Battery thermal runaway diagnostic device and diagnostic method

Abstract

The present invention discloses a battery thermal runaway diagnostic device and method, comprising a stress sensor, a battery module management unit, a battery cluster management unit, and a steel tie. The steel tie is transversely wound around the battery module. The stress sensor is disposed on the steel tie on the side of the battery module. The stress sensor is used to collect battery module stress resistance data on the steel tie. The battery module management unit is used to receive the battery module stress resistance data and transmit it to the battery cluster management unit. The battery cluster management unit is used to record the number of battery module cycles and the battery module state of charge, and then perform battery thermal runaway diagnosis based on the battery module stress resistance data, the number of battery module cycles, and the battery module state of charge. The present invention can collect the deformation stress value, i.e., the anti-expansion force, on the surface of the battery module tie as a threshold for determining the type of thermal runaway, provide sufficient advance warning time for thermal runaway, and reduce diagnostic errors. The device can be widely used in the field of energy storage system monitoring technology.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage system monitoring, and in particular to a battery thermal runaway diagnosis device and a diagnosis method thereof. Background Art

[0002] When a battery is subjected to mechanical, electrical, or thermal abuse, a chain reaction of heat generation occurs within the battery, causing a sharp change in the rate of temperature rise. This overheating phenomenon is known as thermal runaway. Multiple battery cells are first connected in series and parallel to form a battery module, which is then connected in series and parallel to form a battery cluster. If a battery leaks during actual operation, it is difficult to pinpoint the problematic battery module by measuring the cell voltage and temperature parameters. Therefore, it is easy to disconnect the battery charge and discharge circuit only after thermal runaway occurs, resulting in insufficient battery safety warning time and serious safety accidents. Summary of the Invention

[0003] To solve the above technical problems, the purpose of the present invention is to provide a battery thermal runaway diagnosis device and a diagnostic method thereof, which can provide sufficient advance warning time for thermal runaway.

[0004] To achieve the above-mentioned objectives, one aspect of an embodiment of the present application proposes a battery thermal runaway diagnostic device, comprising a stress sensor, a battery module management unit, a battery cluster management unit, and a steel tie, wherein the steel tie is transversely wound around the battery module, the stress sensor is arranged on the steel tie on the side of the battery module, the output end of the stress sensor is connected to the first input end of the battery module management unit, the battery module management unit is connected to the battery cluster management unit, the stress sensor is used to collect the battery module anti-stress data on the steel tie, the battery module management unit is used to receive the battery module anti-stress data and send the battery module anti-stress data to the battery cluster management unit, the battery cluster management unit is used to record the number of battery module cycles and the battery module power status, and then perform battery thermal runaway diagnosis based on the battery module anti-stress data, the number of battery module cycles, and the battery module power status.

[0005] In some embodiments, the battery thermal runaway diagnostic device also includes a temperature sensor, which is arranged on the aluminum cover plate of each battery cell in the battery module. The output end of the temperature sensor is connected to the second input end of the battery module management unit for collecting battery cell temperature data.

[0006] In some embodiments, the battery thermal runaway diagnostic device also includes a voltage sensor, which is arranged on the battery pole of each battery cell in the battery module. The output end of the voltage sensor is connected to the third input end of the battery module management unit for collecting battery cell voltage data.

[0007] To achieve the above objectives, another aspect of the present application provides a diagnostic method for a battery thermal runaway diagnostic device, comprising the following steps:

[0008] The stress resistance data of the battery module on the steel tie is collected through the stress sensor;

[0009] receiving the battery module anti-stress data through the battery module management unit and sending the battery module anti-stress data to the battery cluster management unit;

[0010] The battery module cycle times and battery module power status are recorded by the battery cluster management unit, and battery thermal runaway diagnosis is then performed based on the battery module stress resistance data, the battery module cycle times and the battery module power status.

[0011] In some embodiments, the diagnostic method further comprises:

[0012] The temperature sensor collects the battery cell temperature data of each battery cell in the battery module.

[0013] In some embodiments, the diagnostic method further comprises:

[0014] The battery cell voltage data of each battery cell in the battery module is collected by a voltage sensor.

[0015] In some embodiments, the diagnostic method further comprises:

[0016] Determining, by the battery module management unit, whether the battery cell temperature data and the battery cell voltage data exceed preset alarm thresholds, wherein the preset alarm thresholds include a first-level alarm threshold, a second-level alarm threshold, and a third-level alarm threshold;

[0017] When the battery cell temperature data or the battery cell voltage data exceeds the first-level warning threshold, it is determined that the corresponding battery cell is in a thermal runaway state.

[0018] In some embodiments, the battery thermal runaway diagnosis is performed by the battery cluster management unit according to the battery module stress resistance data, the battery module cycle count, and the battery module power state, which specifically includes:

[0019] Determining, according to the battery module power state, the battery module anti-stress data within a preset first power range as first stress data, and determining, according to the battery module power state, the battery module anti-stress data within a preset second power range as second stress data;

[0020] Obtaining a linear relationship function between the anti-stress data of the battery module and the number of cycles of the battery module, and then obtaining stress estimation values according to the linear relationship function, the stress estimation values including a first stress estimation value, a second stress estimation value, a third stress estimation value, and a fourth stress estimation value;

[0021] When the number of cycles of the battery module is within a preset first cycle number range, determining whether the first stress data exceeds the first stress estimated value and whether the second stress data exceeds the third stress estimated value; if both exceed, determining that the corresponding battery module is in a thermal runaway state;

[0022] When the cycle number of the battery module is within a preset second cycle number range, it is determined whether the first stress data exceeds the second stress estimated value and whether the second stress data exceeds the fourth stress estimated value. If both exceed, it is determined that the corresponding battery module is in a thermal runaway state.

[0023] In some embodiments, obtaining a linear relationship function between the battery module stress resistance data and the battery module cycle number, and then obtaining a stress estimation value according to the linear relationship function, specifically includes:

[0024] Obtaining first stress sample values and corresponding first cycle numbers within the first power range and the first cycle number range, performing linear fitting on the first stress sample values and the first cycle number to obtain a first linear relationship function, and then obtaining the first stress estimated value based on the first linear relationship function;

[0025] Obtaining second stress sample values and corresponding second cycle numbers within the first power range and the second cycle number range, performing linear fitting on the second stress sample values and the second cycle number to obtain a second linear relationship function, and then obtaining the second stress estimated value based on the second linear relationship function;

[0026] Obtaining third stress sample values and corresponding third cycle numbers within the second power range and the first cycle number range, performing linear fitting on the third stress sample values and the third cycle number to obtain a third linear relationship function, and then obtaining the third stress estimated value based on the third linear relationship function;

[0027] Obtain a fourth stress sample value and a corresponding fourth cycle number within the second power range and the second cycle number range, perform linear fitting on the fourth stress sample value and the fourth cycle number to obtain a fourth linear relationship function, and then obtain the fourth stress estimated value based on the fourth linear relationship function.

[0028] In some embodiments, the diagnostic method further includes the step of presetting the first power range, the second power range, the first cycle number range, and the second cycle number range, which specifically includes:

[0029] Setting the first power range to 0% to 30%, and setting the second power range to 70% to 100%;

[0030] The first cycle number range is set to be less than or equal to 100 times, and the second cycle number range is set to be greater than 100 times.

[0031] The beneficial effects of the present invention are as follows: the battery thermal runaway diagnostic device and diagnostic method of the present invention include a stress sensor, a battery module management unit, a battery cluster management unit and a steel tie. The stress sensor located on the steel tie detects the deformation stress value (i.e., anti-expansion force) of the outer surface of the battery module, rather than directly detecting the expansion force of the battery module, which facilitates the installation and maintenance of the stress sensor. The battery cluster management unit then performs batch diagnosis on the anti-stress data of the battery module according to different power states and different cycle times. The deformation stress value (i.e., anti-expansion force) on the surface of the battery module tie can be collected as a threshold for determining the type of thermal runaway, and the target battery module can be quickly located through the battery module management unit and the battery cluster management unit, which can improve the advance warning time of thermal runaway and reduce diagnostic errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following introduction is made to the drawings required for use in the embodiments of the present invention. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative work.

[0033] Figure 1 A structural block diagram of a battery thermal runaway diagnostic device provided by an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of the sensor layout of a battery thermal runaway diagnostic device provided by an embodiment of the present invention;

[0035] Figure 3A flowchart of the steps of a diagnostic method for a battery thermal runaway diagnostic device provided by an embodiment of the present invention;

[0036] Figure 4 A logical diagram of thermal runaway diagnosis using battery cell voltage data or battery cell temperature data provided by an embodiment of the present invention;

[0037] Figure 5 A logical diagram of thermal runaway diagnosis using battery module stress resistance data provided by an embodiment of the present invention.

[0038] Reference numerals: 10, battery cell; 101, battery temperature distribution point; 102, battery voltage distribution point; 103, battery module steel tie strain distribution point; 104, steel tie. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0040] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0041] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0042] Before explaining the embodiments of the present application in detail, some of the nouns and terms involved in the embodiments of the present application are first explained. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0043] Battery thermal runaway: Under conditions of mechanical abuse, electrical abuse, thermal abuse, etc., a heat-generating chain reaction occurs inside the battery, causing an overheating phenomenon in which the battery temperature rise rate changes sharply.

[0044] Battery expansion force: During long-term charge and discharge cycles, the battery cell will expand to a certain extent due to the formation of the internal SEI film or internal side reactions during the lithium insertion and extraction process, thereby squeezing the battery shell.

[0045] During the actual operation of energy storage systems, existing thermal runaway detection technology monitors the operating parameters of battery cell temperature and voltage in real time. When a sudden change in battery cell temperature or voltage occurs or exceeds a set threshold, external warnings of different alarm levels are issued. However, due to the inherent charging, discharging, and deintercalation characteristics of the battery, excessive internal pressure can cause expansion after a period of continuous charging and discharging. This can lead to leakage from the battery casing or expansion and leakage from the explosion-proof valve. These side reactions that precede thermal runaway are difficult to detect and warn in advance.

[0046] To this end, an embodiment of the present invention proposes a battery thermal runaway diagnostic device, including a stress sensor, a battery module management unit, a battery cluster management unit, and a steel tie. The stress sensor located on the steel tie detects the deformation stress value (i.e., anti-expansion force) of the outer surface of the battery module, rather than directly detecting the expansion force of the battery module. This facilitates the installation and maintenance of the stress sensor. The battery cluster management unit then performs batch diagnosis of the battery module anti-stress data according to different power states and different cycle times. The deformation stress value (i.e., anti-expansion force) on the surface of the battery module tie can be collected as a threshold for determining the type of thermal runaway. The target battery module can be quickly located through the battery module management unit and the battery cluster management unit, thereby improving the advance warning time of thermal runaway and reducing diagnostic errors.

[0047] Reference Figure 1 , Figure 1 This is a structural block diagram of a battery thermal runaway diagnostic device provided in an embodiment of the present invention. The embodiment of the present invention proposes a battery thermal runaway diagnostic device, including a stress sensor, a battery module management unit, a battery cluster management unit and a steel tie. The steel tie is transversely wrapped around the battery module. The stress sensor is arranged on the steel tie on the side of the battery module. The output end of the stress sensor is connected to the first input end of the battery module management unit. The battery module management unit is connected to the battery cluster management unit. The stress sensor is used to collect the battery module anti-stress data on the steel tie. The battery module management unit is used to receive the battery module anti-stress data and send the battery module anti-stress data to the battery cluster management unit. The battery cluster management unit is used to record the number of battery module cycles and the battery module power status, and then perform battery thermal runaway diagnosis based on the battery module anti-stress data, the number of battery module cycles and the battery module power status.

[0048] Specifically, a battery module consists of multiple battery cells connected in series and parallel, while a battery module consists of multiple battery modules connected in series. Each battery module corresponds to a battery module management unit, which receives and uploads data from each battery module's collection point. A battery cluster consists of multiple battery modules connected in series, and each battery cluster corresponds to a battery cluster management unit, which manages the data uploaded by each battery module management unit, processes it, and issues warnings.

[0049] Among them, by attaching the stress sensor to the outer surface of the steel tie between the steel tie and the large surface of the battery, and using the steel tie as the support surface, the assembly and maintenance are simple, and the battery module stress detection process will not be affected by the uneven expansion of the battery, which will cause the sensor to be unstable and cause large test errors.

[0050] Reference Figure 1 and Figure 2 , Figure 2 This is a schematic diagram of the sensor layout of the battery thermal runaway diagnostic device. As an optional implementation, the battery thermal runaway diagnostic device also includes a temperature sensor. The temperature sensor is arranged on the aluminum cover plate of each battery in the battery module. The output end of the temperature sensor is connected to the second input end of the battery module management unit for collecting battery cell temperature data.

[0051] Reference Figure 1 and Figure 2 As an optional embodiment, the battery thermal runaway diagnostic device also includes a voltage sensor, which is arranged on the battery pole of each battery in the battery module. The output end of the voltage sensor is connected to the third input end of the battery module management unit for collecting battery cell voltage data.

[0052] For example, in order to better monitor the battery status, Figure 2As shown, the battery cell voltage, battery cell temperature, and battery module steel tie strain force are monitored. In an embodiment of the present invention, a single battery module is composed of 9 battery cells 10 connected in series. The battery voltage distribution point 102 is used to place a voltage sensor to detect and collect the battery cell voltage. The voltage sensor is arranged at any position on the battery pole and fixed by welding. One point is arranged for each battery cell 10, for a total of 9 points. The battery temperature distribution point 101 is used to place a temperature sensor to detect and collect the external temperature of the battery cell 10. The temperature sensor is arranged at any position on the aluminum cover of the battery and fixed by welding or dispensing. The number of temperature sensors and battery cells 10 is arranged at a ratio of no more than 3 / 4, for a total of 2 points. The battery module steel tie strain distribution point 103 is used to place a stress sensor to detect and collect the battery module anti-expansion force. The stress sensor is arranged on the outer surface of the battery module steel tie 104 near the large surface side of the battery (vertical to the positive and negative pole surfaces of the battery) and fixed by welding or dispensing. The stress sensor is arranged at a ratio of no less than 1 / 2 to the number of battery module steel ties, for a total of 2 points.

[0053] It should be noted that the number of battery cells 10 and the number of sensor points can be selected according to actual needs and are not limited thereto in the embodiments of the present invention.

[0054] When the battery cell 10 is charged and discharged in the entire energy storage system with a single battery cluster as a data management unit, the battery cell voltage data V1, V2 to V360, the battery cell temperature data T1, T2 to T80, the battery module stress resistance data F1, F2 to F80, the battery module cycle number N times (each time the rated charge and discharge capacity is reached), and the battery module state of charge (SOC value) are recorded. Then, the battery module management unit uses the battery cell voltage data and the battery cell temperature data to issue a thermal runaway warning. The battery cluster management unit analyzes the measured data of the battery module charge and discharge, and considers that a battery solid electrolyte interface will appear after a certain number of cycles. Thermal runaway judgment fitting is performed for two tiers (above a certain number of cycles and below a certain number of cycles) to improve the accuracy of the fitted stress.

[0055] The above describes the structure and working process of the battery thermal runaway diagnostic device according to an embodiment of the present invention. It can be appreciated that, compared with existing thermal runaway detection technologies, the present invention has the following advantages:

[0056] First, the deformation stress value (i.e., anti-expansion force) on the surface of the battery module tie is detected by a stress sensor located on the steel tie, rather than directly detecting the expansion force of the battery module. The battery module anti-stress data is then diagnosed in batches according to different power states and different cycle times through the battery cluster management unit. This can collect the deformation stress value (i.e., anti-expansion force) on the surface of the battery module tie as the threshold for determining the type of thermal runaway, and quickly locate the target battery module through the battery module management unit and the battery cluster management unit, thereby improving the advance warning time of thermal runaway.

[0057] Second, the stress sensor is attached to the contact part between the steel tie and the large surface of the battery, and the steel tie is used as the support surface. The assembly and maintenance are simple, and the sensor will not be unstable due to uneven battery expansion during the battery module stress detection process, and the test error is low;

[0058] 3. It can adapt to different types of battery modules and is not affected by the internal electrolyte composition of the battery, battery brand and model, battery assembly process, etc., which can improve the versatility of device promotion.

[0059] Reference Figure 3 , Figure 3 This is a flowchart of a diagnostic method for a battery thermal runaway diagnostic device. An embodiment of the present invention provides a diagnostic method for a battery thermal runaway diagnostic device, which is performed by the above-mentioned battery thermal runaway diagnostic device and includes the following steps S101 to S103:

[0060] S101, collecting stress resistance data of the battery module on the steel tie through a stress sensor;

[0061] S102, receiving battery module anti-stress data through the battery module management unit and sending the battery module anti-stress data to the battery cluster management unit;

[0062] S103 , recording the battery module cycle times and the battery module power status through the battery cluster management unit, and then performing battery thermal runaway diagnosis based on the battery module stress resistance data, the battery module cycle times and the battery module power status.

[0063] As an optional embodiment, the diagnostic method further includes the following step S104:

[0064] S104 , collecting temperature data of each battery cell in the battery module through a temperature sensor.

[0065] As an optional embodiment, the diagnostic method further includes the following step S105:

[0066] S105 , collecting battery cell voltage data of each battery in the battery module through a voltage sensor.

[0067] The contents of the above-mentioned battery thermal runaway diagnostic device embodiment are all applicable to the diagnostic method embodiment of the present battery thermal runaway diagnostic device. The functions specifically implemented by the diagnostic method embodiment of the present battery thermal runaway diagnostic device are the same as those of the above-mentioned battery thermal runaway diagnostic device embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned battery thermal runaway diagnostic device embodiment.

[0068] As an optional embodiment, the diagnostic method further includes the following steps S106 and S107:

[0069] S106, determining, by the battery module management unit, whether the battery cell temperature data and the battery cell voltage data exceed preset alarm thresholds, where the preset alarm thresholds include a first-level alarm threshold, a second-level alarm threshold, and a third-level alarm threshold;

[0070] S107 : When the battery cell temperature data or the battery cell voltage data exceeds a first-level alarm threshold, it is determined that the corresponding battery cell is in a thermal runaway state.

[0071] Specifically, if Figure 4 The figure shows a logic diagram for thermal runaway diagnosis using battery cell voltage data or battery cell temperature data. If battery cell voltage data or battery cell temperature data is used for thermal runaway warning, battery cell voltage data V1, V2 to V360 are recorded, and battery cell temperature data T1, T2 to T80 are recorded. According to the alarm threshold, they are divided into level one, level two, and level three alarms. When the cell voltage data or battery cell temperature data reaches the maximum limit value of the level one warning (the most serious warning), a thermal runaway state is reached and operation needs to be stopped for maintenance and inspection.

[0072] Those skilled in the art will appreciate that the first-level, second-level, and third-level alarm thresholds can be set based on the battery type. For example, the first-level alarm thresholds are set to 60°C for the cell temperature alarm, 3.65V for the cell voltage charge alarm, and 2.5V for the cell voltage discharge alarm; the second-level alarm thresholds are set to 45°C for the cell temperature alarm, 3.6V for the cell voltage charge alarm, and 2.7V for the cell voltage discharge alarm; and the third-level alarm thresholds are set to 40°C for the cell temperature alarm, 3.55V for the cell voltage charge alarm, and 2.9V for the cell voltage discharge alarm.

[0073] As an optional implementation, the step of diagnosing battery thermal runaway by the battery cluster management unit based on the battery module stress resistance data, the battery module cycle count, and the battery module power status can be further divided into the following steps S1031 to S1034:

[0074] S1031. Determine, based on the battery module power state, the battery module anti-stress data within a preset first power range as first stress data, and determine, based on the battery module power state, the battery module anti-stress data within a preset second power range as second stress data;

[0075] S1032. Obtain a linear relationship function between the stress resistance data of the battery module and the number of cycles of the battery module, and then obtain stress estimation values according to the linear relationship function, where the stress estimation values include a first stress estimation value, a second stress estimation value, a third stress estimation value, and a fourth stress estimation value;

[0076] S1033: When the number of cycles of the battery module is within a preset first cycle number range, determining whether the first stress data exceeds the first stress estimated value and whether the second stress data exceeds the third stress estimated value; if both exceed, determining that the corresponding battery module is in a thermal runaway state;

[0077] S1034. When the battery module cycle number is within a preset second cycle number range, determine whether the first stress data exceeds the second stress estimated value and whether the second stress data exceeds the fourth stress estimated value. If both exceed, determine that the corresponding battery module is in a thermal runaway state.

[0078] Those skilled in the art will appreciate that the first power range, the second power range, the first cycle number range, and the second cycle number range can be set according to the battery type, and the second power range is generally set to be larger than the first power range. For example, the first power range can be 0% to 30%, 5% to 20%, etc.; the second power range can be 70% to 100%, 75% to 95%, etc.; the first cycle number range can be less than or equal to 150 times, less than or equal to 200 times, etc.; and the second cycle number range can be greater than 150 times, greater than 200 times, etc.

[0079] As an optional embodiment, the diagnostic method further includes the steps of presetting a first power range, a second power range, a first cycle number range, and a second cycle number range, which specifically includes the following steps:

[0080] Set the first power range to 0% to 30%, and set the second power range to 70% to 100%;

[0081] The first cycle number range is set to be less than or equal to 100 times, and the second cycle number range is set to be greater than 100 times.

[0082] For example, the first power range is 0% to 30%, the second power range is 70% to 100%, the first cycle number range is less than or equal to 100 times, and the second cycle number range is greater than 100 times. Figure 5The following is a logical diagram for using battery module stress data for thermal runaway diagnosis. To use this data for thermal runaway warning, the first step is to identify the stress values corresponding to two power state ranges (i.e., 0% to 30% and 70% to 100%) where the module tie's anti-expansion force varies significantly. Then, based on cycles greater than 100 and less than 100, a linear function is fitted between the stress change and the number of cycles. Once this linear function is derived, the trend of changes in the module tie's anti-expansion force under normal charging and discharging conditions can be estimated, and this value can be used as the threshold for determining thermal runaway.

[0083] Because the expansion of the battery fluctuates under different power states, if the measured stress value is between the stress estimated values in the first power range and the second power range (i.e., 0% to 30% and 70% to 100%) within the corresponding cycle number range, it is regarded as a second-level thermal runaway alarm, and the system needs to reduce power operation; when the measured stress value is greater than the stress estimated values in the first power range and the second power range (i.e., 0% to 30% and 70% to 100%), it can be determined that the battery module has reached a thermal runaway state and a first-level warning is issued, and the device needs to stop operating for maintenance and inspection.

[0084] As a further optional implementation, a linear relationship function between the battery module stress resistance data and the battery module cycle number is obtained, and then a stress estimation value is obtained according to the linear relationship function. This step can be specifically divided into the following steps S10321 to S10324:

[0085] S10321. Obtain first stress sample values and corresponding first cycle numbers within a first power range and a first cycle number range, perform linear fitting on the first stress sample values and the first cycle number to obtain a first linear relationship function, and then obtain a first stress estimation value based on the first linear relationship function;

[0086] Specifically, taking the first power range of 0% to 30% and the first cycle number range of less than or equal to 100 times as an example, within the first power range (0% to 30%) and the first cycle number range (N≤100), the first stress sample values corresponding to the first 10 to 20 cycles are taken, and the fitting coefficients a1 and b1 are calculated using linear regression to obtain a first linear relationship function: ΔF1=a1N+b1(N≤100), where ΔF1 represents the stress difference between two cycles within the first power range. When the number of cycles N continues to increase, it can be obtained that the first stress estimated value of the current cycle number is equal to the stress value of the previous cycle test plus ΔF1, that is, F1=ΔF1+F(N-1), where F1 represents the first stress estimated value.

[0087] S10322. Obtain second stress sample values and corresponding second cycle numbers within the first power range and the second cycle number range, perform linear fitting on the second stress sample values and the second cycle number to obtain a second linear relationship function, and then obtain a second stress estimation value based on the second linear relationship function;

[0088] Specifically, taking the first power range of 0% to 30% and the second cycle number range of greater than 100 times as an example, in the first power range (0% to 30%) and the second cycle number range (N>100), the second stress sample values corresponding to the first 110 to 120 cycles are taken, and the fitting coefficients a2 and b2 are calculated by linear regression to obtain the second linear relationship function: ΔF2=a2(N-100)+b2(N>100), where ΔF2 represents the stress difference between the two cycles in the first power range. When the number of cycles N continues to increase, it can be obtained that the second stress estimated value of the current cycle number is equal to the stress value of the previous cycle test plus ΔF2, that is, F2=ΔF2+F(N-1), where F2 represents the second stress estimated value.

[0089] S10323. Obtain third stress sample values and corresponding third cycle numbers within the second power range and the first cycle number range, perform linear fitting on the third stress sample values and the third cycle number to obtain a third linear relationship function, and then obtain a third stress estimated value based on the third linear relationship function;

[0090] Specifically, taking the second power range of 70% to 100% and the first cycle number range of less than or equal to 100 times as an example, in the second power range (70% to 100%) and the first cycle number range (N≤100), the third stress sample values corresponding to the first 10 to 20 cycles are taken, and the fitting coefficients a3 and b3 are calculated by linear regression to obtain the third linear relationship function: ΔF3=a3N+b3(N≤100), where ΔF3 represents the stress difference between the two cycles in the second power range. When the number of cycles N continues to increase, it can be obtained that the third stress estimated value of the current cycle number is equal to the stress value of the previous cycle test plus ΔF3, that is, F3=ΔF3+F(N-1), where F3 represents the third stress estimated value.

[0091] S10324. Obtain the fourth stress sample value and the corresponding fourth cycle number within the second power range and the second cycle number range, and perform linear fitting on the fourth stress sample value and the fourth cycle number to obtain a fourth linear relationship function, and then obtain a fourth stress estimated value based on the fourth linear relationship function.

[0092] Specifically, taking the second power range of 70% to 100% and the second cycle number range of greater than 100 times as an example, in the second power range (70% to 100%) and the second cycle number range (N>100), the fourth stress sample values corresponding to the first 110 to 120 cycles are taken, and the fitting coefficients a4 and b4 are calculated by linear regression to obtain the fourth linear relationship function: ΔF4=a4(N-100)+b4(N>100), where ΔF4 represents the stress difference between the two cycles in the second power range. When the number of cycles N continues to increase, it can be obtained that the fourth stress estimated value of the current cycle number is equal to the stress value of the previous cycle test plus ΔF4, that is, F4=ΔF4+F(N-1), where F4 represents the fourth stress estimated value.

[0093] It should be noted that, by extracting the electrical quantity range where the anti-expansion force varies greatly, the embodiment of the present invention can eliminate inaccurate data and improve the running speed of the diagnosis process.

[0094] In the above description of this specification, reference to the terms "one embodiment / example," "another embodiment / example," or "certain embodiments / examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0095] In the present invention, unless otherwise specified or limited, terms such as "installed," "connected," "connect," and "fixed" should be understood in a broad sense. For example, they may refer to fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two components or interaction between two components, unless otherwise specified or limited. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0096] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0097] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A battery thermal runaway diagnostic device, characterized in that: It includes a stress sensor, a battery module management unit, a battery cluster management unit and a steel tie, wherein the steel tie is transversely wrapped around the battery module, the stress sensor is arranged on the steel tie on the side of the battery module, the output end of the stress sensor is connected to the first input end of the battery module management unit, the battery module management unit is connected to the battery cluster management unit, the stress sensor is used to collect the battery module anti-stress data on the steel tie, the battery module management unit is used to receive the battery module anti-stress data and send the battery module anti-stress data to the battery cluster management unit, the battery cluster management unit is used to record the number of battery module cycles and the battery module power status, and then perform battery thermal runaway diagnosis based on the battery module anti-stress data, the number of battery module cycles and the battery module power status.

2. A battery thermal runaway diagnostic device according to claim 1, characterized in that: The battery thermal runaway diagnostic device also includes a temperature sensor, which is arranged on the aluminum cover plate of each battery cell in the battery module. The output end of the temperature sensor is connected to the second input end of the battery module management unit for collecting battery cell temperature data.

3. The battery thermal runaway diagnostic device according to claim 1, characterized in that: The battery thermal runaway diagnostic device also includes a voltage sensor, which is arranged on the battery pole of each battery cell in the battery module. The output end of the voltage sensor is connected to the third input end of the battery module management unit for collecting battery cell voltage data.

4. A diagnostic method for a battery thermal runaway diagnostic device, configured to be executed by the battery thermal runaway diagnostic device according to any one of claims 1 to 3, characterized in that: The following steps are involved: The stress resistance data of the battery module on the steel tie is collected through the stress sensor; receiving the battery module anti-stress data through the battery module management unit and sending the battery module anti-stress data to the battery cluster management unit; Recording the battery module cycle count and battery module power status through the battery cluster management unit, and then performing battery thermal runaway diagnosis based on the battery module stress resistance data, the battery module cycle count and the battery module power status; The battery thermal runaway diagnosis is performed according to the battery module stress resistance data, the battery module cycle number, and the battery module power state, which specifically includes: Determining, according to the battery module power state, the battery module anti-stress data within a preset first power range as first stress data, and determining, according to the battery module power state, the battery module anti-stress data within a preset second power range as second stress data; Obtaining a linear relationship function between the anti-stress data of the battery module and the number of cycles of the battery module, and then obtaining stress estimation values according to the linear relationship function, the stress estimation values including a first stress estimation value, a second stress estimation value, a third stress estimation value, and a fourth stress estimation value; When the number of cycles of the battery module is within a preset first cycle number range, determining whether the first stress data exceeds the first stress estimated value and whether the second stress data exceeds the third stress estimated value; if both exceed, determining that the corresponding battery module is in a thermal runaway state; When the number of cycles of the battery module is within a preset second cycle number range, determining whether the first stress data exceeds the second stress estimated value and whether the second stress data exceeds a fourth stress estimated value; if both exceed, determining that the corresponding battery module is in a thermal runaway state; The step of obtaining a linear relationship function between the anti-stress data of the battery module and the number of cycles of the battery module, and then obtaining a stress estimation value according to the linear relationship function, specifically includes: Obtaining first stress sample values and corresponding first cycle numbers within the first power range and the first cycle number range, performing linear fitting on the first stress sample values and the first cycle number to obtain a first linear relationship function, and then obtaining the first stress estimated value based on the first linear relationship function; Obtaining second stress sample values and corresponding second cycle numbers within the first power range and the second cycle number range, performing linear fitting on the second stress sample values and the second cycle number to obtain a second linear relationship function, and then obtaining the second stress estimated value based on the second linear relationship function; Obtaining third stress sample values and corresponding third cycle numbers within the second power range and the first cycle number range, performing linear fitting on the third stress sample values and the third cycle number to obtain a third linear relationship function, and then obtaining the third stress estimated value based on the third linear relationship function; Obtain a fourth stress sample value and a corresponding fourth cycle number within the second power range and the second cycle number range, perform linear fitting on the fourth stress sample value and the fourth cycle number to obtain a fourth linear relationship function, and then obtain the fourth stress estimated value based on the fourth linear relationship function.

5. The diagnostic method according to claim 4, characterized in that The diagnostic method further comprises: The temperature sensor collects the battery cell temperature data of each battery cell in the battery module.

6. The diagnostic method according to claim 5, characterized in that The diagnostic method further comprises: The battery cell voltage data of each battery cell in the battery module is collected by a voltage sensor.

7. The diagnostic method according to claim 6, characterized in that The diagnostic method further comprises: Determining, by the battery module management unit, whether the battery cell temperature data and the battery cell voltage data exceed preset alarm thresholds, wherein the preset alarm thresholds include a first-level alarm threshold, a second-level alarm threshold, and a third-level alarm threshold; When the battery cell temperature data or the battery cell voltage data exceeds the first-level warning threshold, it is determined that the corresponding battery cell is in a thermal runaway state.

8. The diagnostic method according to claim 4, characterized in that The diagnostic method further includes the step of presetting the first power range, the second power range, the first cycle number range, and the second cycle number range, which specifically includes: The first power range is set to 0% to 30%, and the second power range is set to 70% to 100%; the first cycle number range is set to be less than or equal to 100 times, and the second cycle number range is set to be greater than 100 times.

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