abnormalities in new energy equipment. Background Technology

[0002] The new energy devices mentioned in this application are devices that provide power through batteries, such as cars that use batteries, hereinafter referred to as electric vehicles. With the rapid development of new energy devices, battery safety has become a major concern.

[0003] To prevent electrical accidents caused by factors such as overheating during battery conduction, manufacturers typically conduct battery tests to determine the safe thresholds for various variables related to safe battery conduction. These thresholds are then entered into the Battery Management System (BMS). During conduction, the relationship between the current battery parameters and the set safe thresholds is compared to determine if there are any abnormalities in battery conduction.

[0004] Obviously, the safety threshold obtained from test experiments is usually fixed, and the corresponding threshold changes constantly as battery performance changes. If a fixed safety threshold is used as the standard for judging anomalies, the judgment result will inevitably be inaccurate.

[0005] Therefore, it is evident that accurately identifying conductivity anomalies in new energy equipment during the electrical conduction process is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] The purpose of this application is to provide a method, apparatus, and medium for detecting conductivity anomalies in new energy equipment, which can be used to more accurately identify conductivity anomalies in new energy equipment during the conduction process.

[0007] To address the aforementioned technical problems, this application provides a method for detecting abnormal conductivity in new energy equipment, comprising:

[0008] Confirm the type of new energy equipment to be tested;

[0009] Select multiple new energy devices under the aforementioned type as the analysis objects;

[0010] Obtain first highest temperature data of a reference conduction process matching the object being analyzed; wherein the first highest temperature data comes from data generated by the object being analyzed during the conduction process;

[0011] Obtain the actual highest temperature data of the current conductive process of the new energy device under test;

[0012] Based on the correspondence between the first highest temperature data and time, an anomaly detection method is used to determine the first safety threshold corresponding to the first highest temperature data.

[0013] Compare the actual highest temperature data with the first safety threshold;

[0014] If the actual highest temperature data is higher than the first safety threshold, then the actual start temperature of the current conduction process is obtained;

[0015] Compare the actual start temperature with the preset start temperature threshold.

[0016] If the actual starting temperature is lower than the preset starting temperature threshold, the actual maximum temperature data of the new energy device under test is determined to be abnormal, which serves as the basis for evaluating the conductivity abnormality of the new energy device under test.

[0017] Preferably, when the actual starting temperature is higher than the preset starting temperature threshold, the method further includes:

[0018] Obtain a second highest temperature data for the reference conduction process that matches the object being analyzed; wherein the second highest temperature data comes from data generated by the object being analyzed during the conduction process;

[0019] Based on the correspondence between the second highest temperature data and time, the second safety threshold corresponding to the second highest temperature data is determined using the anomaly detection method.

[0020] Compare the actual maximum temperature data with the second safety threshold;

[0021] If the actual maximum temperature data is higher than the second safety threshold, then the actual maximum temperature data of the new energy device under test is determined to be abnormal, which serves as the basis for evaluating the conductivity abnormality of the new energy device under test.

[0022] Preferably, obtaining the first highest temperature data of a reference conductivity process matching the object of analysis includes:

[0023] Obtain multiple first target conductive orders that match the analysis object within a first preset time period and a preset area;

[0024] Extract the first highest temperature data of the reference conductive process from each of the first target conductive orders.

[0025] Preferably, obtaining the second highest temperature data of the reference conductivity process matching the object being analyzed includes:

[0026] Obtain multiple second target conductive orders that match the analysis object within the first preset time period, within the preset region, and under a preset conductive time period and / or preset conductive ratio;

[0027] Extract the second highest temperature data of the reference conductive process from each of the second target conductive orders.

[0028] Preferably, obtaining the preset start temperature threshold includes:

[0029] Obtain the temperature data of the start of heat dissipation transmitted by the BMS of each of the analyzed objects;

[0030] The preset start temperature threshold is determined based on the temperature data at which heat dissipation begins.

[0031] Preferably, obtaining the preset start temperature threshold includes:

[0032] Obtain multiple historical conductive orders that match the new energy equipment to be tested within the first preset time period;

[0033] Extract the corresponding first start conductivity temperature data from each of the aforementioned historical conductive orders;

[0034] The preset start temperature threshold is determined based on the first start conduction temperature data.

[0035] Preferably, obtaining the preset start temperature threshold includes:

[0036] Obtain multiple third-target conductive orders that match each of the analyzed objects within the first preset time period;

[0037] Extract the corresponding second starting conductivity temperature data from each of the third target conductive orders;

[0038] The preset start temperature threshold is determined based on the second start conduction temperature data.

[0039] Preferably, when the actual maximum temperature data is higher than the first safety threshold, the method further includes:

[0040] Starting from the moment it is determined that the actual highest temperature data is higher than the first safety threshold, the temperature data of the new energy equipment to be tested at each moment within the second preset time period is obtained.

[0041] Based on the temperature data, obtain the temperature change trend of the new energy device to be tested within the second preset time period;

[0042] If the temperature does not decrease or does not decrease to the preset value within the second preset time period, the actual maximum temperature data of the new energy device under test is determined to be abnormal, and is used as the basis for evaluating the conductivity abnormality of the new energy device under test.

[0043] Preferably, after determining that the actual maximum temperature data of the new energy device under test is abnormal if the actual maximum temperature data is higher than the second safety threshold, the method further includes:

[0044] Stop conducting electricity to the new energy device under test and start the heat dissipation system of the new energy device under test;

[0045] The heat dissipation system adjusts the battery temperature of the new energy device to be tested to the preset start temperature threshold.

[0046] Initiate the conduction of the new energy device under test, and return to the step of obtaining the actual highest temperature data of the current conduction process of the new energy device under test.

[0047] Preferably, after determining that the actual maximum temperature data of the new energy equipment to be tested is abnormal, the method further includes:

[0048] Output a prompt message indicating an abnormal conductivity of the new energy device under test.

[0049] To address the aforementioned technical problems, this application also provides a device for detecting abnormal conductivity in new energy equipment, comprising:

[0050] The confirmation module is used to confirm the type of new energy equipment to be tested;

[0051] The selection module is used to select multiple new energy devices under the aforementioned type as analysis objects;

[0052] The first acquisition module is used to acquire the first highest temperature data of a reference conduction process matching the analysis object; wherein the first highest temperature data comes from the data generated by the analysis object during the conduction process;

[0053] The second acquisition module is used to acquire the actual highest temperature data of the current conductive process of the new energy device under test.

[0054] The first determining module is used to determine the first safety threshold corresponding to the first highest temperature data based on the correspondence between the first highest temperature data and time using an anomaly detection method.

[0055] The first comparison module is used to compare the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, the third acquisition module is triggered.

[0056] The third acquisition module is used to acquire the actual start temperature of the current conduction process;

[0057] The second comparison module is used to compare the actual start temperature with a preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, the second determination module is triggered.

[0058] The second determining module is used to determine that the actual maximum temperature data of the new energy device under test is abnormal, so as to serve as the basis for evaluating the conductivity abnormality of the new energy device under test.

[0059] To address the aforementioned technical problems, this application also provides a device for detecting abnormal conductivity in new energy equipment, comprising:

[0060] Memory, used to store computer programs;

[0061] A processor is used to execute the computer program to implement the steps of the above-described method for detecting electrical abnormalities in new energy equipment.

[0062] To address the aforementioned technical problems, this application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned method for detecting electrical conductivity anomalies in new energy devices.

[0063] The method for detecting conductivity anomalies in new energy equipment provided in this application includes: identifying the type of new energy equipment to be tested; selecting multiple new energy equipment of the same type as the analysis object; obtaining the first maximum temperature data of a reference conductivity process matching the analysis object; obtaining the actual maximum temperature data of the current conductivity process of the new energy equipment to be tested; determining a first safety threshold corresponding to the first maximum temperature data based on the correspondence between the first maximum temperature data and time using an anomaly detection method; comparing the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, obtaining the actual start temperature of the current conductivity process; comparing the actual start temperature with a preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, determining that the actual maximum temperature data of the new energy equipment to be tested is abnormal, which serves as the basis for evaluating conductivity anomalies in the new energy equipment to be tested. In this method, the maximum temperature safety threshold is obtained through reference conductivity process data of new energy equipment of the same type as the new energy equipment to be tested. Since the reference conductivity process data is real data, compared to existing fixed thresholds, the obtained safety threshold more accurately reflects the current conductivity state of the new energy equipment to be tested. The safety threshold obtained by this technical solution can improve the accuracy of conductivity anomaly detection. Furthermore, considering that comparing new energy devices with low initial conductivity temperatures with those with high initial conductivity temperatures could easily lead to misjudgments of the highest temperature anomaly in the new energy device with the higher initial conductivity temperature, this method does not directly determine that the new energy device has a conductivity anomaly when the actual highest temperature data is higher than the first safety threshold. Instead, it further judges the relationship between the initial temperature and the preset initial temperature threshold. Only when the actual initial temperature is lower than the preset initial temperature threshold is the actual highest temperature data of the new energy device under test determined to be abnormal, making the identification of conductivity anomalies in new energy devices more accurate.

[0064] In addition, this application also provides a device for detecting electrical conductivity anomalies in new energy equipment and a computer-readable storage medium, which have the same or corresponding technical features as the aforementioned method for detecting electrical conductivity anomalies in new energy equipment, and have the same effect. Attached Figure Description

[0065] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 A flowchart illustrating a method for detecting electrical conductivity anomalies in new energy equipment, provided in an embodiment of this application;

[0067] Figure 2 A structural diagram of a device for detecting conductivity anomalies in new energy equipment provided in an embodiment of this application;

[0068] Figure 3 A structural diagram of a device for detecting electrical conductivity abnormalities in new energy equipment provided in another embodiment of this application;

[0069] Figure 4 The overall flowchart of the new energy equipment conductivity anomaly detection method provided in the embodiments of this application is shown. Detailed Implementation

[0070] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0071] The core of this application is to provide a method, apparatus, and medium for detecting conductivity anomalies in new energy equipment, which can be used to more accurately identify conductivity anomalies in new energy equipment during the conduction process.

[0072] The new energy equipment proposed in this application can be electric vehicles or other electric devices. Taking the charging of new energy equipment as an example, due to the lack of convenience, users have always complained about the long charging time of new energy equipment. The design of new energy equipment charging often tries to shorten the charging time as much as possible, pursuing a high charging rate, and often touting charging speed and maximum power output in advertising to attract consumers. However, in reality, long-term aggressive driving and frequent high-power fast charging basically keep the battery operating at its safety limits, which obviously harms the battery. Currently, analysis of new energy vehicle fire accidents has found that the causes of the accidents can be roughly divided into five categories: charging, water immersion, collision accidents, spontaneous combustion without accidents, and others. Among them, charging accidents are mainly fires that occur during or shortly after charging. With the widespread use of new energy equipment, people are paying more and more attention to the safety of new energy equipment. Therefore, it is necessary to detect abnormalities in the conduction process of new energy equipment. It should be noted that the conduction process here includes the charging process and the discharging process. Taking electric vehicles as an example, driving and charging electric vehicles are two operating conditions of battery discharging and charging.

[0073] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Figure 1 A flowchart of a method for detecting conductivity anomalies in new energy equipment provided in this application embodiment is shown below. Figure 1 As shown, the method includes:

[0074] S10: Confirm the type of new energy equipment to be tested.

[0075] The new energy device to be tested can be any type of new energy device. There is no specific limitation on the specific new energy device to be tested; it will be determined based on the actual situation. During the anomaly detection process of the new energy device to be tested, data from the device's conduction process is referenced to achieve anomaly detection. It should be noted that the reference new energy device here can refer to the new energy device to be tested itself, other new energy devices besides the one to be tested, or both the one to be tested and other new energy devices besides the one to be tested; there is no limitation in this regard. When the selected reference new energy device is the new energy device to be tested itself, the detection of conduction anomalies can be achieved based on the historical conduction process data of the new energy device to be tested. When the selected reference new energy device is another new energy device besides the one to be tested, the detection of conduction anomalies in the new energy device to be tested can be achieved based on the historical conduction process data and / or the current conduction process data of the other new energy devices. To improve the accuracy of detecting conductivity anomalies in the new energy equipment under test, this embodiment selects a new energy equipment of the same type as the new energy equipment under test as a reference object, that is, the analysis object in the following text. In other words, obtaining the type of the new energy equipment under test is to obtain a new energy equipment of the same type as the new energy equipment under test.

[0076] S11: Select multiple new energy devices under the selected type as the analysis objects.

[0077] In practice, there is no limit to the number of specific analysis objects selected. For example, if the type of new energy vehicle to be tested obtained in the above steps is a BYD EV450, then multiple BYD EV450s can be selected as analysis objects in this step. It should be noted that while multiple new energy vehicles of the same type are selected as analysis objects here, to improve the accuracy of the detection, multiple new energy vehicles of the same type, age, and region as the new energy vehicle to be tested can be selected as analysis objects.

[0078] S12: Obtain the first highest temperature data of a reference conduction process matching the object being analyzed; wherein the first highest temperature data comes from the data generated by the object being analyzed during the conduction process.

[0079] During the electrical conduction process of an electric vehicle (especially during charging), the battery system's temperature, maximum individual cell voltage, total system voltage, and state of charge (SOC) are crucial indicators characterizing the battery's current state. Among these, battery temperature data (including maximum temperature, minimum temperature, maximum temperature number, and minimum temperature number) is mandatory data required by national standards to be transmitted in real-time by the Battery Management System (BMS) to the charging equipment during the charging phase. It is also a vital parameter for the charging equipment to monitor the power battery status of new energy vehicles during charging, and is of great significance for ensuring safe charging of vehicles. In practice, excessively high battery temperatures can easily lead to safety accidents. Therefore, this embodiment uses the maximum temperature data as a basis for detecting electrical anomalies in the new energy vehicle to be tested.

[0080] It should be noted that the maximum temperature anomaly detection described in this application should be interpreted broadly. It includes not only anomaly detection targeting the maximum temperature, but also anomaly detection of other variables directly or indirectly affected by the maximum temperature. In other words, the conductivity anomaly detection method and apparatus for new energy equipment involved in the claims of this application are not limited to anomaly detection with the ultimate goal of determining whether the maximum temperature anomaly is abnormal. Instead, it can also consider anomalies in other variables (such as temperature rise) that are directly or indirectly related to the maximum temperature. In the embodiments of this application, battery temperature specifically refers to the maximum temperature of a single battery cell. Taking charging as an example, battery temperature rise refers to the change in the maximum battery temperature during charging. For example, if the maximum temperature of a single battery cell is 47°C at the 20th minute of charging, and rises to 48°C at the 21st minute, then this 1-minute battery temperature rise is represented as 48-47=1°C. In the above example, the monitoring period for battery temperature rise is 1 minute. Users can also set the duration of the monitoring period according to actual needs; this embodiment of the invention does not specifically limit it.

[0081] Taking the charging process as an example, the information exchange between the off-board charger and the vehicle battery system according to GB / T 27930 includes different time periods: the handshake phase, the parameter configuration phase, the charging phase, and the charging completion phase. This encompasses all stages of energy output and information exchange between the off-board charger and the vehicle battery system from the handshake interaction to the completion of charging. Each charging stage has a corresponding charging record, including data such as the charging vehicle model, vehicle identification information, region information, and the battery's highest and lowest temperatures. Since the object of analysis is a reference object for the new energy equipment under test, the conductivity process matched to the object of analysis is called the reference conductivity process, and the first highest temperature data of the reference conductivity process matched to the object of analysis is obtained. It should be noted that the first highest temperature data is not a fixed value, but varies depending on the selected time period, region, conductivity duration, conductivity ratio, etc.

[0082] S13: Obtain the actual highest temperature data of the current conductive process of the new energy equipment under test.

[0083] To detect conductivity anomalies in new energy equipment under test, it is necessary to obtain the actual highest temperature data during the current conduction process of the equipment. Taking the charging process of the equipment under test as an example, if the current charging process may take 20 minutes, in order to reduce the amount of data uploaded, charging data is uploaded to the cloud every 30 seconds. Each uploaded charging data is the highest temperature data within the corresponding 30 seconds, thus obtaining the actual highest temperature data of the current charging process of the equipment under test.

[0084] S14: Based on the correspondence between the first highest temperature data and time, the first safety threshold corresponding to the first highest temperature data is determined using an anomaly detection method.

[0085] The method used for anomaly detection is not limited; statistical analysis or cluster analysis methods can be employed. Specifically, the statistical analysis method can be a normal distribution statistical method, and the cluster analysis method can be a Gaussian mixture clustering method. Here, the normal distribution statistical method is used as an example to illustrate determining the first safety threshold corresponding to the first highest temperature data during the reference charging process.

[0086] (1) Select reference charging process data from the charging orders of new energy equipment of the same type as the new energy equipment to be tested in the past 30 days as sample data;

[0087] (2) For each order, obtain the maximum value of the highest battery temperature per minute as the highest temperature corresponding to this order;

[0088] (3) Calculate the average μ and standard deviation σ of the highest temperature for all orders;

[0089] (4) According to the "3σ" principle of normal distribution: the interval (μ-3σ, μ+3σ) is the actual possible range of values ​​for the random variable X. The probability of X falling outside this interval is less than three per thousand, and in practical problems, such an event is generally considered unlikely to occur. If the variable exceeds this three per thousand, it is an outlier. Therefore, the threshold for the first highest temperature is μ+3σ, which is the first safety threshold.

[0090] S15: Compare the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, proceed to step S16.

[0091] The actual maximum temperature data is compared with a first safety threshold. If the actual maximum temperature data is less than or equal to the first safety threshold, it indicates that the actual maximum temperature data is normal; if the actual maximum temperature data is higher than the first safety threshold, it can be preliminarily determined that the actual maximum temperature data is abnormal. However, relying solely on the maximum temperature data for anomaly testing of the new energy equipment may result in inaccurate test results. Therefore, after initially determining that the actual maximum temperature data is abnormal, further assessment of the accuracy of the test results is necessary.

[0092] S16: Obtain the actual start temperature of the current conduction process.

[0093] In practice, situations such as vehicles being exposed to direct sunlight, having just completed highway driving, or having just finished prolonged operation can cause excessively high starting temperatures. This results in the actual starting temperature of the new energy vehicle under test being significantly higher than the starting temperature of the object being analyzed, leading to misjudgments of conductivity abnormalities in the device. Therefore, after initially identifying an anomaly in the actual maximum temperature data, this embodiment uses the starting temperature to further assess the test results. Thus, the actual starting temperature of the current conductivity process is obtained, and as listed above, charging data is uploaded to the cloud every 30 seconds. The first charging data uploaded to the cloud is referred to as the actual starting temperature.

[0094] S17: Compare the actual start temperature with the preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, proceed to step S18.

[0095] The actual starting temperature is compared with the preset starting temperature threshold. The value of the preset starting temperature threshold is not limited; for example, the starting temperature threshold can be determined based on the starting temperature of the object being analyzed.

[0096] S18: Determine if the actual maximum temperature data of the new energy equipment under test is abnormal, so as to serve as the basis for evaluating the conductivity abnormality of the new energy equipment under test.

[0097] When the actual starting temperature is lower than the preset starting temperature, it indicates that the actual starting temperature is not high, and it is determined that the abnormality in the actual maximum temperature data is causing the abnormal conductivity of the new energy equipment under test.

[0098] The method for detecting conductivity anomalies in new energy equipment provided in this embodiment includes: identifying the type of new energy equipment to be tested; selecting multiple new energy equipment of the same type as analysis objects; obtaining first maximum temperature data of a reference conductivity process matching the analysis objects; obtaining actual maximum temperature data of the current conductivity process of the new energy equipment to be tested; determining a first safety threshold corresponding to the first maximum temperature data based on the correspondence between the first maximum temperature data and time using an anomaly detection method; comparing the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, obtaining the actual start temperature of the current conductivity process; comparing the actual start temperature with a preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, determining that the actual maximum temperature data of the new energy equipment to be tested is abnormal, which serves as the basis for evaluating conductivity anomalies in the new energy equipment to be tested. In this method, the maximum temperature safety threshold is obtained through reference conductivity process data of new energy equipment of the same type as the new energy equipment to be tested. Since the reference conductivity process data is real data, compared with existing fixed thresholds, the obtained safety threshold can more accurately reflect the current conductivity state of the new energy equipment to be tested. The safety threshold obtained by this technical solution can improve the accuracy of conductivity anomaly detection. Furthermore, considering that comparing new energy devices with low initial conductivity temperatures with those with high initial conductivity temperatures could easily lead to misjudgments of the highest temperature anomaly in the new energy device with the higher initial conductivity temperature, this method does not directly determine that the new energy device has a conductivity anomaly when the actual highest temperature data is higher than the first safety threshold. Instead, it further judges the relationship between the initial temperature and the preset initial temperature threshold. Only when the actual initial temperature is lower than the preset initial temperature threshold is the actual highest temperature data of the new energy device under test determined to be abnormal, making the identification of conductivity anomalies in new energy devices more accurate.

[0099] In the above embodiments, after initially determining that the conductivity of the new energy equipment under test is abnormal, the actual starting temperature is further used to determine whether the conductivity of the new energy equipment under test is abnormal. If the actual starting temperature is lower than a preset starting temperature threshold, the conductivity of the new energy equipment under test is determined to be abnormal. If the actual starting temperature is higher than the preset starting temperature threshold, it is necessary to further determine that the highest temperature data of the new energy equipment under test is abnormal. Therefore, in order to more accurately detect the conductivity abnormality of the new energy equipment, a preferred embodiment is that, when the actual starting temperature is higher than the preset starting temperature threshold, the detection method for the conductivity abnormality of the new energy equipment further includes:

[0100] Obtain the second highest temperature data of a reference conduction process that matches the object being analyzed; wherein the second highest temperature data comes from the data generated by the object being analyzed during the conduction process;

[0101] Based on the correspondence between the second highest temperature data and time, the second safety threshold corresponding to the second highest temperature data is determined using anomaly detection methods.

[0102] Compare the actual maximum temperature data with the second safety threshold;

[0103] If the actual maximum temperature data is higher than the second safety threshold, the actual maximum temperature data of the new energy equipment under test is determined to be abnormal, which will serve as the basis for evaluating the conductivity abnormality of the new energy equipment under test.

[0104] The above steps derive the first safety threshold based on the first highest temperature data. In this embodiment, the second safety threshold is derived based on the second highest temperature data. It should be noted that the conditions for obtaining the first and second highest temperature data differ. To ensure more accurate detection results, the conditions for obtaining the second highest temperature data are more stringent than those for obtaining the first highest temperature data. Consequently, the second safety threshold derived from the second highest temperature data is more accurate than the first safety threshold derived from the first highest temperature data. The method for obtaining the second safety threshold from the second highest temperature data is the same as the method for obtaining the first safety threshold from the first highest temperature data; therefore, the method for obtaining the second safety threshold from the second highest temperature data will not be described further here.

[0105] After obtaining the second safety threshold, the actual maximum temperature data is compared with the second safety threshold, which is more accurate than the first safety threshold. If the actual maximum temperature data is higher than the second safety threshold, it is determined that the actual maximum temperature data of the new energy equipment under test is abnormal, and thus the conductivity of the new energy equipment under test is abnormal.

[0106] In the method provided in this embodiment, the actual maximum temperature data is first compared with a first safety threshold. Then, the actual starting temperature is compared with a preset starting temperature threshold to eliminate false judgments caused by excessively high actual starting temperatures. Finally, the actual maximum temperature data is further compared with a second safety threshold. Therefore, this method performs multiple anomaly detections on the new energy equipment under test to determine the detection result. Compared to a detection result determined by only one comparison, the detection result obtained by the method provided in this embodiment is more accurate.

[0107] In practice, in order to quickly obtain the first highest temperature data, a preferred implementation method is to obtain the first highest temperature data of a reference conductive process matching the object of analysis, including:

[0108] Obtain multiple first target conductive orders that match the analysis object within a first preset time period and a preset area;

[0109] Extract the highest temperature data of the reference conductive process from each first target conductive order.

[0110] To facilitate understanding of battery data during the conduction process, in this implementation, the data generated by the new energy equipment during conduction is stored in a conduction order. The conduction order records data such as the amount of electricity conducted, the power conducted, and the temperature corresponding to each conduction moment, categorized by conduction time. Therefore, when the first highest temperature data is needed, it can be directly obtained from the first target conduction order. To ensure the reference value of the first highest temperature data obtained from each analysis object and to improve the accuracy of detecting conduction anomalies in the new energy equipment under test, this embodiment limits the acquisition of the target conduction order corresponding to the analysis object to first target conduction orders within a first preset time period and a preset area. The first preset time period and preset area are not limited; for example, if the first target conduction orders matching the analysis object within the same charging area from 8:30 AM to 9:00 AM on July 10, 2022 are obtained, the battery data throughout the entire conduction process is recorded in the conduction order in chronological order.

[0111] The method provided in this embodiment for analyzing the first highest temperature of an object during a reference conduction process from a first target conductive order is convenient and fast because the first target conductive order records temperature data corresponding to different moments during the conduction process of the new energy equipment according to the conduction time.

[0112] In the above embodiments, the first highest temperature data is obtained from the first target conductive order. In this embodiment, to conveniently and quickly obtain the second highest temperature data, the method used is also to obtain the highest temperature data from the conductive order. Specifically, obtaining the second highest temperature data of the reference conductive process matching the analysis object includes:

[0113] Obtain multiple second target conductive orders that match the analysis object within a first preset time period, within a preset area, and under a preset conductive time period and / or preset conductive ratio;

[0114] Extract the second highest temperature data of the reference conductive process from each second target conductive order.

[0115] Since conduction duration and conductivity rate are key factors affecting battery temperature, this embodiment, when obtaining the second maximum temperature, not only limits the first preset duration and preset region, but also limits the conduction duration and conductivity rate. That is, the first maximum temperature data is obtained within the first preset duration, within the preset region, with a preset conduction duration and / or a preset conductivity rate. The first preset duration, preset region, preset conduction duration, and / or preset conductivity rate are not limited and are determined based on actual conditions. It should be noted that, to ensure the conductivity safety of new energy equipment, the preset conductivity rate value cannot exceed the maximum conductivity rate.

[0116] The method provided in this embodiment for obtaining the second highest temperature of the analysis object during the reference conduction process from the second target conduction order is similar to the method for obtaining the first highest temperature data, both of which are obtained from conduction orders. The difference is that the first target conduction order is the conduction data of the analysis object within a first preset time and preset area, while the second target conduction order is the conduction data of the analysis object within a first preset time and preset area, a preset conduction time, and / or a preset conduction ratio. The second highest temperature data obtained by taking the conduction time and / or conduction ratio into account is more referential than the first highest temperature data. As a result, the second safety threshold obtained from the second highest temperature data can more accurately determine whether there is an abnormality in the conduction of the new energy equipment under test than the first safety threshold obtained from the first highest temperature data.

[0117] In the above embodiments, the actual starting temperature is compared with a preset starting temperature threshold to determine whether the actual starting temperature is normal. In practice, to make the obtained preset starting temperature threshold more reliable, a preferred embodiment includes obtaining the preset starting temperature threshold by:

[0118] Obtain the temperature data of the start of heat dissipation transmitted by the BMS of each analysis object;

[0119] The preset start temperature threshold is determined based on the temperature data at which heat dissipation begins.

[0120] The Battery Management System (BMS) needs to manage the battery to achieve maximum energy storage, round-trip efficiency, and safety under various conditions (temperature, altitude, maximum rate capability, state of charge, cycle life, etc.). When determining the preset start-up temperature threshold based on the start-up temperature data transmitted by the BMS of each analyzed object, the average value of the start-up temperature data can be obtained and used as the preset start-up temperature threshold. Alternatively, the frequency of occurrence of each start-up temperature data point can be counted, and the most frequently occurring temperature can be used as the preset start-up temperature threshold. Currently, the preset start-up temperature threshold determined based on the start-up temperature of the BMS of the analyzed object is 35 degrees Celsius.

[0121] Furthermore, in implementation, a preset start-up temperature threshold can be determined using historical data of the new energy equipment to be tested. A preferred implementation method includes obtaining the preset start-up temperature threshold by:

[0122] Obtain multiple historical conductive orders that match the new energy equipment to be tested within a first preset time period;

[0123] Extract the corresponding first-start conductivity temperature data from each historical conductive order;

[0124] The preset start temperature threshold is determined based on the first start conduction temperature data.

[0125] Specifically, the corresponding first start conduction temperature data can be extracted from the historical orders of the new energy equipment to be tested. The average value of the first start conduction temperature data can be obtained and used as the preset start temperature threshold. Alternatively, the number of times each first start conduction temperature data appears can be counted and the first start conduction temperature data with the most occurrences can be selected as the preset start temperature threshold.

[0126] In addition, during implementation, a preset start temperature threshold can be determined based on the conductivity of the object being analyzed. A preferred embodiment involves obtaining the preset start temperature threshold by:

[0127] Obtain multiple third-target conductive orders that match each analysis object within a first preset time period;

[0128] Extract the corresponding second-starting conductivity temperature data from each third-target conductive order;

[0129] The preset start temperature threshold is determined based on the second start conduction temperature data.

[0130] Specifically, after obtaining the third target conductive order, the second start conductive temperature data is extracted from each order. The average value of the second start conductive temperature data can be obtained and used as the preset start temperature threshold. Alternatively, the number of occurrences of each second start conductive temperature data can be counted, and the second start conductive temperature data with the most occurrences can be selected as the preset start temperature threshold.

[0131] This section lists three methods for determining the preset start-up temperature threshold. In practice, other methods can also be used to obtain the preset start-up temperature threshold. Obtaining the preset start-up temperature threshold through multiple methods makes the obtained threshold more flexible and facilitates the detection of the actual start-up temperature of the new energy equipment under test.

[0132] In the above embodiments, after the actual maximum temperature data exceeds the first safety threshold, anomaly detection is further performed on the new energy equipment under test based on the starting temperature. In practice, after the actual maximum temperature data exceeds the first safety threshold, anomaly detection can also be performed on the new energy equipment under test based on the temperature change trend. Specifically, when the actual maximum temperature data exceeds the first safety threshold, the detection method for abnormal conductivity of the new energy equipment further includes:

[0133] Once the actual highest temperature data is determined to be higher than the first safety threshold, the temperature data of the new energy equipment to be tested at each moment is obtained within the second preset time period.

[0134] Based on the temperature data, obtain the temperature change trend of the new energy equipment to be tested within the second preset time period;

[0135] If the temperature does not drop or does not drop to the preset value within the second preset time period, the actual maximum temperature data of the new energy equipment under test is determined to be abnormal, which will serve as the basis for evaluating the conductivity abnormality of the new energy equipment under test.

[0136] The specific value of the second preset duration is not limited and is determined based on the actual situation. If the temperature change trend of the new energy device under test is downward or drops to the preset value within the second preset duration, it indicates that the new energy device under test has normal conductivity; conversely, it indicates that the new energy device under test has abnormal conductivity. The specific data of the preset value to which the new energy device under test drops is not limited and is also determined based on the actual situation. In practice, the preset value can be determined based on data from the conductivity process of new energy devices of the same type as the new energy device under test. Taking the analysis object in the above embodiment as an example, a method for obtaining the preset value is described. First, the highest temperature data of each analysis object is obtained. Then, after the second preset duration, the temperature data of the analysis object at the current moment is obtained (it should be noted that the current moment refers to the last moment in the second preset duration). The difference between the highest temperature data of each analysis object and the corresponding current temperature data is obtained. The average value of each difference is calculated. The difference between the actual highest temperature data of the new energy device under test and the average value is the preset value.

[0137] The method provided in this embodiment, which determines whether there is an abnormality in the conductivity of the new energy device under test by observing the temperature change trend within a preset time period when the actual maximum temperature data is higher than the first safety threshold, is more accurate than the method that directly determines that the new energy device under test is abnormal when the actual maximum temperature data is higher than the first safety threshold.

[0138] In implementation, to rule out the possibility of abnormal conductivity in new energy equipment due to excessively high actual starting temperature, a preferred embodiment includes, after determining that the actual maximum temperature data of the new energy equipment under test is abnormal if the actual maximum temperature data exceeds the second safety threshold, the following steps are also included:

[0139] Stop the electrical conductivity of the new energy equipment under test and start the heat dissipation system of the new energy equipment under test;

[0140] The battery temperature of the new energy device under test is adjusted to the preset start temperature threshold through the heat dissipation system.

[0141] Initiate the conduction process of the new energy device under test and return to the step of obtaining the actual highest temperature data of the current conduction process of the new energy device under test.

[0142] Batteries in new energy devices are extremely sensitive to temperature, with 20-35°C being their comfortable operating range. To increase battery life, these devices typically include cooling systems such as fans and liquid cooling systems. When the battery temperature is too high, these systems dissipate heat. Since the actual starting temperature is higher than a preset starting temperature threshold, the actual maximum temperature data is further compared with a second safety threshold to determine if the actual maximum temperature data of the new energy device under test is abnormal. Therefore, to avoid detecting abnormal conductivity in the new energy device under test due to an excessively high actual starting temperature, this embodiment stops the conductivity of the new energy device under test and activates the cooling system to cool the battery, reducing the battery temperature to the preset starting temperature threshold. The conductivity of the new energy device under test is then restarted, returning to the step of obtaining the actual maximum temperature data of the current conductivity process of the new energy device under test.

[0143] In this embodiment, if the actual maximum temperature data is higher than the second safety threshold, after determining that the actual maximum temperature data of the new energy device under test is abnormal, the battery temperature is adjusted to the preset start temperature threshold through the heat dissipation system, effectively eliminating the influence of abnormal actual start temperature data on the test results; secondly, the step of obtaining the actual maximum temperature data of the current conduction process of the new energy device under test is returned, so that the conduction abnormality of the new energy device under test can be continuously detected.

[0144] In practice, to facilitate users' understanding of the test results for the new energy equipment under test, a preferred implementation method includes, after determining that the actual maximum temperature data of the new energy equipment under test is abnormal, the following steps are also taken:

[0145] Output a prompt message to indicate abnormal conductivity of the new energy equipment under test.

[0146] There are no restrictions on the method or content of the prompts. For example, after it is determined that the actual maximum temperature data of the new energy equipment under test is abnormal, an alarm can be triggered by a buzzer to alert the user that the new energy equipment under test has a conductivity problem, so that the user can intuitively understand that the new energy equipment under test has a conductivity problem.

[0147] The above embodiments have described in detail the method for detecting conductivity anomalies in new energy equipment. This application also provides embodiments of a device for detecting conductivity anomalies in new energy equipment. It should be noted that this application describes the embodiments of the device from two perspectives: one based on functional modules and the other based on hardware.

[0148] Figure 2 A structural diagram of a device for detecting conductivity anomalies in new energy equipment provided in one embodiment of this application. This embodiment, based on functional modules, includes:

[0149] Confirmation module 10 is used to confirm the type of new energy equipment to be tested;

[0150] Select module 11, which is used to select multiple new energy devices under a certain type as the analysis object;

[0151] The first acquisition module 12 is used to acquire the first highest temperature data of a reference conduction process that matches the object being analyzed; wherein, the first highest temperature data comes from the data generated by the object being analyzed during the conduction process;

[0152] The second acquisition module 13 is used to acquire the actual highest temperature data of the current conductive process of the new energy equipment under test;

[0153] The first determining module 14 is used to determine the first safety threshold corresponding to the first maximum temperature data based on the correspondence between the first maximum temperature data and time using an anomaly detection method.

[0154] The first comparison module 15 is used to compare the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, the third acquisition module 16 is triggered.

[0155] The third acquisition module 16 is used to acquire the actual start temperature of the current conduction process; wherein, the actual start temperature is the data generated for the first time in the current conduction process of the new energy device under test;

[0156] The second comparison module 17 is used to compare the actual start temperature with the preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, the second determination module 18 is triggered.

[0157] The second determining module 18 is used to determine whether the actual maximum temperature data of the new energy equipment under test is abnormal, so as to serve as the basis for evaluating the conductivity abnormality of the new energy equipment under test.

[0158] Since the embodiments of the apparatus and the embodiments of the method correspond to each other, please refer to the description of the embodiments of the method for the embodiments of the apparatus, which will not be repeated here.

[0159] The device for detecting conductivity anomalies in new energy equipment provided in this embodiment confirms the type of new energy equipment to be tested through a confirmation module; selects multiple new energy equipment under the type as analysis objects through a selection module; acquires the first maximum temperature data of a reference conductivity process matching the analysis object through a first acquisition module; wherein the first maximum temperature data comes from the data generated by the analysis object during the conductivity process; acquires the actual maximum temperature data of the current conductivity process of the new energy equipment to be tested through a second acquisition module; determines the first safety threshold corresponding to the first maximum temperature data through a first determination module based on the correspondence between the first maximum temperature data and time using an anomaly detection method; compares the actual maximum temperature data with the first safety threshold through a first comparison module; if the actual maximum temperature data is higher than the first safety threshold, a third acquisition module is triggered to acquire the actual start temperature of the current conductivity process; wherein the actual start temperature is the data generated for the first time in the current conductivity process of the new energy equipment to be tested; compares the actual start temperature with a preset start temperature threshold through a second comparison module; if the actual start temperature is lower than the preset start temperature threshold, a second determination module is triggered to determine that the actual maximum temperature data of the new energy equipment to be tested is abnormal, as a basis for evaluating the conductivity anomaly of the new energy equipment to be tested. In this device, the maximum temperature safety threshold is obtained through reference conductivity data from a new energy device of the same type as the device under test. Since this reference conductivity data is real data, the obtained safety threshold more accurately reflects the current conductivity state of the new energy device under test compared to existing fixed thresholds. This improved safety threshold enhances the accuracy of conductivity anomaly detection. Furthermore, considering that comparing new energy devices with low initial conductivity temperatures with those with high initial conductivity temperatures could easily lead to misjudgments of the maximum temperature anomaly in the device with the higher initial conductivity temperature, this device does not directly determine a conductivity anomaly when the actual maximum temperature data exceeds the first safety threshold. Instead, it further assesses the relationship between the initial temperature and a preset initial temperature threshold. Only when the actual initial temperature is lower than the preset initial temperature threshold is the actual maximum temperature data of the new energy device under test deemed abnormal, thus making the identification of conductivity anomalies in new energy devices more accurate.

[0160] Figure 3This is a structural diagram of a device for detecting conductivity anomalies in new energy equipment, provided as another embodiment of this application. This embodiment is based on a hardware perspective, such as... Figure 3 As shown, the device for detecting abnormal conductivity in new energy equipment includes:

[0161] Memory 20 is used to store computer programs;

[0162] The processor 21 is used to execute a computer program to implement the steps of the method for detecting electrical abnormalities in new energy equipment as described in the above embodiments.

[0163] The device for detecting abnormal conductivity in new energy equipment provided in this embodiment may include, but is not limited to, smartphones, tablets, laptops, or desktop computers.

[0164] The processor 21 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 21 may be implemented using at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 21 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 21 may also include an Artificial Intelligence (AI) processor, which is used to handle computational operations related to machine learning.

[0165] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 20 is used to store at least the following computer program 201, which, after being loaded and executed by the processor 21, is capable of implementing the relevant steps of the method for detecting conductivity anomalies in new energy equipment disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, and the storage method may be temporary or permanent storage. The operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, the data involved in the aforementioned method for detecting conductivity anomalies in new energy equipment.

[0166] In some embodiments, the device for detecting abnormal conductivity of new energy equipment may further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0167] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the device for detecting electrical anomalies in new energy equipment and may include more or fewer components than shown.

[0168] The device for detecting electrical conductivity anomalies in new energy equipment provided in this application includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the following method: the method for detecting electrical conductivity anomalies in new energy equipment, with the same effect as above.

[0169] Finally, this application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above method embodiments.

[0170] It is understood that if the methods in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, 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 executes all or part of the steps of the methods described in the various embodiments of this application. 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.

[0171] The computer-readable storage medium provided in this application includes the aforementioned method for detecting conductivity anomalies in new energy equipment, and has the same effect.

[0172] To enable those skilled in the art to better understand the technical solution of this application, the following description is provided in conjunction with the appendix. Figure 4 This application will now provide a more detailed description of the above. Figure 4 This is an overall flowchart of the electrical conductivity anomaly detection method for new energy equipment provided in this application embodiment. Figure 4 As shown, the method includes:

[0173] S19: Obtain a charging / discharging order;

[0174] S20: Obtain the highest temperature of the order;

[0175] S21: Obtain the highest temperature safety threshold for the same region, vehicle model, and time.

[0176] S22: Determine if the highest temperature index of the order is abnormal; if not, proceed to step S23 or step S29; if yes, proceed to step S24.

[0177] S23: Confirmed as a normal order;

[0178] S24: Obtain the order start temperature;

[0179] S25: Determine if the starting temperature is too high; if not, proceed to step S26; if yes, proceed to step S27.

[0180] S26: The highest temperature is confirmed to be abnormal, resulting in an order error.

[0181] S27: Obtain the highest temperature safety threshold for the same region, vehicle model, time, charging duration, and charging rate.

[0182] S28: Determine if the highest temperature indicator of the order is abnormal; if not, return to step S23; if yes, return to step S26.

[0183] S29: Determine whether the temperature will subsequently decrease; if yes, return to step S23; if no, return to step S26.

[0184] The conductivity anomaly detection method for new energy equipment provided in this embodiment obtains the highest temperature safety threshold through reference conductivity process data of new energy equipment of the same type as the new energy equipment under test. Since the reference conductivity process data is real data, the obtained safety threshold more accurately reflects the current conductivity state of the new energy equipment under test compared to existing fixed thresholds. This method improves the accuracy of conductivity anomaly detection. Furthermore, in cases where a conductivity anomaly is initially determined, the method further determines the anomaly based on the starting temperature. Considering that comparing new energy equipment with low starting conductivity temperatures with those with high starting conductivity temperatures could easily lead to misjudgment of the highest temperature anomaly in the equipment with the higher starting conductivity temperature, this embodiment provides a more accurate method for identifying conductivity anomalies in new energy equipment. Alternatively, in cases where a conductivity anomaly is initially determined, the method further determines the anomaly based on the subsequent temperature change trend, making the identification of conductivity anomalies in new energy equipment even more accurate.

[0185] The foregoing provides a detailed description of the method, apparatus, and medium for detecting conductivity anomalies in new energy equipment provided in this application. The various embodiments in the specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

[0186] It should also be noted that, in this specification, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for detecting electrical conductivity anomalies in new energy equipment, characterized in that, include: Confirm the type of new energy equipment to be tested; Select multiple new energy devices under the aforementioned type as the analysis objects; Obtain first highest temperature data of a reference conduction process matching the object being analyzed; wherein the first highest temperature data comes from data generated by the object being analyzed during the conduction process; Obtain the actual highest temperature data of the current conductive process of the new energy device under test; Based on the correspondence between the first highest temperature data and time, an anomaly detection method is used to determine the first safety threshold corresponding to the first highest temperature data. Compare the actual highest temperature data with the first safety threshold; If the actual highest temperature data is higher than the first safety threshold, then the actual start temperature of the current conduction process is obtained; Compare the actual start temperature with the preset start temperature threshold. If the actual starting temperature is lower than the preset starting temperature threshold, the actual maximum temperature data of the new energy device under test is determined to be abnormal, which serves as the basis for evaluating the conductivity abnormality of the new energy device under test.

2. The method for detecting conductivity anomalies in new energy equipment according to claim 1, characterized in that, If the actual starting temperature is higher than the preset starting temperature threshold, the method further includes: Obtain a second highest temperature data for the reference conduction process that matches the object being analyzed; wherein the second highest temperature data comes from data generated by the object being analyzed during the conduction process; Based on the correspondence between the second highest temperature data and time, the second safety threshold corresponding to the second highest temperature data is determined using the anomaly detection method. Compare the actual maximum temperature data with the second safety threshold; If the actual maximum temperature data is higher than the second safety threshold, then the actual maximum temperature data of the new energy device under test is determined to be abnormal, which serves as the basis for evaluating the conductivity abnormality of the new energy device under test.

3. The method for detecting electrical conductivity anomalies in new energy equipment according to claim 1, characterized in that, The acquisition of the first highest temperature data of the reference conductivity process matching the object of analysis includes: Obtain multiple first target conductive orders that match the analysis object within a first preset time period and a preset area; Extract the first highest temperature data of the reference conductive process from each of the first target conductive orders.

4. The method for detecting electrical conductivity anomalies in new energy equipment according to claim 3, characterized in that, The acquisition of the second highest temperature data of the reference conductivity process matching the analyzed object includes: Obtain multiple second target conductive orders that match the analysis object within the first preset time period, within the preset region, and under a preset conductive time period and / or preset conductive ratio; Extract the second highest temperature data of the reference conductive process from each of the second target conductive orders.

5. The method for detecting conductivity anomalies in new energy equipment according to any one of claims 1 to 4, characterized in that, Obtaining the preset start temperature threshold includes: Obtain the temperature data of the start of heat dissipation transmitted by the BMS of each of the analyzed objects; The preset start temperature threshold is determined based on the temperature data at which heat dissipation begins.

6. The method for detecting abnormal conductivity in new energy equipment according to claim 3 or 4, characterized in that, Obtaining the preset start temperature threshold includes: Obtain multiple historical conductive orders that match the new energy equipment to be tested within the first preset time period; Extract the corresponding first start conductivity temperature data from each of the aforementioned historical conductive orders; The preset start temperature threshold is determined based on the first start conduction temperature data.

7. The method for detecting abnormal conductivity in new energy equipment according to claim 3 or 4, characterized in that, Obtaining the preset start temperature threshold includes: Obtain multiple third-target conductive orders that match each of the analyzed objects within the first preset time period; Extract the corresponding second starting conductivity temperature data from each of the third target conductive orders; The preset start temperature threshold is determined based on the second start conduction temperature data.

8. The method for detecting conductivity anomalies in new energy equipment according to claim 1, characterized in that, If the actual maximum temperature data is higher than the first safety threshold, the method further includes: Starting from the moment it is determined that the actual highest temperature data is higher than the first safety threshold, the temperature data of the new energy equipment to be tested at each moment within the second preset time period is obtained. Based on the temperature data, obtain the temperature change trend of the new energy device to be tested within the second preset time period; If the temperature does not decrease or does not decrease to the preset value within the second preset time period, the actual maximum temperature data of the new energy device under test is determined to be abnormal, and is used as the basis for evaluating the conductivity abnormality of the new energy device under test.

9. The method for detecting conductivity anomalies in new energy equipment according to claim 2, characterized in that, After determining that the actual maximum temperature data of the new energy equipment under test is abnormal if the actual maximum temperature data is higher than the second safety threshold, the method further includes: Stop conducting electricity to the new energy device under test and start the heat dissipation system of the new energy device under test; The heat dissipation system adjusts the battery temperature of the new energy device to be tested to the preset start temperature threshold. Initiate the conduction of the new energy device under test, and return to the step of obtaining the actual highest temperature data of the current conduction process of the new energy device under test.

10. The method for detecting conductivity anomalies in new energy equipment according to claim 9, characterized in that, After determining that the actual maximum temperature data of the new energy equipment under test is abnormal, the method further includes: Output a prompt message indicating an abnormal conductivity of the new energy device under test.

11. A device for detecting abnormal conductivity in new energy equipment, characterized in that, include: The confirmation module is used to confirm the type of new energy equipment to be tested; The selection module is used to select multiple new energy devices under the aforementioned type as analysis objects; The first acquisition module is used to acquire the first highest temperature data of a reference conduction process matching the analysis object; wherein the first highest temperature data comes from the data generated by the analysis object during the conduction process; The second acquisition module is used to acquire the actual highest temperature data of the current conductive process of the new energy device under test. The first determining module is used to determine the first safety threshold corresponding to the first highest temperature data based on the correspondence between the first highest temperature data and time using an anomaly detection method. The first comparison module is used to compare the actual maximum temperature data with the first safety threshold; if the actual maximum temperature data is higher than the first safety threshold, the third acquisition module is triggered. The third acquisition module is used to acquire the actual start temperature of the current conduction process; The second comparison module is used to compare the actual start temperature with a preset start temperature threshold; if the actual start temperature is lower than the preset start temperature threshold, the second determination module is triggered. The second determining module is used to determine that the actual maximum temperature data of the new energy device under test is abnormal, so as to serve as the basis for evaluating the conductivity abnormality of the new energy device under test.

12. A device for detecting abnormal conductivity in new energy equipment, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the steps of the method for detecting electrical abnormalities in new energy equipment as described in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for detecting electrical conductivity anomalies in new energy equipment as described in any one of claims 1 to 10.

Images