Battery management system, heating film anomaly identification method, battery pack and electric device

Abstract

This application provides a battery management system, a heating film anomaly identification method, a battery pack, and an electrical device. The battery management system includes a sampling circuit and a controller. The sampling circuit collects the current of the main circuit, the highest temperature value of the battery module, and the lowest temperature value of the battery module. The controller forms a state dataset based on the data acquired by the sampling circuit at each timestamp and identifies whether there is an anomaly in the heating film of the heating circuit based on the state dataset. In this application, the anomaly of the heating film can be identified by analyzing the collected state data related to the battery module. This allows for timely identification and diagnosis of heating film anomalies when the operating state of the heating circuit does not meet expectations. By taking timely measures, the risk of further deterioration of the heating film anomaly leading to serious consequences can be reduced, thereby improving the performance and stability of the battery system.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a battery management system, a heating film abnormality identification method, a battery pack, and electrical equipment. Background Technology

[0002] Energy conservation and emission reduction are key to the sustainable development of the automotive industry, and electric vehicles, due to their energy-saving and environmentally friendly advantages, have become an important component of this sustainable development. For electric vehicles, battery technology is a crucial factor in their development.

[0003] Currently, heating films are commonly used to heat battery components. However, if the heating film malfunctions, it can even lead to safety accidents. Therefore, in order to ensure the safe and reliable operation of batteries, timely identification and diagnosis of heating film abnormalities is an urgent problem to be solved. Summary of the Invention

[0004] This application aims to at least address one of the technical problems existing in the background art. Therefore, one objective of this application is to provide a battery management system, a heating film anomaly identification method, a battery pack, and electrical equipment, capable of timely identifying and diagnosing heating film anomalies, thereby enabling timely countermeasures and reducing the risk of serious consequences caused by heating film failure.

[0005] An embodiment of the first aspect of this application provides a battery management system applied to a battery pack. The battery pack has a main circuit connected to battery components and a heating circuit connected to the main circuit. The heating circuit includes N heating films arranged in parallel. The heating circuit is capable of switching between an on-state and an off-state, where N is a positive integer and N≥2. The battery management system includes:

[0006] The sampling circuit is used to collect the current of the main circuit, the highest temperature value of the battery pack, and the lowest temperature value of the battery pack.

[0007] The controller is configured to:

[0008] A state dataset is formed based on the data obtained by the downsampling circuit at each timestamp; wherein, the state dataset includes at least the timestamp and the highest temperature value, lowest temperature value and main circuit current value corresponding to each timestamp;

[0009] Based on the status dataset, identify and determine whether there is any abnormality in the heating film in the heating circuit.

[0010] The battery management system of this application embodiment is designed so that the controller forms a state dataset based on the state data related to the battery components collected by the sampling circuit. By processing and analyzing the state dataset, it can be used to identify whether there are heating film abnormalities in a heating circuit with N heating films connected in parallel. In this way, heating film abnormalities can be identified and diagnosed before the heating circuit fails completely and its operating state does not meet expectations, realizing fault prediction and early warning. By taking timely measures, the risk of further deterioration of heating film abnormalities leading to serious consequences can be reduced, thereby improving the reliability and safety of the battery pack.

[0011] In some embodiments, the controller is configured to:

[0012] Based on the state dataset, determine the highest and lowest temperature rise rates of the heating circuit during each heating period; determine whether the highest and lowest temperature rise rates meet preset conditions; if they do, determine that there is an abnormality in the heating film in the heating circuit and the abnormality mode is incorrect connection of the heating film resistor; wherein, the heating circuit remains in the open state during the heating period.

[0013] This embodiment analyzes the difference between the highest and lowest temperature rise rates to determine the resistance balance of multiple heating films. When the resistance of multiple heating films is uneven, an anomaly is identified, specifically incorrect heating film resistor connections. This allows for timely detection and correction of incorrect heating film resistor connections, providing early warning of uneven battery module temperatures and reducing damage caused by such conditions.

[0014] In some embodiments, the sampling circuit is further used to collect the on / off state of the heating circuit, and the state dataset further includes a first identifier corresponding to each timestamp, the first identifier being used to indicate the on / off state of the heating circuit.

[0015] The controller is configured to be used for:

[0016] Extract K consecutive data points from the state dataset that are located between two adjacent non-heating state data points and whose first identifier indicates that the heating circuit is in the on state, to obtain the data set for each heating time period, where K is a positive integer greater than or equal to 2; wherein, the first identifier of the non-heating state data indicates that the heating circuit is in the off state.

[0017] For each heating time period, determine the highest and lowest temperature rise rates for that heating time period.

[0018] This embodiment includes a first identifier in the status dataset. The first identifier can clearly distinguish the time periods when the heating circuit is on and off. By filtering the data where the heating circuit is on, the heating time period can be accurately identified and extracted, reducing the impact of non-heating time period data on the accuracy of abnormal diagnosis.

[0019] In some embodiments, the controller is configured to:

[0020] For the highest and lowest temperature values ​​contained in the data set for each heating time period, the data are processed separately based on temperature analysis steps to obtain the highest temperature rise rate and the lowest temperature rise rate.

[0021] The temperature analysis step includes determining the instantaneous temperature rise rate during the heating period, analyzing the instantaneous temperature rise rate based on the sliding window method, calculating the average value within each sliding window, and calculating the average value of all sliding windows; the window size of the sliding window is M, M+2≤K, where M is a positive integer greater than or equal to 2.

[0022] This embodiment determines the instantaneous temperature rise rate and then uses the sliding window method to analyze the instantaneous temperature rise rate. This allows for smoothing of the instantaneous temperature rise rate through the sliding window, which helps to eliminate noise and improve the accuracy of the analysis.

[0023] In some embodiments, the first-order difference method is used to determine the instantaneous temperature rise rate during the heating period. After analysis using the first-order difference method, the changing trends of the highest and lowest temperature values ​​are captured from the instantaneous temperature rise rate. This allows for accurate judgment even with a small amount of data, which helps to accelerate the diagnosis process of heating film anomalies and enables early analysis of incorrect heating film resistance using a small amount of data.

[0024] In some embodiments, the preset condition is one of the following conditions:

[0025] The highest temperature rise rate is greater than or equal to the first threshold value, and the lowest temperature rise rate is less than or equal to the second threshold value, where the second threshold value is a non-negative number and less than the first threshold value.

[0026] The difference between the highest temperature rise rate and the lowest temperature rise rate is greater than the third threshold value, the third threshold value is less than the difference between the first threshold value and the second threshold value, and the third threshold value is close to the first threshold value.

[0027] In this embodiment, the preset condition is designed such that when the preset condition is met, it indicates that there is a large difference between the highest temperature rise rate and the lowest temperature rise rate of the battery module. Since the uneven resistance of the heating film in the heating circuit will affect the temperature rise rate of the battery module when the heating film resistor is connected incorrectly, the preset condition can be used as a standard for accurately diagnosing the incorrect connection of the heating film resistor.

[0028] In some embodiments, the first threshold is 1.8℃ / min, the second threshold is 0℃ / min, and the third threshold is 1.5℃ / min.

[0029] In some embodiments, the controller is configured to: determine a heating current value based on a state dataset, wherein the heating current value is the total current value of the heating circuit and is related to the main circuit current value; analyze and process a first data group consisting of heating current values ​​belonging to historical time periods and their associated timestamps and a second data group consisting of heating current values ​​belonging to the latest time period and their associated timestamps to determine whether a first failure condition is met; if the first failure condition is met, determine that there is an anomaly in the heating film in the heating circuit and the anomaly mode is heating film ablation; wherein the first failure condition is that the heating current value in the second data group is reduced by i / N compared to the heating current value in the first data group, 1≤i<N, and i is a positive integer.

[0030] This embodiment processes the current-related features of the battery module's state data, observing the changes in the main circuit current value over different time periods. If the current value in the latest time period is lower than the current value in historical time periods (i / N, 1≤i<N), and this change persists for a certain period, an anomaly in the heating film can be identified, specifically the partial ablation of multiple heating films. This allows for timely detection and remediation of heating film ablation before the heating circuit completely fails, reducing damage caused by overheating and mitigating the risk of further deterioration and serious consequences from heating film ablation.

[0031] In some embodiments, the sampling circuit is further used to collect the on / off state of the heating circuit, and the state dataset further includes a first identifier corresponding to each timestamp, the first identifier being used to indicate the on / off state of the heating circuit.

[0032] The controller is configured to: extract two adjacent data sets with different first identifiers from the state dataset, and determine the difference between the main circuit current value after the first identifier change and the main circuit current value before the first identifier change in the two data sets as the heating current value.

[0033] The heating current value is closely related to the main circuit current value. Specifically, when the heating circuit switches from an off state to an on state, the current in the main circuit increases, and the increment is the heating current value. Based on this, this embodiment uses the difference between the main circuit current value after the first indicator changes and the main circuit current value before the first indicator changes as the heating current value. The heating circuit current value can be extracted simply by calculation. This eliminates the need for additional hardware such as sensors to independently detect the heating current, which helps reduce system complexity and hardware costs.

[0034] In some embodiments, the battery pack further includes Q power branches to which load elements belong, the load elements being connected in parallel with the heating film, the power branches being switchable between an on state and an off state, the sampling circuit being used to collect the on / off state of the power branches, the state dataset further includes Q second identifiers corresponding to each timestamp, the Q second identifiers being one-to-one with the Q power branches, the second identifiers being used to indicate the on / off state of the corresponding power branch; where Q is a positive integer;

[0035] The controller is configured to be used for:

[0036] The heating current values ​​that meet the outlier selection criteria are filtered out to obtain the filtered dataset. The outlier selection criteria include at least one of the following:

[0037] The heating current value is less than 0A;

[0038] The time interval between the two data points corresponding to the heating current value exceeds the preset duration.

[0039] The second identifiers of the two data points corresponding to the heating current values ​​are different;

[0040] The first data group, consisting of heating current values ​​belonging to historical time periods and their associated timestamps, and the second data group, consisting of heating current values ​​belonging to the most recent time period and their associated timestamps, are analyzed and processed.

[0041] This embodiment reduces the impact of power supply branch interruptions and system instability on data accuracy by removing heating current values ​​that meet the abnormal data selection criteria before processing and analysis. It also reduces analysis deviations caused by irregular preset sampling periods, which can significantly improve the accuracy of heating current value analysis. This, in turn, improves the accuracy of using this as a basis for judging partial heating film ablation and optimizes the effect of heating film ablation anomaly detection.

[0042] In some embodiments, the controller is configured to:

[0043] Data that meets the target data selection criteria are filtered from the state dataset to obtain a preprocessed dataset. The target data selection criteria are used to indicate whether the battery assembly is in a charging state.

[0044] The heating current value is determined based on the preprocessed dataset.

[0045] This embodiment analyzes data from the charging state. Compared to the discharging state data, the charging state data is more stable and has less interference, and can more clearly reflect the changes in the heating current value, which is beneficial to improving the accuracy of detecting abnormal heating film ablation.

[0046] In some embodiments, the target data selection condition is a negative main circuit current value. When the battery module is charging, the current flows into the battery module, resulting in a negative main circuit current. Based on this principle, this embodiment uses a negative main circuit current value as the target data selection condition to filter out data indicating that the battery module is charging, and this filtering method does not rely on complex logic.

[0047] In some embodiments, the sampling circuit is also used to collect the charging and discharging state of the battery assembly. The state dataset also includes a third identifier corresponding to each timestamp. The third identifier is used to indicate the charging and discharging state of the battery assembly. The target data selection condition can also be that the third identifier indicates that the battery assembly is in a charging state.

[0048] This embodiment facilitates the clear and accurate screening of data indicating that the battery components are in a charging state, thereby reducing the possibility of false screening.

[0049] In some embodiments, the controller is configured to:

[0050] Cluster analysis was performed on the first and second data groups based on the clustering algorithm;

[0051] Determine whether multiple groups are formed, and the heating current value of the group corresponding to the second data group is reduced by i / N compared to the heating current value of the group corresponding to the first data group.

[0052] Compared to analysis using trained models or time series models, this embodiment uses a clustering algorithm to divide the first and second data groups into multiple subsets based on features or patterns. This helps identify whether the heating current values ​​of the subsets corresponding to the second data group are normal compared to the heating current values ​​of the subsets corresponding to the first data group, thereby determining whether the first failure condition is met. This eliminates the need for pre-labeling or training the data.

[0053] In some embodiments, the controller is configured to:

[0054] If the first failure condition is met, continue to determine whether the second failure condition is met. The second failure condition is that the rate of increase of at least one of the highest and lowest temperature values ​​of the heating time period to which the timestamp in the second data group belongs gradually decreases.

[0055] If the second failure condition is met, the abnormal mode is determined to be heating film ablation.

[0056] This embodiment combines the heating current value and the battery module temperature to comprehensively analyze and determine whether there is partial heating film ablation. In other words, the decrease in heating current value and the slowdown in the rate of temperature rise of the battery module are used as two indicators to determine heating film ablation, which helps to more accurately determine whether there is partial heating film ablation and improves diagnostic accuracy.

[0057] In some embodiments, the second failure condition is that the lowest temperature rise rate of the heating time period to which the timestamp in the second data group belongs is less than 0°C / min.

[0058] This embodiment, by focusing on the lowest temperature rise rate, can detect signs of heating film ablation earlier and more accurately. By taking timely measures, further damage to the battery system caused by heating film ablation can be avoided.

[0059] An embodiment of the second aspect of this application provides a method for identifying abnormalities in a heating film, including:

[0060] Acquire sampling data;

[0061] A state dataset is formed based on the sampled data at each timestamp; wherein, the state dataset includes at least the timestamp and the highest temperature value, lowest temperature value and main circuit current value corresponding to each timestamp;

[0062] Based on the status dataset, identify and determine whether there is any abnormality in the heating film in the heating circuit.

[0063] An embodiment of the third aspect of this application provides a battery pack, including: a battery component, a main circuit, a heating circuit, and a battery management system according to any one of the embodiments of the first aspect of this application. The main circuit has a main positive circuit and a main negative circuit. One end of the main positive circuit is connected to the positive terminal of the battery component, and one end of the main negative circuit is connected to the negative terminal of the battery component. The heating circuit includes N heating films arranged in parallel. One end of each of the N heating films is connected to one of the main positive circuit and the main negative circuit through a heating switch, and the other end is connected to the other of the main positive circuit and the main negative circuit. The heating switch can be turned on and off, so that the heating circuit can switch between an on state and an off state. Wherein, N is a positive integer, and N≥2.

[0064] An embodiment of the fourth aspect of this application provides an electrical device including a battery pack provided by any of the embodiments of the first aspect of this application.

[0065] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0066] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments disclosed in this application and should not be construed as limiting the scope of this application.

[0067] Figure 1 A simplified electrical schematic diagram of the battery circuit of the battery pack provided in the embodiments of this application under normal heating film conditions;

[0068] Figure 2 A simplified electrical schematic diagram of the battery circuit of the battery pack provided in the embodiment of this application when one of the heating films is burned off.

[0069] Figure 3 A simplified electrical schematic diagram of the battery circuit of the battery pack provided in the embodiments of this application in the case of incorrect connection of the two heating film resistors;

[0070] Figure 4 This is a schematic diagram showing the state dataset in tabular form for some embodiments of this application;

[0071] Figure 5 This is a schematic diagram illustrating the calculation process of the maximum temperature rise rate during the heating time period in some embodiments of this application;

[0072] Figure 6 This is a schematic diagram illustrating the extraction of heating current values ​​in some embodiments of this application;

[0073] Figure 7 This is a schematic diagram showing the clustering analysis results corresponding to some embodiments of this application;

[0074] Figure 8 A flowchart illustrating a heating film anomaly identification method provided in some embodiments of this application;

[0075] Figure 9 This is a flowchart illustrating a heating film anomaly identification method provided in other embodiments of this application. Detailed Implementation

[0076] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0077] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0078] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0079] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0080] In the description of the embodiments of this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0081] Currently, judging from market trends, the application of power batteries is becoming increasingly widespread. Power batteries are not only used in energy storage systems such as hydropower, thermal power, wind power, and solar power plants, but also extensively used in electric vehicles such as electric bicycles, electric motorcycles, and electric cars, as well as in military equipment and aerospace. With the continuous expansion of power battery applications, market demand is also constantly increasing.

[0082] A battery's range is closely related to its capacity and the ambient temperature. When a battery operates at low temperatures, the electrolyte's fluidity decreases, affecting its charge and discharge performance. Low temperatures also slow down the chemical reaction rate and increase the battery's internal resistance, impacting discharge performance and charging speed. To improve battery performance in low-temperature environments, battery thermal management systems use heating films to provide the necessary heat, allowing the battery to maintain its optimal operating temperature.

[0083] Specifically, the heating film typically has two connection terminals. One terminal connects to the main positive circuit between the positive terminal of the battery pack and the load, and the other terminal connects to the main negative circuit between the negative terminal of the battery pack and the load, allowing the battery pack to supply power to the heating film. With prolonged operation of the battery pack, the heating film is prone to overheating, causing the adhesive between the heating film and the battery pack to fail. If the heating film detaches and burns out, it can come into contact with other electrical components, potentially damaging them and causing a safety hazard.

[0084] To improve battery safety, some existing technologies propose incorporating a fusible wire near the heating wire of the heating film. This fusible wire is connected in parallel with the heating wire. As the heating film heats up during operation, the fusible wire's temperature rises accordingly until it reaches a preset temperature and melts, triggering an alarm signal from the heating film. While this method allows users to detect the heating film overheating promptly based on the alarm signal and take appropriate measures to prevent escalation, the heating film is already completely ineffective by the time it issues the alarm, severely impacting the battery system's performance and stability, and affecting the user experience. Furthermore, because the heating film is already overheated, a rapid user response is required, meaning the available response time is short.

[0085] Based on the above considerations, this application provides a battery management system, a heating film anomaly identification method, a battery pack, and electrical equipment, which can be used to identify and determine whether the heating film is abnormal. In the early stages of a fault, heating film anomalies often manifest as deviations in heating performance, but heating can still be achieved. This embodiment aims to detect anomalies in a timely manner when the heating film's operating state does not meet expectations due to incorrect resistor connection or ablation. By taking countermeasures, intervention can be made before the abnormal heating film deteriorates further and causes serious consequences, preventing complete loss of heating function, improving the performance and stability of the battery system, and providing users with more response time.

[0086] Based on the above ideas, this application provides a Battery Management System (BMS), which can be used, but is not limited to, in electrical equipment such as vehicles, ships, or aircraft, as well as in energy storage devices. The battery management system disclosed in this application can be used in the power system of such electrical equipment or energy storage device, which facilitates timely identification and determination of heating film abnormalities. Energy storage devices can be, but are not limited to, energy storage containers, energy storage cabinets, etc. Electrical equipment can be, but is not limited to, mobile phones, tablets, laptops, electric toys, power tools, electric vehicles, electric cars, ships, spacecraft, etc. Electric toys can include stationary or mobile electric toys, such as game consoles, electric car toys, electric ship toys, and electric airplane toys, etc. Spacecraft can include airplanes, rockets, space shuttles, and spacecraft, etc. For simplicity, the following embodiments all use electric vehicles as examples.

[0087] The battery management system is located in the battery apparatus. For ease of understanding, the battery circuitry of the battery apparatus will be described first below.

[0088] Figure 1 A simplified electrical schematic diagram of the battery circuit of the battery pack provided in the embodiments of this application under normal heating film conditions. (See attached diagram.) Figure 1 As shown, the battery circuit 10 of the battery pack includes a battery assembly 11 and a main circuit 12. The main circuit 12 includes a main positive circuit 121 and a main negative circuit 122. The positive terminal of the battery assembly 11 is connected to the load 13 through the main positive circuit 121, and the negative terminal of the battery assembly 11 is connected to the load 13 through the main negative circuit 122. A main positive switch K+ is provided on the main positive circuit 121, and a main negative switch K- is provided on the main negative circuit 122.

[0089] The battery circuit 10 also includes a heating circuit 14, which includes multiple heating films 141 arranged in parallel. One end of each heating film 141 is connected to the end of the main positive switch K+ furthest from the battery assembly 11, and the other end of each heating film 141 is connected to the end of the main negative switch K- furthest from the battery assembly 11, thus connecting the heating circuit 14 to the main circuit 12. Please refer to [reference needed]. Figure 1 The number of heating films 141 is two. The number of heating films 141 is not limited to two; it can also be three or more. In other words, the number of heating films 141 is N, where N is a positive integer, and N≥2. For ease of understanding, the following embodiments of this application will first be described exemplarily with two heating films 141.

[0090] The heating circuit 14 also includes a heating switch S1, such as Figure 1 As shown, one end of the plurality of heating films 141 is connected to the end of the main positive switch K+ away from the battery assembly 11 via a heating switch S1. The location of the heating switch S1 is not limited to this; for example, the other end of the plurality of heating films 141 is connected to the end of the main negative switch K- away from the battery assembly 11 via the heating switch S1. The heating switch S1 can be turned on and off, allowing the heating circuit 14 to switch between an on state and an off state. The main positive switch K+, the main negative switch K-, and the heating switch S1 can be, but are not limited to, relays, transistors, etc.

[0091] Combination Figure 1 It can be seen that, under normal conditions, all heating films 141 in the heating circuit 14 have four heating metal wires 1411, and the resistance of each heating metal wire 1411 is R. 膜 As an example, heating circuit 14 is in the off state and not energized, main positive switch K+ and main negative switch K- are closed, main circuit 12 is conducting, and the main circuit current value I is... 主 =V / R总 Where V is the voltage value of battery component 11, and R... 总 This is the total resistance of battery circuit 10. Figure 1 In the middle, R 总 Equal to the resistance R of load 13 负载 I 主 =V / R 负载 When heating of battery assembly 11 is required, heating switch S1 closes, heating circuit 14 switches from open to closed state, and the other switch states remain unchanged. 总 =(R 负载 *R 膜总 ) / R 负载 +R 膜总 I 主 =V(R) 负载 +R 膜总 ) / R 负载 *R 膜总 =V / R 膜总 +V / R 负载 Therefore, it can be deduced that when heating circuit 14 switches from the off state to the on state, the current in main circuit 12 increases, and the increment is V / R. 膜总 This refers to the total current value of the heating circuit 14. Under normal conditions, the equivalent resistance R of all the heating films 141 in the heating circuit 14 is... 膜总 =2R 膜 The total current of heating circuit 14 is V / 2R 膜 .

[0092] Figure 2 A simplified electrical schematic diagram of the battery circuit 10 of the battery pack provided in this application embodiment, in the case where one of the heating films 141 is burned off. Figure 2 As shown, when one of the heating films 141 is burned off, the equivalent resistance R of the heating circuit 14... 膜总 =4R 膜 The total current value of heating circuit 14 is V / 4R. 膜 The ablation of the heating film 141 refers to the damage to the heating film 141 caused by overheating, overload, or material aging, resulting in a decrease in its resistance performance or failure.

[0093] contrast Figure 1 The battery circuit 10 shown is Figure 2As shown in the battery circuit 10, under normal conditions and when one of the heating films 141 is burned out, after the heating circuit 14 switches from the off state to the on state, the current in the main circuit 12 increases, and the increment is the current value of the heating circuit 14 in the on state. This is because after the heating circuit 14 is turned on, the equivalent resistance of the heating circuit 14 and the resistance of the load 13 are combined into the total resistance of the main circuit 12, and the total resistance of the battery circuit 10 decreases. In addition, the heating branch to which the burned heating film 141 belongs is no longer conductive. Therefore, when one of the heating films 141 is burned out, the equivalent resistance of the heating circuit 14 is larger, and correspondingly, the total current value of the heating circuit 14 is smaller, and the current value of the main circuit is also smaller. Specifically, the ratio of the total current value of the heating circuit 14 when one of the heating films 141 is burned out to the total current value of the heating circuit 14 when the heating film 141 is normal is 1 / 2.

[0094] Figure 3 A simplified electrical schematic diagram of the battery circuit 10 of the battery pack provided in this application embodiment, in the case of incorrect connection of the two heating film resistors. (See attached diagram.) Figure 3 As shown, when the heating wires 1411 of the two heating films 141 in the heating circuit 14 are connected incorrectly, the number of heating wires 1411 in the two heating films 141 will be inconsistent, and their resistance values ​​will be inconsistent accordingly. Incorrect connection of heating film resistors refers to the inconsistent resistance of multiple heating films 141 connected in parallel to the same main circuit 12.

[0095] For example, the resistance of the heating film 141 having two heating wires 1411 is 2R. 膜 The heating film 141, which has six heating wires 1411, has a resistance of 6R. 膜 It is understandable that incorrect connection will cause uneven resistance between the two heating films 141, resulting in uneven current distribution between them. The heating film 141 with lower resistance will have a higher current, while the heating film 141 with higher resistance will have a lower current. In other words, the temperature rise rate of the two heating films 141 will be inconsistent, and the rate of increase of the highest temperature value of the battery module 11 will be significantly higher than the rate of increase of the lowest temperature value.

[0096] The battery management system includes a sampling circuit and a controller. The sampling circuit is used to collect the current of the main circuit 12, the highest temperature value of the battery assembly 11, and the lowest temperature value of the battery assembly 11. The controller is configured to: form a state dataset based on the data acquired by the sampling circuit at each time stamp; wherein the state dataset includes at least a time stamp and the highest temperature value, the lowest temperature value, and the main circuit current value corresponding to each time stamp; and identify and determine whether there is an abnormality in the heating film in the heating circuit based on the state dataset.

[0097] The sampling circuit can collect data in real time or at preset sampling intervals and report the collected data to the controller. This embodiment does not impose a specific limitation on the preset sampling interval, for example, it can be 1s, 2s, 3s, 5s, 10s, etc.

[0098] As an example, the sampling circuit may include a current detection circuit 15 for acquiring the current value of the main circuit. As an example, the current detection circuit 15 may also be replaced by a current sensor. As an example, the sampling circuit may include a temperature sensor array, consisting of multiple temperature sensors arranged at different locations on the battery assembly 11, each temperature sensor monitoring the temperature at different locations on the battery assembly 11. The temperature sensor array obtains a temperature matrix, where the maximum value in the temperature matrix is ​​the highest temperature value, and the minimum value in the temperature matrix is ​​the lowest temperature value.

[0099] The controller forms a state dataset based on the sampling data reported by the sampling circuit. The state dataset is a collection of data related to the state characteristics of the battery component 11. The state dataset can be presented in any form, but not limited to, tables (such as CSV, database tables), text, or graphical data. Figure 4 This is a schematic diagram illustrating the state dataset in tabular form for some embodiments of this application. The state dataset can be exemplarily referred to when presented in tabular form. Figure 4 As shown. The timestamp is used to indicate the moment when the sampling circuit collects the status information of battery assembly 11.

[0100] Based on the impact of the ablation and disconnection of the heating film 141 on the total current value and the main circuit current value of the heating circuit 14, the controller processes the current-related features of the main circuit 12 in the state data and observes the changes in the main circuit current value over different time periods. This allows the controller to identify and determine whether there is an abnormality in the heating film in the heating circuit, with the abnormality pattern being heating film ablation. Utilizing the characteristic that the rate of increase between the highest and lowest temperatures of the battery module 11 differs significantly when the heating film resistor is incorrectly connected, the controller processes the temperature-related features in the state data of the battery module 11 to analyze the resistance balance of multiple heating films 141. This allows the controller to identify and determine whether there is an abnormality in the heating film in the heating circuit, with the abnormality pattern being incorrect heating film resistor connection.

[0101] The battery management system of this embodiment collects the current of the main circuit 12, the highest temperature value of the battery component 11 and the lowest temperature value of the battery component 11 by designing a sampling circuit. It is also designed that the controller can form a status dataset based on the data collected by the sampling circuit. By processing and analyzing the status dataset, it can be used to identify whether there is a heating film resistor misconnection or heating film ablation in the heating circuit 14 with N heating films 141 arranged in parallel.

[0102] The ability to identify and diagnose heating film 141 abnormalities early in the stages of uneven temperature distribution in battery assembly 11 and overheating of heating film 141 enables fault prediction and early warning. This allows for timely intervention before the heating circuit completely fails, reducing the risk of further deterioration of heating film 141 abnormalities and serious consequences, thus improving the reliability and safety of the battery pack. Furthermore, this provides users with more response time.

[0103] Compared to the approach of adding a fusible wire to the heating film 141 to diagnose faults, the method of this embodiment identifies and diagnoses whether multiple heating films 141 in the heating circuit 14 are abnormal by analyzing the state data set of the battery assembly 11, without the need for additional fusible wires, thus eliminating the negative impact of adding fusible wires on the cost of the heating film 141. Furthermore, since the method of this embodiment does not rely on fusible wires, it has good practical compatibility and wide applicability, and can be applied to battery packs that have already been manufactured and whose heating films 141 do not have fusible wires; that is, this method can be applied to various types of battery packs.

[0104] According to some embodiments of this application, the controller is configured to: determine the highest and lowest temperature rise rates of the heating circuit 14 during each heating time period based on a state dataset; determine whether the highest and lowest temperature rise rates meet preset conditions, and if so, determine that the abnormal mode is a heating film resistor misconnection; wherein the heating circuit 14 remains in a closed state during the heating time period.

[0105] The heating time period refers to the time interval during which the heating switch S1 is closed, the heating circuit 14 is in a closed state, and the heating film 141 on the heating circuit 14 is working. (In the state dataset such as...) Figure 4 As shown, the time period between the timestamps corresponding to A1 and A7 is the heating period. Therefore, during the heating period, current flows through the uninterrupted heating film 141, causing the battery assembly 11 to heat up. During battery pack operation, whenever the temperature of the battery assembly 11 fluctuates due to ambient temperature or other factors and fails to reach its optimal operating temperature, the heating switch S1 closes to initiate heating, thus creating multiple heating periods.

[0106] The maximum temperature rise rate refers to the rate at which the maximum temperature value of the battery module 11 changes over time, reflecting how quickly the maximum temperature value of the battery module 11 rises. The minimum temperature rise rate refers to the rate at which the minimum temperature value of the battery module 11 changes over time, reflecting how quickly the minimum temperature value of the battery module 11 rises.

[0107] The battery management system in this embodiment analyzes the difference between the highest and lowest temperature rise rates to determine the resistance balance of multiple heating films 141. When the resistance of the multiple heating films 141 is uneven, it can be determined that there is an abnormality in the heating film 141, and the abnormality mode is incorrect connection of the heating film resistor. This allows for timely detection and correction of incorrect heating film resistor connection, providing early warning of uneven temperature in the battery module 11 and reducing damage caused by uneven temperature in the battery module 11 (e.g., thermal runaway due to localized overheating of the battery module 11).

[0108] According to some embodiments of this application, please continue to refer to Figure 4 The sampling circuit can also be used to collect the on / off state of the heating circuit. The state dataset can also include a first identifier corresponding to each timestamp, which is used to indicate the on / off state of the heating circuit 14.

[0109] The controller can also be configured to be used for:

[0110] Extract K consecutive data points from the state dataset that are located between two adjacent non-heating state data points and whose first identifier indicates that the heating circuit 14 is in the on state, to obtain the data set for each heating time period, where K is a positive integer greater than or equal to 2; wherein, the first identifier of the non-heating state data indicates that the heating circuit 14 is in the off state.

[0111] For each heating time period, determine the highest and lowest temperature rise rates for that heating time period.

[0112] The sampling circuit may include a relay status detector for detecting the on / off state of the heating circuit. Alternatively, the relay status detector may be replaced with a Hall sensor.

[0113] As an example, the first identifier can be the switching signal of heating switch S1, which can be either 0 or 1. Please continue reading. Figure 4 When the first flag is 1, it indicates that the heating switch S1 is closed, the heating circuit 14 is in the on state, and the battery assembly 11 is being heated. When the first flag is 0, it indicates that the heating switch S1 is open, the heating circuit 14 is in the off state, and heating is stopped. As an example, the first flag can also be a pulse width modulation (PWM) signal.

[0114] For example, a state dataset such as Figure 4In the scenario shown, the data containing A1, A7, A8, A12, A17, and A22 are all in a non-heated state. Since the data containing A1 and A7 are two adjacent non-heated data sets, the five consecutive data sets between them (i.e., the data containing A2 through A6) form a data set for a heating period. For similar reasons, the data containing A9 through A11, A13 through A16, and A18 through A21 can also form a data set for a heating period.

[0115] In other words, the first timestamp when the first identifier changes from 0 to 1 is taken as the start time of the heating period, and the first timestamp when the adjacent first identifier changes from 1 to 0 is taken as the end time of the heating period. The change of the first identifier from 0 to 1 means that the heating circuit 14 changes from an off state to an on state.

[0116] K is related to the methods used to determine the highest and lowest temperature rise rates.

[0117] This embodiment includes a first identifier in the status dataset, which indicates the on / off state of the heating circuit 14. This allows for the accurate extraction and analysis of the highest and lowest temperature values ​​during the heating period. This ensures that when analyzing the difference between the highest and lowest temperature rise rates to diagnose whether the heating film resistor is incorrectly connected, it is not affected by non-heating status data, thus improving the accuracy of anomaly diagnosis.

[0118] There are various ways to determine the maximum and minimum temperature rise rates during a heating period. In some exemplary embodiments, the controller can be specifically configured to: calculate the instantaneous temperature rise rate of the highest temperature and the instantaneous temperature rise rate of the lowest temperature between two adjacent timestamps in the heating period, for the highest and lowest temperature values ​​contained in the data set of each heating period; then take the average of all the instantaneous temperature rise rates of the highest temperature as the maximum temperature rise rate, and take the average of all the instantaneous temperature rise rates of the lowest temperature as the minimum temperature rise rate. It is understood that in this method, K is at least 3, meaning that when there are at least three consecutive data points between two adjacent non-heating state data points and the first identifier indicates that the heating circuit 14 is in the on-state, this data is extracted as the data set for the heating period for further analysis and processing. The method for determining the maximum and minimum temperature rise rates in this embodiment is simple.

[0119] According to some embodiments of this application, the controller can be specifically configured to: process the highest and lowest temperature values ​​contained in the data set for each heating time period based on temperature analysis steps to obtain the highest temperature rise rate and the lowest temperature rise rate.

[0120] The temperature analysis step is implemented using the following steps: S11, determine the instantaneous temperature rise rate during the heating period. S12, analyze the instantaneous temperature rise rate based on the sliding window method and calculate the average value within each sliding window. S13, calculate the average value of all sliding windows. The window size of the sliding window is M, M+2≤K, where M is a positive integer greater than or equal to 2.

[0121] The instantaneous temperature rise rate characterizes the amount of temperature change per unit time. In this paper, the controller can implement S11 using either the first-order difference method or the derivative method. Taking the instantaneous temperature rise rate for determining the highest temperature value as an example, the process of implementing S11 using the first-order difference method is as follows: calculate the difference between the highest temperature values ​​corresponding to two adjacent time stamps within the heating time period, and then take the ratio of this difference to the time difference between the two time stamps, which is the instantaneous temperature rise rate of the highest temperature value. Under normal circumstances, the ratio of the time difference between the two time stamps mentioned here is the preset sampling period. Combined with... Figure 4 The state dataset shown is provided as an example; please refer to [reference needed]. Figure 5 The instantaneous temperature rise rate for the heating time periods corresponding to A2 to A6 is calculated as follows: the difference between T3max and T2max is divided by the preset sampling period ΔT. This calculation process is then used to calculate the instantaneous temperature rise rate of the highest temperature value corresponding to the other two adjacent time stamps. Thus, four results (i.e., the instantaneous temperature rise rate of the highest temperature value) can be calculated from the five sets of data for the heating time periods corresponding to A2 to A6. Step S12 then analyzes these four results.

[0122] As an example, the process of implementing S11 using the derivative method is as follows: based on the timestamps of the heating time period and the corresponding highest temperature value, a highest temperature function is fitted, and then the derivative of the highest temperature function is taken to obtain the instantaneous temperature rise rate. In comparison, the first-order difference method is computationally simpler and can still effectively calculate the instantaneous temperature rise rate even with a small amount of time series data. In other words, the first-order difference method can provide reasonable calculations with a limited sample size. This allows for the reasonable calculation of the instantaneous temperature rise rate even when the data satisfying the heating time period condition is the minimum value of K.

[0123] In step S12, a sliding window is established, and the average value within the sliding window is taken. It can be understood that K in this method is related to the window size M of the sliding window, with K being at least M+2. When the window size is 2, K is at least 4. When the window size is 2, K is at least 5. That is, the larger the window size, the larger the amount of data corresponding to the heating time period.

[0124] Continue to combine Figure 4 and Figure 5 The five sets of data corresponding to the heating time periods A2 to A6 can be used to calculate four instantaneous temperature rise rates using the first-order difference method. Sliding windows are established for these four instantaneous temperature rise rates. When the window size is 3, the number of windows is 2. The first window includes the three instantaneous temperature rise rates with the earlier timestamps, and the second window includes the three instantaneous temperature rise rates with the later timestamps. The average value of the two sliding windows is then calculated.

[0125] This embodiment determines the instantaneous temperature rise rate and then uses the sliding window method to analyze the instantaneous temperature rise rate. This allows for smoothing of the instantaneous temperature rise rate through the sliding window, which helps to eliminate noise and improve the accuracy of the analysis.

[0126] When using the first-order difference method to calculate the instantaneous temperature rise rate, this embodiment remains applicable even when the sample size for the heating time period is small, reducing dependence on the amount of data. This allows for the diagnosis of incorrect heating film resistance connection by analyzing the difference between the highest and lowest temperature rise rates, even when there is limited data in the acquired state dataset that meets the heating time period condition, thus improving the sensitivity of anomaly identification.

[0127] As an alternative embodiment of this application, the data set of the heating time period can also be input into the trained model used to fit the temperature data.

[0128] According to some embodiments of this application, the preset condition can be one of the following conditions:

[0129] The highest temperature rise rate is greater than or equal to the first threshold value, and the lowest temperature rise rate is less than or equal to the second threshold value. The second threshold value is a non-negative number and is less than the first threshold value.

[0130] The difference between the highest temperature rise rate and the lowest temperature rise rate is greater than the third threshold value, the third threshold value is less than the difference between the first threshold value and the second threshold value, and the third threshold value is close to the first threshold value.

[0131] As an example, the preset condition can be that the highest temperature rise rate is greater than or equal to a first threshold value, and the lowest temperature rise rate is less than or equal to a second threshold value. When this preset condition is met, it means that the rate of increase of the highest temperature value of the battery module 11 is too high, while the lowest temperature value no longer rises or even shows a decreasing trend, indicating a severe temperature imbalance in the battery module 11. The first threshold value is a threshold indicating that the rate of increase of the highest temperature value of the battery module 11 is too high. Its value range can be reasonably designed according to actual operating conditions and experience. For example, any value between 1.6℃ / min and 2℃ / min can be selected, specifically any value among 1.6℃ / min, 1.8℃ / min, and 2℃ / min. The second threshold value can be any value among 0.2℃ / min, 0.15℃ / min, and 0℃ / min.

[0132] As an example, the preset condition can also be that the difference between the highest temperature rise rate and the lowest temperature rise rate is greater than a third threshold value. When this preset condition is met, it means that the lowest temperature rise rate of the battery module 11 is less than the first threshold value and greater than the second threshold value, but the difference between the highest temperature rise rate and the lowest temperature rise rate is too large, the rate of increase of the lowest temperature value slows down, and the temperature of the battery module 11 is severely uneven. When the first threshold value is in the range of [1.6℃ / min, 2℃ / min] and the second threshold value is 0℃ / min, without violating the condition that the third threshold value is less than the difference between the first and second threshold values, the value range of the third threshold value can be [1.3℃ / min, 1.7℃ / min]. Specifically, any value among 1.3℃ / min, 1.5℃ / min, and 1.7℃ / min can be selected.

[0133] As described above, when the heating film resistors are connected incorrectly, the current distribution of the two heating films 141 with unequal resistance values ​​is uneven, and the temperature rise rates of the two heating films 141 show different trends; the heating film 141 with a smaller resistance value has a higher temperature rise rate than the heating film 141 with a larger resistance value. Based on this, this embodiment is designed such that, when the preset conditions are met, a large difference between the rate of increase of the highest temperature value and the rate of increase of the highest temperature value indicates that the resistance of the heating film 141 in the heating circuit 14 is uneven, which can be used to accurately diagnose incorrect heating film resistor connections.

[0134] According to some embodiments of this application, the controller is configured to: determine a heating current value based on a state dataset, wherein the heating current value is the total current value of the heating circuit 14 and is related to the main circuit current value; analyze and process a first data group formed by heating current values ​​belonging to historical time periods and their associated timestamps and a second data group formed by heating current values ​​belonging to the latest time period and their associated timestamps to determine whether a first failure condition is met; if the first failure condition is met, determine that the heating film 141 in the heating circuit 14 is abnormal and the abnormal mode is heating film 141 ablation; wherein the first failure condition is that the heating current value in the second data group is reduced by i / N compared to the heating current value in the first data group, 1≤i<N, where i is a positive integer. That is, i=1,2,3,4,...,N-1.

[0135] When heating switch S1 is closed and heating circuit 14 is in the on state, the heating current value is equal to the ratio of the voltage of battery assembly 11 to the equivalent resistance of heating circuit 14. Based on the above, assuming other switching states of battery circuit 10 remain unchanged, the difference between the main circuit current value when heating circuit 14 is in the on state and the main circuit current value when heating circuit 14 is in the off state is equal to the heating current value. When the heating current value in the second data group is reduced by i / N compared to the heating current value in the first data group, the number of heating films 141 that undergo ablation is correspondingly i.

[0136] This embodiment utilizes the characteristic of the impact of the ablation and disconnection of the heating film 141 on the total current value and the main circuit current value of the heating circuit 14. By processing the current-related features of the state data concentrated in the main circuit 12, the changes in the main circuit current value in different time periods are observed. When the current value in the latest time period is lower than i / N of the current value in the historical time period, where 1≤i<N, and the change range persists for a certain period of time, it can be determined that there is an anomaly in the heating film 141, and the anomaly mode is the ablation of some of the heating films 141. This can provide early warning of overheating of the heating film 141, which is conducive to timely detection and remediation of the ablation of the heating film 141. This not only reduces the damage caused by the overheating of the heating film 141, but also ensures that the heating circuit 14 is not completely failed (Ni heating films 141 are still not disconnected due to ablation), that is, the heating circuit 14 has not lost its heating capacity and can still heat the battery assembly 11, which helps to keep the battery assembly 11 at the optimal operating temperature and have better performance.

[0137] It should also be understood that those skilled in the art would readily conceive of designing the sampling circuit to include multiple ammeters corresponding one-to-one with the multiple heating branches, directly collecting the heating current value using the ammeters. However, this would introduce multiple ammeters, occupying installation space in the battery assembly 11 and affecting the energy density of the battery pack. In contrast, this embodiment designs a sampling circuit to collect the current value of the main circuit 12, and then analyzes and processes the current value of the main circuit 12 to obtain the heating current value. This reduces the hardware cost and system complexity of the battery pack, and the hardware occupies less space, which is beneficial for improving energy density.

[0138] It should be noted that possible causes of incorrect heating film resistor connection include, for example, incorrect wiring of the heating wire 1411 during the installation of the heating circuit 14. In this case, based on the data collected by the sampling circuit during the initial operation of the battery pack's equipment, if the highest and lowest temperature rise rates meet preset conditions, the incorrect heating film resistor connection can be determined, and the user can correct this anomaly during the initial operation of the equipment. As another example, a possible cause of incorrect heating film resistor connection is a wiring error during maintenance after the battery pack's equipment has been running for a period of time. In this case, after maintenance, based on the data collected by the sampling circuit during the re-operation of the battery pack's equipment, the incorrect heating film resistor connection can be determined, and the user can then correct it. Therefore, it is evident that both newly manufactured battery packs and battery packs that have been running for a period of time may have incorrect heating film resistor connection.

[0139] It should be understood that incorrect connection of the heating film resistor can immediately cause uneven current and temperature rise differences among the multiple heating films 141 with incorrectly connected resistors. The difference between the highest and lowest temperature rise rates can be quickly observed. However, when part of the heating film 141 is ablated, the equivalent resistance of the heating circuit 14 increases, the total current decreases, and the temperature rise rate slows down. Furthermore, since the effect of ablation on temperature is gradual, the decreasing trend in the temperature rise rate takes longer to manifest. In other words, the number of samples in the state dataset required to determine that the anomaly mode is incorrect connection of the heating film resistor is less than the number of samples in the state dataset required to determine that the anomaly mode is partial ablation of the heating film 141. In view of this, when the heating circuit 14 has both the abnormality of incorrect heating film resistor connection and partial heating film 141 burning, the abnormality mode can be identified as incorrect heating film resistor connection more quickly. The user can then make corrections to make the equivalent resistance of each heating film 141 consistent. After the battery assembly 11 restarts, the abnormality mode of partial heating film 141 burning can be identified again. Since the abnormality of incorrect heating film resistor connection has been corrected, the process of diagnosing the abnormality mode of partial heating film 141 burning is not disturbed, and the diagnosis result is accurate.

[0140] According to some embodiments of this application, when the sampling circuit is also used to collect the on / off state of the heating circuit and the state dataset also includes a first identifier, the controller can be configured to: extract two adjacent data with different first identifiers from the state dataset, and determine the difference between the main circuit current value after the first identifier changes and the main circuit current value before the first identifier changes in the two data as the heating current value.

[0141] Please continue to refer to this. Figure 4 The first identifier is either 1 or 0. Two adjacent data points with different first identifiers can be understood as the data points before and after the first identifier changes from 0 to 1, such as the data corresponding to A1 and the data corresponding to A2. Alternatively, two adjacent data points with different first identifiers can also be understood as the data points before and after the first identifier changes from 1 to 0, such as the data corresponding to A6 and the data corresponding to A7. The first identifier is used to indicate the on / off state of the heating circuit 14. Therefore, the difference in the main circuit current value before and after the heating circuit 14 is turned on or off is the heating current value. In other words, the difference in the main circuit current value before and after the heating switch S1 is turned on or off is the heating current value.

[0142] Figure 6 This is a schematic diagram illustrating the extraction of heating current values ​​according to some embodiments of this application. Please refer to... Figure 4 and Figure 6 ,from Figure 4 The following heating current values ​​can be extracted from the state dataset shown: A2-A1, A7-A6, A9-A8, A12-A11, A13-A12, A17-A16, A18-A17, A22-A21, A23-A22.

[0143] This embodiment collects the on / off state of the heating circuit, making the state dataset include a first identifier. The first identifier serves as an indication of the operating state of the heating circuit 14, intuitively reflecting its on / off state. As mentioned earlier, when the heating circuit 14 switches from an off state to an on state, the current in the main circuit 12 increases, and the increment is the heating current value. Therefore, by calculating the difference in the main circuit current value before and after the heating circuit 14 is switched on and off, the current value of the heating circuit 14 can be accurately extracted. This eliminates the need for additional hardware such as sensors to independently detect the heating current value, reducing system complexity and hardware costs.

[0144] According to some embodiments of this application, the controller can be specifically configured to:

[0145] The heating current values ​​that meet the outlier selection criteria are filtered out to obtain the filtered dataset. The outlier selection criteria include at least one of the following:

[0146] The heating current value is less than 0A;

[0147] The time interval between the two data points corresponding to the heating current value exceeds the preset duration.

[0148] The second identifiers of the two data points corresponding to the heating current values ​​are different;

[0149] The first data group, consisting of heating current values ​​belonging to historical time periods and their associated timestamps, and the second data group, consisting of heating current values ​​belonging to the most recent time period and their associated timestamps, are analyzed and processed.

[0150] In this example, the battery circuit 10 also includes Q power branches belonging to load elements. The load elements are connected in parallel with the heating film 141. The power branches can switch between a conducting state and a cut-off state. The sampling circuit can also be used to collect the on / off state of the power branches. The state dataset also includes Q second identifiers corresponding to each timestamp. The Q second identifiers correspond one-to-one with the Q power branches, and the second identifiers are used to indicate the on / off state of the corresponding power branch. Here, Q is a positive integer.

[0151] To collect the on / off status of the electrical branch, the sampling circuit may also include a switch status detector. Filtering the status dataset to obtain a filtered dataset removes noise, allowing subsequent analysis and processing to better focus on the changing trends of the heating current value.

[0152] When heating circuit 14 is in the off state, the heating current is 0A. When heating circuit 14 is in the on state, current flows to heating film 141, and the heating current is greater than 0A. A heating current less than 0A means that heating circuit 14 is malfunctioning.

[0153] The time interval between two data points corresponding to the heating current value exceeds the preset duration, meaning the difference in timestamps between two adjacent data points with different on / off states of the heating circuit 14 used to calculate the heating current value exceeds the preset duration. In the case where the state dataset includes a first identifier, this means the time difference between two adjacent data points with different first identifiers exceeds the preset duration. The preset duration is a threshold characterizing whether the interval between two adjacent data points with different first identifiers is regular. If the preset duration is longer than the preset sampling period, it means the time difference between two adjacent data points with different first identifiers does not conform to the preset sampling period, which may easily lead to other unacquired data between the extracted adjacent data points with different first identifiers. For example, if the preset sampling period is 10s, the preset duration can range from [15s, 50s], and can specifically be any value from 15s, 20s, 30s, 40s, or 50s.

[0154] For example, using a state dataset such as Figure 4 As shown in the example, Figure 6As shown, the preset sampling period is 1 minute. The actual interval between the two data points corresponding to the heating current values ​​A9-A8 is 4 minutes, which is much longer than the preset sampling period. This meets the criteria for selecting abnormal data and is therefore rejected.

[0155] The battery circuit 10 may also include a load element. One end of the load element can be connected to the other end of the main positive switch K+ via a control switch, and the other end can be connected to the other end of the main negative switch K-. The battery assembly 11 provides current to the load element, that is, the load element is connected to the main circuit 12. The control switch is used to control the on / off state of the power supply branch to which the load element belongs. After the power supply branch to which the load element belongs switches from the off state to the on state, the current value of the main circuit will also change, specifically by increasing.

[0156] The second indicator can be designed with reference to the first indicator, and can be either 0 or 1. When the second indicator is 1, it indicates that the control switch is closed and the power supply branch is in a conductive state. When the second indicator is 0, it indicates that the control switch is open and the power supply branch is in a disconnected state.

[0157] For example, using a state dataset such as Figure 4 As shown in the example, Figure 6 As shown, the two data points corresponding to heating current values ​​A12-A11 have different second identifiers, which meets the criteria for selecting abnormal data, and therefore they are removed. Similarly, heating current values ​​A17-A16 and A18-A17 can also be removed. The two data points corresponding to heating current values ​​A2-A1 both have a second identifier of 0, and the two data points corresponding to heating current values ​​A13-A12 both have a second identifier of 1, which does not meet the condition of different second identifiers.

[0158] In this paper, the heating current value and its associated timestamp can refer to the first timestamp of the two data points corresponding to the heating current value. Alternatively, the heating current value can also refer to the second timestamp of the two data points corresponding to the heating current value. For example, the timestamps corresponding to the heating current values ​​A2-A1 and A2 form a set.

[0159] This embodiment is designed to remove heating current values ​​less than 0A, thus avoiding the retention of heating current values ​​less than 0A and the introduction of errors into the filtered dataset. This reduces the negative impact of erroneous data caused by battery component instability on the accuracy of judging the ablation of heating film 141, and helps to improve the reliability and accuracy of abnormal identification of heating film 141.

[0160] This embodiment is designed in such a way that it can also remove two data points with a long time interval between them corresponding to the heating current value, thereby reducing the possibility of data discontinuity caused by long time intervals and resulting in incorrect analysis. This helps to improve the continuity of data, reduce the analysis deviation caused by irregular sampling intervals, and make the abnormal identification accuracy of heating film 141 higher.

[0161] This embodiment is designed in such a way that if the second identifiers of the two data corresponding to the heating current value are different, they can be eliminated, so that the main circuit current value of the two data will not be affected by the opening and closing of the power supply branch. This makes the equivalent resistance of the heating circuit 14 the only variable affecting the main circuit current value. This can improve the accuracy of the heating current value calculated based on the difference between the main circuit current value before and after the heating circuit 14 is turned on and off, and thus help to improve the accuracy of subsequent analysis.

[0162] By removing data that meets the abnormal data conditions, the amount of data in the filtered dataset is reduced. This also reduces the amount of data that the controller needs to process when analyzing the filtered dataset, making the subsequent analysis and diagnosis process more efficient.

[0163] According to some embodiments of this application, the controller can also be configured to:

[0164] Data that meets the target data selection criteria are filtered from the state dataset to obtain a preprocessed dataset. The target data selection criteria are used to indicate that the battery assembly 11 is in a charging state.

[0165] The heating current value is determined based on the preprocessed dataset.

[0166] In other words, data indicating that the battery assembly 11 is in a charging state is extracted from the state dataset, which serves as the basis for diagnosing whether the heating film 141 has been burned. Taking an electric vehicle as an example, the electric vehicle is in a discharging state during driving. During this process, the load 13 changes frequently, and the generated data involves the current fluctuations of multiple electrical components such as the load 13 and load elements. The current changes are complex and may interfere with the analysis of the heating current value.

[0167] This embodiment analyzes data from the charging state. Compared to the discharging state data, the charging state data is more stable and has less interference, and can more clearly reflect the changes in the heating current value, which is beneficial to improving the accuracy of detecting ablation anomalies in the heating film 141.

[0168] According to some embodiments of this application, the sampling circuit can also be used to collect the charge and discharge state of the battery assembly, such as... Figure 4 and Figure 6 As shown, the state dataset may also include a third identifier corresponding to each timestamp, which indicates the charge / discharge state of the battery assembly 11. Target data selection criteria may include at least one of the following: the main circuit current value is negative; the third identifier indicates that the battery assembly 11 is in a charging state.

[0169] To collect the charge and discharge status of the battery assembly, the sampling circuit may specifically include voltage sensors and power sensors, etc.

[0170] Taking an electric vehicle as an example, when the electric vehicle is charging, it is connected to the power grid, and the power grid provides current to the battery pack 11. At this time, the battery pack 11 is the current receiver, and the current flows stably to the battery pack 11. Therefore, the main circuit current value is negative. Based on this principle, data with a negative main circuit current value is determined to be data generated when the battery pack 11 is charging, and data with a positive main circuit current value is removed.

[0171] The third identifier can be, for example, a charging state or a discharging state. Alternatively, similar to the first identifier, the third identifier can also be 0 or 1. When the third identifier is 1, it indicates that the battery assembly 11 is in a charging state. When the third identifier is 0, it indicates that the battery assembly 11 is in a discharging state.

[0172] For example, in a state dataset such as Figure 4 In the case shown, data with the third identifier of 1 can be filtered out to form a preprocessed dataset, while data with the third identifier of 0 can be filtered out.

[0173] This embodiment can filter data indicating that the battery module 11 is in a charging state based on the negative value of the main circuit current. This filtering method is simple, direct, highly automated, and does not rely on complex logic. This embodiment can also filter based on a third identifier, which can help to clearly and accurately filter data indicating that the battery module 11 is in a charging state, reducing the possibility of false filtering.

[0174] According to some embodiments of this application, the controller can be specifically configured to: perform cluster analysis on a first data group and a second data group based on a clustering algorithm; determine whether multiple subsets are formed, and the heating current value of the subset corresponding to the second data group is reduced by i / N compared with the heating current value of the subset corresponding to the first data group.

[0175] Clustering algorithms are data analysis methods used for unsupervised learning, which divide data into several groups. For example, but not limited to, any of the following algorithms can be used to perform clustering analysis on the first and second data groups: K-means clustering, density-based spatial clustering of applications with noise (DBSCAN), hierarchical clustering, etc.

[0176] As an example, DBSCAN is used to perform two-dimensional clustering analysis on the timestamp and heating current values ​​in the first and second data groups. The analysis then determines whether the clustering results form two subsets, and whether the heating current value of the subset corresponding to the second data group is reduced by i / N compared to the heating current value of the subset corresponding to the first data group. In other words, the heating current value of the cluster corresponding to the most recent time period is reduced by i / N compared to the heating current value of the cluster corresponding to the historical time periods. The clustering analysis results can also be visualized into charts. Figure 7 This is a schematic diagram showing the clustering analysis results corresponding to some embodiments of this application. Figure 7 In the diagram, the clusters circled by double dots represent the heating current values ​​for the latest time period, while the clusters circled by dashed lines represent the heating current values ​​for historical time periods. The heating current value of the clusters corresponding to the latest time period is half that of the clusters corresponding to historical time periods.

[0177] In this article, subset, cluster, and cluster group can be used interchangeably. A cluster group refers to a group of similar data points that are grouped into the same group or cluster based on some feature or metric.

[0178] In contrast, using DBSCAN for cluster analysis eliminates the need to pre-specify the number of clusters and can discover clusters of arbitrary shapes. Thus, even if the resulting clusters are complex, anomaly identification can still be performed based on the DBSCAN cluster analysis results, improving the operational reliability of the method in this embodiment.

[0179] As an example, machine learning algorithms can also be used to train a model based on historical data. This trained model can then be used to determine whether the heating current value in the latest time period is abnormal, thereby identifying whether there is partial ablation of the heating film 141. As another example, a time series model can be built based on historical data for analysis.

[0180] Compared to analysis using trained models or time series models, this embodiment uses a clustering algorithm to process the first and second data groups, dividing the data into multiple subsets based on features or patterns. This helps identify whether the heating current values ​​of the subsets corresponding to the second data group are normal compared to the heating current values ​​of the subsets corresponding to the first data group, thereby determining whether the first failure condition is met. In this way, no prior labeling or training of the data is required; only the processed data needs to be input. Clustering algorithms can handle large-scale datasets, allowing for the rapid identification of ablation anomalies from a large amount of data.

[0181] According to some embodiments of this application, the controller can be configured to:

[0182] If the first failure condition is met, continue to determine whether the second failure condition is met. The second failure condition is that the rate of increase of at least one of the highest and lowest temperature values ​​of the heating time period to which the timestamp in the second data group belongs gradually decreases.

[0183] If the second failure condition is met, the abnormal mode is determined to be ablation of the heating film 141.

[0184] If the second failure condition is not met, it is determined that the heating film 141 has not been ablated.

[0185] In other words, under the premise of meeting the first failure condition, the temperature change during the corresponding heating period is further analyzed. When the highest and / or lowest temperature values ​​during the corresponding heating period change in a decreasing manner, it is determined that the heating film 141 is ablated. This is because the current of the heating film 141 is directly related to its heating capacity. Partial ablation of the heating film 141 will reduce the total heating power consumption of the heating circuit 14, decrease the heating capacity, and slow down the temperature rise rate of the unablated heating film 141, thus directly affecting the temperature rise of the battery module 11.

[0186] In the second data set, the second timestamp of the two data points corresponding to the heating current value is the start time of the heating period. The system determines whether the rate of increase of the highest and lowest temperature values ​​during this heating period is decreasing. For example, the state dataset is presented as follows: Figure 4 As shown, the starting time of the heating time period to which the heating current value A2-A1 belongs is the timestamp corresponding to A2. Therefore, the heating time period to which the heating current value A2-A1 belongs is the time period between the timestamp corresponding to A2 and the timestamp corresponding to A6.

[0187] Compared to relying solely on changes in heating current value to analyze and diagnose the erosion of the heating film 141, this embodiment is designed to combine the heating current value condition and the battery component 11 temperature condition to comprehensively analyze and determine whether there is partial erosion of the heating film 141. This can eliminate the interference of external factors (such as system load fluctuations, battery state changes, etc.) on the heating current value, thereby facilitating a more accurate determination of whether there is partial erosion of the heating film 141, avoiding errors caused by external factors affecting the heating current value and thus improving system stability.

[0188] According to some embodiments of this application, the second failure condition can be specifically configured such that the lowest temperature rise rate of the heating time period to which the timestamp in the second data group belongs is less than 0°C / min.

[0189] A minimum temperature rise rate of less than 0℃ / min means that the rate of increase of the minimum temperature value during the heating period is less than 0℃ / min, i.e., the minimum temperature value decays. It can be understood that the function of the heating film 141 is to heat the battery module 11 or its surrounding environment. The heating effect of the heating film 141 is typically transferred gradually outward from the heat source. The highest temperature region of the battery module 11 is closer to the heating film 141, while the lowest temperature region is farther from the heat source. During heat conduction, the temperature change in the lowest temperature region usually lags behind other regions. Therefore, the ablation of the heating film 141 has a smaller impact on the temperature rise rate of the highest temperature region but a larger impact on the temperature rise rate of the lowest temperature region, resulting in a significant slowdown or even decay in the temperature of the lowest temperature region. In other words, in the case of heating film 141 ablation, the lowest temperature region of the battery module 11 is more sensitive.

[0190] In this embodiment, the temperature rise rate of the lowest temperature region is less than 0°C / min as an indicator for judging the ablation of the heating film 141. By focusing on the lowest temperature rise rate, signs of ablation of the heating film 141 can be detected earlier and more accurately. By taking timely measures, further damage to the battery system caused by the ablation of the heating film 141 can be avoided.

[0191] Based on the same inventive concept, this application also provides a heating film anomaly identification method, which is applied to the controller of the battery management system described above. Figure 8 This is a flowchart illustrating a heating film anomaly identification method provided in some embodiments of this application, such as... Figure 8 As shown, the heating film anomaly identification method includes the following steps.

[0192] S21, acquire sampling data.

[0193] S22, form a state dataset based on the sampled data at each timestamp; wherein, the state dataset includes at least the timestamp and the highest temperature value, lowest temperature value and main circuit current value corresponding to each timestamp.

[0194] S23, Based on the status dataset, identify and determine whether there is an abnormality in the heating film in the heating circuit.

[0195] In S21, the sampling data is the data collected by the sampling circuit. The sampling data includes at least the highest temperature value of the battery pack, the lowest temperature value of the battery pack, and the main circuit current value.

[0196] Based on the same inventive concept, this application also provides a battery pack, which includes a battery assembly, a main circuit, a heating circuit, and the battery management system described in the above embodiments. The main circuit has a main positive circuit and a main negative circuit. One end of the main positive circuit is connected to the positive terminal of the battery assembly, and one end of the main negative circuit is connected to the negative terminal of the battery assembly. The heating circuit includes N heating films arranged in parallel. One end of each of the N heating films is connected to one of the main positive circuit and the main negative circuit via a heating switch, and the other end is connected to the other of the main positive circuit and the main negative circuit. The heating switch can be turned on and off, allowing the heating circuit to switch between an on / off state.

[0197] The battery assembly 11 is connected to the load 13 via the main circuit 12. The load 13 can refer to the load 13 in the electrical equipment to which the battery pack belongs. This embodiment does not impose specific limitations on the number and resistance value of the heating wires 1411 in the heating film 141. Exemplarily, the heating branch to which the heating film 141 belongs may also include other devices, such as fuses.

[0198] The battery pack may include one or more battery components 11 for providing voltage and capacity. Battery component 11 may include a single battery cell or multiple battery cells connected in series via a busbar. As an example, battery component 11 may be formed by arranging multiple battery cells and securing them together with cable ties or similar means to create a single module. As an example, battery component 11 may also be housed within a housing. Exemplarily, battery component 11 may be housed within a housing by directly securing it to the housing, or by directly securing multiple battery cells to the housing. The housing may be part of the vehicle's chassis structure, for example, at least a portion of the vehicle's floor or at least a portion of the vehicle's crossbeams and longitudinal beams.

[0199] In some embodiments, the battery assembly 11 can also be connected to a load element in the electrical device to which the battery pack belongs via the main circuit 12. The load element is connected in parallel with the heating film, and there are Q load elements. For example, the electrical device is an electric vehicle, and the load 13 and load elements can be, but are not limited to, a power conversion system (PCS), a drive motor, an air conditioning system, a lighting system, a signal system, etc.

[0200] Based on the same inventive concept, this application also provides an electrical device, which includes the battery pack described in the above embodiments. As mentioned above, the electrical device may be, but is not limited to, vehicles, ships, aircraft, etc.

[0201] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.

[0202] A specific embodiment of this application is described below. It should be understood that this specific embodiment is described for illustrative purposes only and should not be construed as limiting the scope of this application.

[0203] The battery pack includes a battery assembly 11, a main circuit 12, and a battery management system. The battery assembly 11 is connected to a load 13 via the main circuit 12. The battery circuit 10 also includes a heating circuit 14, which comprises two heating films 141 connected in parallel. One end of each heating film 141 is connected between the main positive switch K+ of the main circuit 12 and the load 13, and the other end is connected between the main negative switch K- of the main circuit 12 and the load 13. The heating circuit 14 can switch between an on / off state and an off state. The battery management system includes a sampling circuit and a controller. The sampling circuit collects the current of the main circuit, the highest temperature value of the battery assembly, and the lowest temperature value of the battery assembly. The controller can execute a heating film anomaly detection method to identify heating film anomalies. This heating film anomaly detection method is as follows: Figure 9 As shown, where, Figure 9 This is a flowchart illustrating a heating film anomaly identification method provided in other embodiments of this application.

[0204] In step S500, the sampling circuit sends the collected state data of the battery component 11 with a timestamp to the controller, and the controller receives the sampled data. The sampling circuit collects data at preset sampling intervals.

[0205] like Figure 9 As shown, in step S501, the controller obtains a status dataset based on the sampled data. The status dataset is presented in tabular form. The status dataset includes a timestamp and the corresponding highest temperature value, lowest temperature value, first identifier, second identifier, third identifier, and main circuit current value. The first identifier, second identifier, and third identifier are all 0 or 1. A first identifier of 1 indicates that the heating circuit 14 is in the on state, and a first identifier of 0 indicates that the heating circuit 14 is in the off state. A second identifier of 1 indicates that the power supply branch to which the load element belongs is in the on state, and a first identifier of 0 indicates that the heating circuit 14 is in the off state. A third identifier of 1 indicates that the battery assembly 11 is in the charging state, and a first identifier of 0 indicates that the battery assembly 11 is in the discharging state.

[0206] Steps S502 to S506 involve analyzing the highest and lowest temperature values ​​in the state dataset to diagnose whether partial ablation exists in the multiple heating films 141.

[0207] In step S502, multiple consecutive data points located between two adjacent non-heating state data points and with a first identifier of 1 are extracted from the state dataset to obtain a data set for each heating time period; wherein, the first identifier of the non-heating state data is 0.

[0208] In step S503, for the highest and lowest temperature values ​​contained in the data set of each heating time period, the following steps are performed: the instantaneous temperature rise rate is calculated by the first-order difference method; a sliding window is established; the average value of each sliding window is calculated; the average value of all sliding windows is calculated to obtain the highest temperature rise rate and the lowest temperature rise rate.

[0209] In step S504, it is determined whether the condition that the highest temperature rise rate is ≥1.8℃ / min and the lowest temperature rise rate is ≤0℃ / min is true. In step S505, it is determined whether the condition that the highest temperature rise rate - the lowest temperature rise rate is >1.5℃ / min is true.

[0210] If either step S504 or step S505 is true, then proceed to step S506 to determine that there is an abnormality in the heating film in the heating circuit and the abnormality mode is that the heating film resistor is connected incorrectly.

[0211] Steps S507 to S506 involve analyzing the highest and lowest temperature values ​​in the state dataset to diagnose whether partial ablation exists in the multiple heating films 141.

[0212] In step S507, the data with the third identifier 1 is filtered out from the state dataset to obtain the preprocessed dataset.

[0213] In step S508, two adjacent data sets with different first identifiers are extracted from the preprocessed dataset, and the difference between the main circuit current value after the change of the first identifier and the main circuit current value before the change of the first identifier in the two data sets is determined as the heating current value.

[0214] In steps S509 to S512, heating current values ​​less than 0A are filtered out, heating current values ​​whose time interval between two corresponding data points exceeds 40s are filtered out, and heating current values ​​whose second identifiers are different are filtered out, thus obtaining a filtered dataset.

[0215] In step S513, a two-dimensional clustering analysis is performed on the filtered dataset based on the DBSCAN algorithm. The two dimensions are the heating current value and the second time stamp of the two timestamps corresponding to the heating current value.

[0216] In step S514, it is determined whether the ratio of the heating current value of the latest cluster to the heating current value of the adjacent previous cluster is approximately 1 / 2. If yes, proceed to step S515; otherwise, proceed to step S517 to determine that the heating film 141 has not been ablated.

[0217] In step S515, it is determined whether the lowest temperature rise rate of the heating time period to which the heating current value of the latest cluster belongs is <0℃ / min. If yes, proceed to step S516 to determine that there is an abnormality in the heating film in the heating circuit and the abnormality mode is partial ablation of the heating film 141. If no, proceed to step S517.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of the claims and specification of this application. In particular, as long as there is no structural conflict, the various technical features mentioned in each embodiment can be combined in any way. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A battery management system applied to a battery pack, characterized in that, The battery pack has a main circuit connected to the battery components and a heating circuit connected to the main circuit. The heating circuit includes N heating films arranged in parallel. The heating circuit can switch between an on / off state and an off state, where N is a positive integer and N≥2. The battery management system includes: A sampling circuit is used to collect the current of the main circuit, the highest temperature value of the battery assembly, and the lowest temperature value of the battery assembly. The controller is configured to: A state dataset is formed based on the data obtained by the sampling circuit at each timestamp; wherein, the state dataset includes at least a timestamp and the highest temperature value, lowest temperature value, and main circuit current value corresponding to each timestamp; Based on the state dataset, it is determined whether there is an abnormality in the heating film of the heating circuit.

2. The battery management system according to claim 1, characterized in that, The controller is configured to: Based on the state dataset, determine the highest and lowest temperature rise rates of the heating circuit during each heating time period; determine whether the highest and lowest temperature rise rates meet preset conditions; if they do, determine that the heating film in the heating circuit is abnormal and the abnormal mode is incorrect connection of the heating film resistor; wherein, the heating circuit maintains the circuit state during the heating time period.

3. The battery management system according to claim 2, characterized in that, The sampling circuit is also used to collect the on / off state of the heating circuit, and the state dataset also includes a first identifier corresponding to each timestamp, the first identifier being used to indicate the on / off state of the heating circuit; The controller is configured to: Extract K consecutive data points from the state dataset that are located between two adjacent non-heating state data points and whose first identifier indicates that the heating circuit is in the on state, to obtain a data set for each heating time period, where K is a positive integer greater than or equal to 2; wherein, the first identifier of the non-heating state data indicates that the heating circuit is in the off state; For each heating time period, the highest and lowest temperature rise rates for that heating time period are determined.

4. The battery management system according to claim 3, characterized in that, The controller is configured to: For each heating time period, the data set containing the highest and lowest temperature values ​​is processed based on temperature analysis steps to obtain the highest temperature rise rate and the lowest temperature rise rate. The temperature analysis step includes determining the instantaneous temperature rise rate during the heating time period, analyzing the instantaneous temperature rise rate based on the sliding window method, calculating the average value within each sliding window, and calculating the average value of all the sliding windows; the window size of the sliding window is M, M+2≤K, where M is a positive integer greater than or equal to 2.

5. The battery management system according to any one of claims 2 to 4, characterized in that, The preset condition is one of the following conditions: The highest temperature rise rate is greater than or equal to a first threshold value, and the lowest temperature rise rate is less than or equal to a second threshold value, wherein the second threshold value is a non-negative number and less than the first threshold value. The difference between the highest temperature rise rate and the lowest temperature rise rate is greater than a third threshold value, and the third threshold value is less than the difference between the first threshold value and the second threshold value and is close to the first threshold value.

6. The battery management system according to any one of claims 1 to 4, characterized in that, The controller is configured to: determine a heating current value based on the state dataset, the heating current value being the total current value of the heating circuit and related to the main circuit current value; analyze and process a first data group formed by the heating current values ​​belonging to historical time periods and their associated timestamps, and a second data group formed by the heating current values ​​belonging to the latest time period and their associated timestamps, to determine whether a first failure condition is met; if the first failure condition is met, determine that the heating film in the heating circuit is abnormal and the abnormal mode is heating film ablation; wherein, the first failure condition is that the heating current value in the second data group is reduced by i / N compared to the heating current value in the first data group, 1≤i<N, where i is a positive integer.

7. The battery management system according to claim 6, characterized in that, The sampling circuit is also used to collect the on / off state of the heating circuit, and the state dataset also includes a first identifier corresponding to each timestamp, the first identifier being used to indicate the on / off state of the heating circuit; The controller is configured to: Extract two adjacent data points with different first identifiers from the state dataset, and determine the heating current value as the difference between the main circuit current value after the first identifier changes and the main circuit current value before the first identifier changes in the two data points.

8. The battery management system according to claim 7, characterized in that, The battery pack also includes Q power branches belonging to load elements, the load elements being connected in parallel with the heating film, and the power branches being switchable between a conducting state and a cut-off state. The sampling circuit is also used to collect the on / off state of the power branches. The state dataset also includes Q second identifiers corresponding to each timestamp, and the Q second identifiers correspond one-to-one with the Q power branches. The second identifiers are used to indicate the on / off state of the corresponding power branch; where Q is a positive integer. The controller is configured to: The heating current values ​​that meet the abnormal data selection criteria are filtered out to obtain a filtered dataset, wherein the abnormal data selection criteria include at least one of the following: The heating current value is less than 0A; The time interval between the two data points corresponding to the heating current value exceeds the preset duration; The second identifiers of the two data points corresponding to the heating current values ​​are different; The first data group, consisting of the heating current values ​​and their associated timestamps belonging to the historical time period, and the second data group, consisting of the heating current values ​​and their associated timestamps belonging to the latest time period, are analyzed and processed in the filtered dataset.

9. The battery management system according to any one of claims 6 to 8, characterized in that, The controller is configured to: Data that meets the target data selection criteria are filtered from the state dataset to obtain a preprocessed dataset. The target data selection criteria are used to indicate that the battery assembly is in a charging state. The heating current value is determined based on the preprocessed dataset.

10. The battery management system according to claim 9, characterized in that, The sampling circuit is also used to collect the charging and discharging state of the battery assembly. The state dataset also includes a third identifier corresponding to each timestamp, which is used to indicate the charging and discharging state of the battery assembly. The target data selection criteria include at least one of the following: The current value of the main circuit is negative. The third identifier indicates that the battery assembly is in the charging state.

11. The battery management system according to any one of claims 6 to 8, characterized in that, The controller is configured to: Cluster analysis was performed on the first data group and the second data group based on a clustering algorithm; If multiple subsets are formed, and the heating current value of the subset corresponding to the second data group is reduced by i / N compared to the heating current value of the subset corresponding to the first data group, then the first failure condition is determined to be met.

12. The battery management system according to any one of claims 6 to 8, characterized in that, The controller is configured to: If the first failure condition is met, the second failure condition is then determined. The second failure condition is that the rate of increase of at least one of the highest temperature value and the lowest temperature value in the heating time period to which the timestamp in the second data group belongs gradually decreases. If the second failure condition is met, it is determined that the heating film in the heating circuit is abnormal and the abnormal mode is heating film ablation.

13. The battery management system according to claim 12, characterized in that, The second failure condition is that the lowest temperature rise rate of the heating time period to which the timestamp in the second data group belongs is less than 0°C / min.

14. A method for identifying abnormalities in a heating film, characterized in that, include: Acquire sampling data; A state dataset is formed based on the sampled data at each timestamp; wherein the state dataset includes at least a timestamp and the highest temperature value, lowest temperature value, and main circuit current value corresponding to each timestamp; Based on the state dataset, it is determined whether there is any abnormality in the heating film in the heating circuit.

15. A battery pack, characterized in that, include: Battery components; The main circuit has a main positive circuit and a main negative circuit. One end of the main positive circuit is connected to the positive terminal of the battery assembly, and one end of the main negative circuit is connected to the negative terminal of the battery assembly. A heating circuit includes N heating films arranged in parallel. One end of each of the N heating films is connected to one of the main positive circuit and the main negative circuit via a heating switch, and the other end is connected to the other of the main positive circuit and the main negative circuit. The heating switch is operable, allowing the heating circuit to switch between an on / off state; where N is a positive integer, N≥2; and The battery management system according to any one of claims 1 to 13.

16. An electrical appliance, characterized in that, include: The battery pack according to claim 15.

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