A battery operation management system and method based on multi-parameter fusion analysis

Abstract

The application discloses a battery operation management system and method based on multi-parameter fusion analysis, relates to the technical field of battery management and energy storage, and divides battery historical operation data by setting a thermal runaway current monitoring threshold, forms different data set analysis, reduces misjudgment of thermal runaway risk judgment, and further analyzes current characteristics of the battery under different operation states.Meanwhile, the current fluctuation data is analyzed and corrected, a current monitoring time window is constructed, normal current fluctuation interference is effectively excluded, abnormal current in battery operation is accurately identified, and the reliability and effectiveness of battery current monitoring are improved.According to a current curve diagram, a temperature gradient is calculated, a dynamic temperature gradient model is constructed in combination with a neural network, temperature accumulation energy generated when battery current is abnormal is obtained, current abnormality results are further accurately analyzed, potential thermal runaway risks are early warned, and stable operation of the battery is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of battery management and energy storage, and in particular to a battery operation management system and method based on multi-parameter fusion analysis. Background Art

[0002] As a key energy storage component, batteries play a vital role in the global energy transition, with widespread applications in electric vehicles, large-scale energy storage systems, and renewable energy storage. With growing energy demand and increasing environmental protection requirements, battery efficiency, safety, and sustainability have become core elements in ensuring energy transition and promoting green development.

[0003] During battery operation and management, battery current is easily affected by various internal and external factors, causing fluctuations and exhibiting changes of varying amplitudes and frequencies. This phenomenon is quite common, but brief current fluctuations are often misjudged as abnormalities, triggering false warnings. This not only disrupts the normal operation of the battery but also adversely affects battery management, increasing unnecessary intervention and maintenance costs. Therefore, to ensure stable and efficient battery operation, it is extremely important to accurately identify and deeply analyze battery current fluctuations. This helps significantly improve the accuracy of warnings, effectively reduce unreasonable operational interventions, and ensure the scientific and reliable nature of battery operation and management. Summary of the Invention

[0004] The purpose of the present invention is to provide a battery operation management system and method based on multi-parameter fusion analysis to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a battery operation management method based on multi-parameter fusion analysis, the battery operation management method comprising the following steps:

[0006] Step S1, collecting current data and temperature data of the battery during operation, and setting a thermal runaway current monitoring threshold for the battery based on the specified operating temperature range of the battery and the current curve analysis;

[0007] Step S1-1, obtaining current data of the battery during operation through a battery management system, wherein the current data is expressed as the current value generated by the battery during operation, including the charging current value and the discharging current value; and obtaining temperature data of the battery during operation through a temperature sensor;

[0008] Step S1-2: Obtain the specified operating temperature range of the battery through technical documents provided by the battery manufacturer or certification reports that comply with international standards;

[0009] Step S1-3: constructing a current curve graph based on the current data acquired by the battery management system and the time series of the current data acquisition, wherein the current curve graph represents the changing trend of the battery current during operation by matching the current value at each time point with the corresponding time tag;

[0010] Step S1-4: Calculate the frequency of occurrence of each current value based on the current values ​​in the current curve graph, select the current value with the highest frequency of occurrence to set the battery's thermal runaway current monitoring threshold, and the thermal runaway current monitoring threshold is used to determine whether the battery meets the current monitoring condition.

[0011] By selecting the current value that appears most frequently in the current curve during battery operation as the thermal runaway current monitoring threshold, significant effects can be achieved in many aspects. On the one hand, this current value usually represents the current level that most frequently occurs when the battery is in normal working condition. Setting the threshold based on this value can closely fit the actual operating characteristics of the battery. Compared with arbitrarily setting the threshold, it can effectively reduce frequent misjudgments caused by unreasonable thresholds and greatly improve the accuracy of battery thermal runaway risk assessment. On the other hand, when the battery current deviates from this common state and exceeds the set threshold, it is very likely to indicate that an abnormal reaction is occurring inside the battery, such as increased internal resistance of the battery, local short circuit, etc., thereby prompting the system to issue a timely warning, reminding staff to pay attention to the battery status and take countermeasures in advance to ensure the safe and stable operation of the battery and reduce the possibility of serious accidents caused by thermal runaway.

[0012] Step S2: Acquire historical operating data of the battery, the historical operating data including current data and current fluctuation data during historical operation of the battery, filter the historical operating data in combination with a thermal runaway current monitoring threshold, store the historical operating data that meets the screening criteria to form a thermal runaway current analysis set, and store the historical operating data that does not meet the screening criteria to form a normal current reference set;

[0013] Obtain historical current data and current fluctuation data of the battery, wherein the current fluctuation data represents the current value caused by current fluctuation due to interference with the battery; judge current data greater than the thermal runaway current monitoring threshold as meeting the screening conditions, and form a thermal runaway current analysis set by storing current data that meet the screening conditions; and form a normal current reference set by storing current data that does not meet the screening conditions.

[0014] By screening the battery's historical operating data, current data exceeding the thermal runaway current monitoring threshold is stored in the thermal runaway current analysis set, and the rest is stored in the normal current reference set. Its function is to classify the battery's historical data and analyze the two sets of data with the largest possible current fluctuations.

[0015] Step S3: extracting current fluctuation data from the thermal runaway current analysis set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation abnormality determination benchmark; extracting current fluctuation data from the normal current reference set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation correction value; correcting the data in the thermal runaway current analysis set based on the current data collected during battery operation in combination with the thermal runaway fluctuation correction value, and determining whether the battery current is abnormal during operation based on the current data collected during battery operation in combination with the thermal runaway fluctuation abnormality determination benchmark;

[0016] Step S3-1, traversing and reading the current fluctuation data in the thermal runaway current analysis set, processing the current fluctuation data using a bubble sort method, and screening out the maximum current fluctuation value as a thermal runaway fluctuation abnormality determination criterion, wherein the thermal runaway fluctuation abnormality determination criterion is represented by the maximum value of the current fluctuation data that meets the thermal runaway current monitoring threshold in the battery history;

[0017] Step S3-2: traverse and read the current fluctuation data in the normal current reference set, process the current fluctuation data using a bubble sort method, and select the maximum value of the current fluctuation as the thermal runaway fluctuation correction value;

[0018] Step S3-3: collect the current data of the battery in real time during operation, and modify the thermal runaway current analysis set in combination with the thermal runaway fluctuation correction value. The modification process is as follows:

[0019] Step S3-3-1: When the current data collected in real time plus the current data of the thermal runaway fluctuation correction value exceeds the thermal runaway current monitoring threshold, the current data exceeding the thermal runaway current monitoring threshold is highlighted:

[0020] When the current data transiently exceeds the thermal runaway current monitoring threshold due to fluctuations but does not continuously exceed the threshold, the current data does not meet the conditions for inclusion in the thermal runaway current analysis set and is added to the normal current reference set.

[0021] When the collected current data continuously exceeds the thermal runaway current monitoring threshold, the condition for joining the thermal runaway current analysis set is met, and the current data is added to the thermal runaway current analysis set;

[0022] The thermal runaway current analysis set is corrected using real-time current data combined with thermal runaway fluctuation correction values. Data where current fluctuations cause the current data to increase but are not actually in a continuous thermal runaway state is removed and assigned to the normal current reference set. Only data that continuously exceeds the thermal runaway current monitoring threshold is retained in the thermal runaway current analysis set. This process further refines the data source, making the data used for subsequent battery operation monitoring more targeted and accurate. It can effectively eliminate interference from short-term current fluctuations, thereby more accurately identifying the battery's true thermal runaway risk and improving the reliability and effectiveness of battery operation monitoring.

[0023] Step S3-3-2: When the current data obtained by adding the current data obtained by real-time collection and the current data obtained by the thermal runaway fluctuation correction value does not exceed the thermal runaway current monitoring threshold, the current data is added to the normal current reference set;

[0024] Step S3-4: Based on the data in the thermal runaway current analysis set, select the shortest interval between two sets of current fluctuation data to set the current monitoring time window;

[0025] Step S3-5: Obtain the operating current range specified for the battery through the technical documentation provided by the battery manufacturer or a certification report that complies with international standards, and select the minimum value of the operating current range as the minimum monitoring current of the current monitoring time window;

[0026] Step S3-6: Monitor the current data during battery operation through the current monitoring time window. When more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be abnormal; when no more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be normal.

[0027] By comprehensively applying thermal runaway fluctuation correction values ​​to dynamically screen real-time current data, and combining historical thermal runaway data with the battery to determine a unique current monitoring time window, the minimum value of the battery's specified operating current range is used as the key monitoring indicator. Its role is to build a sophisticated current monitoring system that fits the actual characteristics of the battery. In this way, it can effectively eliminate misjudgments caused by normal current fluctuations, accurately identify abnormal current conditions during battery operation, and achieve the effect of improving the accuracy and reliability of battery current monitoring, providing strong support for timely detection of potential battery faults and ensuring stable battery operation.

[0028] Step S4: When the current during battery operation is determined to be abnormal, the temperature accumulated energy of the battery is calculated based on the temperature data collected during battery operation;

[0029] The temperature gradient during battery operation is calculated based on the current curve. A dynamic temperature gradient model during battery operation is constructed in combination with the neural network model. The dynamic temperature gradient model is used to calculate the product of the battery current and the temperature gradient during battery operation and integrate the product to obtain the temperature accumulation energy of the battery. The calculation formula for the temperature accumulation energy is as follows:

[0030] ;

[0031] Where ET represents the temperature-accumulated energy of the battery; t represents the current time, the upper limit of integration; t0 represents the abnormal time, which serves as the lower limit of integration; Ti+1 represents the battery temperature at the previous moment; ti-1 represents the moment before the current moment t; I(t) represents the current value of the battery at time t; dt represents the differential of the integral variable t, a small increment in the time dimension.

[0032] Step S5: Perform a thermal runaway warning on the battery based on the battery's specified parameters and the temperature accumulated energy calculation result;

[0033] a temperature accumulation energy threshold is set by reading parameters specified by the battery, wherein the parameters specified by the battery include a specified operating temperature range and thermal management characteristics of the battery; when the value of the temperature accumulation energy calculated in step S4 exceeds the temperature accumulation energy threshold, a warning signal of abnormal battery operating temperature is issued; when the value of the calculated temperature accumulation energy does not exceed the temperature accumulation energy threshold, the operating temperature of the battery is within the specified operating temperature range, and the temperature generated by the battery operation continues to be monitored;

[0034] Set the temperature accumulation energy threshold according to the specified operating temperature range of the battery. The calculation formula is as follows:

[0035] ;

[0036] Where, Emax represents the temperature accumulation energy threshold of the battery; c represents the specific heat capacity of the battery; m represents the mass of the battery; Tmax represents the upper limit temperature of the specified operating temperature range of the battery; T0 represents the initial temperature of the battery;

[0037] A temperature accumulation energy threshold is set based on the battery's specified operating temperature range and thermal management characteristics. By comparing the calculated threshold with the temperature accumulation energy calculated in step S4, a thermal runaway warning is issued for the battery. This approach scientifically determines the warning threshold by combining physical properties such as the battery's specific heat capacity and mass with the specified operating temperature range. The result is precise monitoring of the battery's operating temperature. When the temperature accumulation energy exceeds the threshold, a timely warning signal is issued indicating abnormal battery operating temperature, enabling early detection of thermal runaway risks and preventing safety incidents. Continued monitoring ensures stable battery operation within the specified operating temperature range, improving battery safety and reliability while minimizing potential economic losses and safety hazards.

[0038] Furthermore, a battery operation management system based on multi-parameter fusion analysis includes a data acquisition module, a historical data analysis module, a current fluctuation analysis module, a current anomaly judgment module and a thermal runaway warning module;

[0039] The data acquisition module is responsible for collecting the battery's current and temperature data in real time; the historical data analysis module is used to analyze the battery's historical operating data, filter and construct a data set; the current fluctuation analysis module is used to analyze current fluctuations and extract the maximum fluctuation value; the current anomaly judgment module is used to judge whether the battery current is abnormal based on the current data and threshold; the thermal runaway warning module is used to issue a thermal runaway warning based on the temperature accumulated energy calculation result and the set threshold;

[0040] The output end of the data acquisition module is electrically connected to the input end of the historical data analysis module; the output end of the historical data analysis module is electrically connected to the input end of the current fluctuation analysis module; the output end of the current fluctuation analysis module is electrically connected to the input end of the current anomaly judgment module; the output end of the current anomaly judgment module is electrically connected to the input end of the thermal runaway warning module;

[0041] The data acquisition module includes a current data acquisition unit and a temperature data acquisition unit; the current data acquisition unit is used to acquire current data during battery operation; the temperature data acquisition unit is used to acquire temperature data during battery operation;

[0042] The historical data analysis module includes a current data screening unit and a thermal runaway current analysis set construction unit; the current data screening unit is used to screen current data that meets the thermal runaway current monitoring conditions; the thermal runaway current analysis set construction unit is used to construct a thermal runaway current data set according to the screening conditions;

[0043] The current fluctuation analysis module includes a current fluctuation maximum value extraction unit and a current anomaly analysis and correction unit; the current fluctuation maximum value extraction unit is used to extract the maximum value in the current fluctuation data; the current anomaly analysis and correction unit is used to correct the thermal runaway current data set and identify current anomalies;

[0044] The current abnormality judgment module includes a temperature gradient calculation unit and a temperature accumulation energy calculation unit; the temperature gradient calculation unit is used to calculate the temperature change rate of the battery during operation; the temperature accumulation energy calculation unit is used to calculate the temperature accumulation energy of the battery based on the temperature gradient;

[0045] The thermal runaway warning module includes a temperature accumulation energy threshold setting unit and a thermal runaway warning unit; the temperature accumulation energy threshold setting unit is used to set the temperature accumulation energy threshold according to the operating parameters of the battery; the thermal runaway warning unit is used to issue a thermal runaway warning signal when the temperature accumulation energy exceeds the threshold.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. This invention closely matches the actual operating characteristics of the battery by scientifically setting the thermal runaway current monitoring threshold and classifying historical operating data. Using the most frequently occurring current value in the current curve as the threshold reduces misjudgments and improves the accuracy of thermal runaway risk assessment. Simultaneously, a thermal runaway current analysis set and a normal current reference set are formed, facilitating subsequent in-depth analysis of the battery's current characteristics under different operating conditions.

[0048] 2. This invention effectively eliminates interference from normal current fluctuations by analyzing and correcting current fluctuation data and establishing a current monitoring time window. By using the thermal runaway fluctuation correction value to filter real-time current data and combining it with historical thermal runaway data to determine the monitoring time window, and using the minimum value of the operating current range as the monitoring indicator, it can accurately identify abnormal currents during battery operation, greatly improving the reliability and effectiveness of battery current monitoring.

[0049] 3. This invention achieves precise monitoring of battery operating temperature by combining battery physical characteristics with specified parameters to calculate the temperature-accumulated energy threshold and provide thermal runaway warnings. The threshold is determined based on the battery's specific heat capacity, mass, and operating temperature range, and compared with the actual temperature-accumulated energy. A timely warning is issued when the threshold is exceeded, identifying thermal runaway risks in advance and ensuring stable battery operation within the specified temperature range, reducing potential losses and safety hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of a battery operation management method based on multi-parameter fusion analysis according to the present invention;

[0051] Figure 2 This is a structural diagram of a battery operation management system based on multi-parameter fusion analysis of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] Example 1: Figure 1 As shown, the present invention provides a technical solution, a battery operation management method based on multi-parameter fusion analysis, and the battery operation management method includes the following steps:

[0054] Step S1, collecting current data and temperature data of the battery during operation, and setting a thermal runaway current monitoring threshold for the battery based on the specified operating temperature range of the battery and the current curve analysis;

[0055] Step S1-1, obtaining current data of the battery during operation through a battery management system, wherein the current data is expressed as the current value generated by the battery during operation, including the charging current value and the discharging current value; and obtaining temperature data of the battery during operation through a temperature sensor;

[0056] Step S1-2: Obtain the specified operating temperature range of the battery through technical documents provided by the battery manufacturer or certification reports that comply with international standards;

[0057] Step S1-3: constructing a current curve graph based on the current data acquired by the battery management system and the time series of the current data acquisition, wherein the current curve graph represents the changing trend of the battery current during operation by matching the current value at each time point with the corresponding time tag;

[0058] Step S1-4: Calculate the frequency of occurrence of each current value based on the current values ​​in the current curve graph, select the current value with the highest frequency of occurrence to set the battery's thermal runaway current monitoring threshold, and the thermal runaway current monitoring threshold is used to determine whether the battery meets the current monitoring condition.

[0059] During implementation, the battery parameters are first read to obtain the specified operating temperature and current ranges. Next, the battery management system is used to obtain the battery's operating current data, while the temperature sensor is used to obtain the battery's operating temperature data. Based on the current data and the acquired time series, a current curve is constructed that clearly shows the changing trend of the battery current during operation. Next, based on the current values ​​in the current curve, the frequency of each current value is calculated. The current value with the highest frequency of occurrence is selected as the battery's thermal runaway current monitoring threshold to determine whether the battery has met the current monitoring conditions.

[0060] Step S2: Acquire historical operating data of the battery, the historical operating data including current data and current fluctuation data during historical operation of the battery, filter the historical operating data in combination with a thermal runaway current monitoring threshold, store the historical operating data that meets the screening criteria to form a thermal runaway current analysis set, and store the historical operating data that does not meet the screening criteria to form a normal current reference set;

[0061] Obtain historical current data and current fluctuation data of the battery, wherein the current fluctuation data represents the current value caused by current fluctuation due to interference with the battery; judge current data greater than the thermal runaway current monitoring threshold as meeting the screening conditions, and form a thermal runaway current analysis set by storing current data that meet the screening conditions; and form a normal current reference set by storing current data that does not meet the screening conditions.

[0062] In specific implementations, the battery's historical operating data is first obtained from the battery management system or related data storage device. This historical operating data includes the battery's historical operating current data as well as current fluctuations caused by interference. The acquired historical operating data is then compared one by one using the set thermal runaway current monitoring threshold as a screening criterion. Current data exceeding the thermal runaway current monitoring threshold is determined to meet the screening criteria and stored to form a thermal runaway current analysis set. Data that does not meet the screening criteria is stored together to form a normal current reference set.

[0063] Step S3: extracting current fluctuation data from the thermal runaway current analysis set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation abnormality determination benchmark; extracting current fluctuation data from the normal current reference set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation correction value; correcting the data in the thermal runaway current analysis set based on the current data collected during battery operation in combination with the thermal runaway fluctuation correction value, and determining whether the battery current is abnormal during operation based on the current data collected during battery operation in combination with the thermal runaway fluctuation abnormality determination benchmark;

[0064] Step S3-1, traversing and reading the current fluctuation data in the thermal runaway current analysis set, processing the current fluctuation data using a bubble sort method, and screening out the maximum current fluctuation value as a thermal runaway fluctuation abnormality determination criterion, wherein the thermal runaway fluctuation abnormality determination criterion is represented by the maximum value of the current fluctuation data that meets the thermal runaway current monitoring threshold in the battery history;

[0065] Step S3-2: traverse and read the current fluctuation data in the normal current reference set, process the current fluctuation data using a bubble sort method, and select the maximum value of the current fluctuation as the thermal runaway fluctuation correction value;

[0066] Step S3-3: collect the current data of the battery in real time during operation, and modify the thermal runaway current analysis set in combination with the thermal runaway fluctuation correction value. The modification process is as follows:

[0067] Step S3-3-1: When the current data collected in real time plus the current data of the thermal runaway fluctuation correction value exceeds the thermal runaway current monitoring threshold, the current data exceeding the thermal runaway current monitoring threshold is highlighted:

[0068] When the current data transiently exceeds the thermal runaway current monitoring threshold due to fluctuations but does not continuously exceed the threshold, the current data does not meet the conditions for inclusion in the thermal runaway current analysis set and is added to the normal current reference set.

[0069] When the collected current data continuously exceeds the thermal runaway current monitoring threshold, the condition for joining the thermal runaway current analysis set is met, and the current data is added to the thermal runaway current analysis set;

[0070] Step S3-3-2: When the current data obtained by adding the current data obtained by real-time collection and the current data obtained by the thermal runaway fluctuation correction value does not exceed the thermal runaway current monitoring threshold, the current data is added to the normal current reference set;

[0071] Step S3-4: Based on the data in the thermal runaway current analysis set, select the shortest interval between two sets of current fluctuation data to set the current monitoring time window;

[0072] Step S3-5: Obtain the operating current range specified for the battery through the technical documentation provided by the battery manufacturer or a certification report that complies with international standards, and select the minimum value of the operating current range as the minimum monitoring current of the current monitoring time window;

[0073] Step S3-6, monitor the current data of the battery during operation through the current monitoring time window. When more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be abnormal; when no more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be normal.

[0074] In the specific implementation, the current fluctuation data with the largest current fluctuation in the thermal runaway current analysis set and the normal current reference set is selected as the benchmark. When the battery is running, the current fluctuation may reach a value. The current fluctuation data extracted from the normal current reference set is used to judge whether the current fluctuation exceeds the set thermal runaway current monitoring threshold. If it is only a momentary fluctuation, it is judged that it does not meet the requirements for joining the thermal runaway current analysis set, reducing redundant data in the thermal runaway current analysis set. When the fluctuation exceeds the set thermal runaway current monitoring threshold, the current data is highlighted for monitoring. When the current data continuously exceeds the set thermal runaway current monitoring threshold, the conditions for joining the thermal runaway current analysis set are met, and the monitored current data of this part is added to the thermal runaway current analysis set. When the current data meets the set thermal runaway current monitoring threshold, the current fluctuation data with the largest current fluctuation value in the thermal runaway current analysis set is extracted as the benchmark, and the current monitoring time window is set according to the minimum time interval of the current fluctuation, and the minimum monitoring current is set according to the working current range specified by the battery to monitor the battery.

[0075] Step S4: When the current during battery operation is determined to be abnormal, the temperature accumulated energy of the battery is calculated based on the temperature data collected during battery operation;

[0076] The temperature gradient of the battery during operation is calculated based on the current curve, and a dynamic temperature gradient model of the battery during operation is constructed in combination with the neural network model. The product of the current and the temperature gradient during battery operation is calculated through the dynamic temperature gradient model and integrated to obtain the temperature accumulation energy of the battery.

[0077] Step S5: Perform a thermal runaway warning on the battery according to the battery's specified parameters and the temperature-accumulated energy calculation result.

[0078] Setting a temperature accumulation energy threshold by reading battery-specified parameters, wherein the battery-specified parameters include a specified operating temperature range and thermal management characteristics of the battery;

[0079] When the value of the temperature accumulated energy calculated in step S4 exceeds the temperature accumulated energy threshold, a warning signal indicating abnormal battery operating temperature is issued;

[0080] When the calculated value of the temperature accumulated energy does not exceed the temperature accumulated energy threshold, the operating temperature of the battery meets the prescribed operating temperature range, and the temperature generated by the battery operation continues to be monitored.

[0081] In specific implementation, when the battery operating current is judged to be abnormal after current data processing and analysis, the battery temperature needs to be further analyzed. First, the temperature gradient during battery operation is calculated based on the previously constructed current curve graph, and a dynamic temperature gradient model is constructed in combination with the neural network model. When the current is abnormal, the chemical reactions and internal resistance inside the battery will change, which may cause the battery heat generation rate to accelerate. For example, if an abnormal condition such as a short circuit occurs inside the battery, the current will increase sharply, the Joule heat of the battery will increase significantly, and the battery temperature will rise rapidly. At this time, the dynamic temperature gradient model is used to calculate the product of the battery operating current and the temperature gradient and integrate it to obtain the temperature accumulation energy generated when the battery current data begins to become abnormal. By judging this temperature accumulation energy, the judgment result of the current abnormality can be further accurately analyzed, the operating status of the battery can be more accurately assessed, and potential risks such as thermal runaway can be warned in advance.

[0082] Example 2, as Figure 2 As shown, the present invention provides a battery operation management system based on multi-parameter fusion analysis, which includes a data acquisition module, a historical data analysis module, a current fluctuation analysis module, a current anomaly judgment module and a thermal runaway warning module;

[0083] The data acquisition module is responsible for collecting the battery's current and temperature data in real time; the historical data analysis module is used to analyze the battery's historical operating data, filter and construct a data set; the current fluctuation analysis module is used to analyze current fluctuations and extract the maximum fluctuation value; the current anomaly judgment module is used to judge whether the battery current is abnormal based on the current data and threshold; the thermal runaway warning module is used to issue a thermal runaway warning based on the temperature accumulated energy calculation result and the set threshold;

[0084] The output end of the data acquisition module is electrically connected to the input end of the historical data analysis module; the output end of the historical data analysis module is electrically connected to the input end of the current fluctuation analysis module; the output end of the current fluctuation analysis module is electrically connected to the input end of the current anomaly judgment module; the output end of the current anomaly judgment module is electrically connected to the input end of the thermal runaway warning module;

[0085] The data acquisition module includes a current data acquisition unit and a temperature data acquisition unit; the current data acquisition unit is used to acquire current data during battery operation; the temperature data acquisition unit is used to acquire temperature data during battery operation;

[0086] The historical data analysis module includes a current data screening unit and a thermal runaway current analysis set construction unit; the current data screening unit is used to screen current data that meets the thermal runaway current monitoring conditions; the thermal runaway current analysis set construction unit is used to construct a thermal runaway current data set according to the screening conditions;

[0087] The current fluctuation analysis module includes a current fluctuation maximum value extraction unit and a current anomaly analysis and correction unit; the current fluctuation maximum value extraction unit is used to extract the maximum value in the current fluctuation data; the current anomaly analysis and correction unit is used to correct the thermal runaway current data set and identify current anomalies;

[0088] The current abnormality judgment module includes a temperature gradient calculation unit and a temperature accumulation energy calculation unit; the temperature gradient calculation unit is used to calculate the temperature change rate of the battery during operation; the temperature accumulation energy calculation unit is used to calculate the temperature accumulation energy of the battery based on the temperature gradient;

[0089] The thermal runaway warning module includes a temperature accumulation energy threshold setting unit and a thermal runaway warning unit; the temperature accumulation energy threshold setting unit is used to set the temperature accumulation energy threshold according to the operating parameters of the battery; the thermal runaway warning unit is used to issue a thermal runaway warning signal when the temperature accumulation energy exceeds the threshold.

[0090] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A battery operation management method based on multi-parameter fusion analysis, characterized by: The battery operation management method comprises the following steps: Step S1, collecting current data and temperature data of the battery during operation, and setting a thermal runaway current monitoring threshold for the battery based on the specified operating temperature range of the battery and the current curve analysis; Step S2: Acquire historical operating data of the battery, the historical operating data including current data and current fluctuation data during historical operation of the battery, filter the historical operating data in combination with a thermal runaway current monitoring threshold, store the historical operating data that meets the screening criteria to form a thermal runaway current analysis set, and store the historical operating data that does not meet the screening criteria to form a normal current reference set; Step S3: extracting current fluctuation data from the thermal runaway current analysis set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation abnormality determination benchmark; extracting current fluctuation data from the normal current reference set for analysis, and screening out the maximum value of the current fluctuation as a thermal runaway fluctuation correction value; correcting the data in the thermal runaway current analysis set based on the current data collected during battery operation in combination with the thermal runaway fluctuation correction value, and determining whether the battery current is abnormal during operation based on the current data collected during battery operation in combination with the thermal runaway fluctuation abnormality determination benchmark; When the current data collected in real time plus the current data of the thermal runaway fluctuation correction value exceeds the thermal runaway current monitoring threshold, the current data exceeding the thermal runaway current monitoring threshold is highlighted: When the current data exceeds the thermal runaway current monitoring threshold momentarily due to fluctuations but does not continuously exceed the threshold, the current data does not meet the conditions for inclusion in the thermal runaway current analysis set and is added to the normal current reference set. When the collected current data continuously exceeds the thermal runaway current monitoring threshold, the condition for joining the thermal runaway current analysis set is met, and the current data is added to the thermal runaway current analysis set; When the current data collected in real time plus the current data of the thermal runaway fluctuation correction value does not exceed the thermal runaway current monitoring threshold, the current data is added to the normal current reference set; Step S4: When the current during battery operation is determined to be abnormal, the temperature accumulated energy of the battery is calculated based on the temperature data collected during battery operation; Step S5: Perform a thermal runaway warning on the battery according to the battery's specified parameters and the temperature-accumulated energy calculation result.

2. The battery operation management method based on multi-parameter fusion analysis according to claim 1 is characterized in that: The specific steps of step S1 are as follows: Step S1-1, obtaining current data of the battery during operation through a battery management system, wherein the current data is expressed as the current value generated by the battery during operation, including the charging current value and the discharging current value; and obtaining temperature data of the battery during operation through a temperature sensor; Step S1-2: Obtain the specified operating temperature range of the battery through technical documents provided by the battery manufacturer or certification reports that comply with international standards; Step S1-3: constructing a current curve graph based on the current data acquired by the battery management system and the time series of the current data acquisition, wherein the current curve graph represents the changing trend of the battery current during operation by matching the current value at each time point with the corresponding time tag; Step S1-4: Calculate the frequency of occurrence of each current value based on the current values ​​in the current curve graph, select the current value with the highest frequency of occurrence to set the battery's thermal runaway current monitoring threshold, and the thermal runaway current monitoring threshold is used to determine whether the battery meets the current monitoring condition.

3. The battery operation management method based on multi-parameter fusion analysis according to claim 2 is characterized in that: In step S2, historical current data and current fluctuation data of the battery are obtained, wherein the current fluctuation data represents the current value of the battery causing the current to fluctuate due to interference; Determining current data greater than a thermal runaway current monitoring threshold as meeting a screening condition, and forming a thermal runaway current analysis set by storing the current data meeting the screening condition; A normal current reference set is formed by storing current data that does not meet the screening conditions.

4. The battery operation management method based on multi-parameter fusion analysis according to claim 3 is characterized in that: The specific steps of step S3 are as follows: Step S3-1, traversing and reading the current fluctuation data in the thermal runaway current analysis set, processing the current fluctuation data using a bubble sort method, and screening out the maximum current fluctuation value as a thermal runaway fluctuation abnormality determination criterion, wherein the thermal runaway fluctuation abnormality determination criterion is represented by the maximum value of the current fluctuation data that meets the thermal runaway current monitoring threshold in the battery history; Step S3-2: traverse and read the current fluctuation data in the normal current reference set, process the current fluctuation data using a bubble sort method, and select the maximum value of the current fluctuation as the thermal runaway fluctuation correction value.

5. The battery operation management method based on multi-parameter fusion analysis according to claim 4 is characterized in that: In step S3, it also includes: Step S3-3: collecting the current data of the battery in real time during operation, and correcting the thermal runaway current analysis set in combination with the thermal runaway fluctuation correction value; Step S3-4: Based on the data in the thermal runaway current analysis set, select the shortest interval between two sets of current fluctuation data to set the current monitoring time window; Step S3-5: Obtain the operating current range specified for the battery through the technical documentation provided by the battery manufacturer or a certification report that complies with international standards, and select the minimum value of the operating current range as the minimum monitoring current of the current monitoring time window; Step S3-6, monitor the current data of the battery during operation through the current monitoring time window. When more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be abnormal; when no more than one group of current data appears in the current monitoring time window, the current data of the current battery operation is judged to be normal.

6. The battery operation management method based on multi-parameter fusion analysis according to claim 5 is characterized in that: In step S4, the temperature gradient during battery operation is calculated based on the current curve graph, and a dynamic temperature gradient model during battery operation is constructed in combination with the neural network model. The product of the current and the temperature gradient during battery operation is calculated by the dynamic temperature gradient model and integrated to obtain the temperature accumulation energy of the battery.

7. The battery operation management method based on multi-parameter fusion analysis according to claim 6 is characterized in that: In step S5, a temperature accumulation energy threshold is set by reading the parameters specified by the battery, wherein the parameters specified by the battery include the specified operating temperature range and thermal management characteristics of the battery; when the value of the temperature accumulation energy calculated in step S4 exceeds the temperature accumulation energy threshold, a warning signal of abnormal battery operating temperature is issued; when the value of the calculated temperature accumulation energy does not exceed the temperature accumulation energy threshold, the temperature of the battery during operation is within the specified operating temperature range, and the temperature generated by the battery operation continues to be monitored.

8. A battery operation management system based on multi-parameter fusion analysis, applied to the battery operation management method based on multi-parameter fusion analysis according to any one of claims 1 to 7, characterized in that: The battery operation management system includes a data acquisition module, a historical data analysis module, a current fluctuation analysis module, a current anomaly judgment module and a thermal runaway warning module; The data acquisition module is responsible for collecting the current and temperature data of the battery in real time; the historical data analysis module is used to analyze the historical operation data of the battery, filter and construct a data set; The current fluctuation analysis module is used to analyze the current fluctuation and extract the maximum fluctuation value; The current abnormality judgment module is used to judge whether the battery current is abnormal based on the current data and the threshold; The thermal runaway warning module is used to issue a thermal runaway warning based on the temperature accumulation energy calculation result and the set threshold; The output end of the data acquisition module is electrically connected to the input end of the historical data analysis module; the output end of the historical data analysis module is electrically connected to the input end of the current fluctuation analysis module; the output end of the current fluctuation analysis module is electrically connected to the input end of the current anomaly judgment module; the output end of the current anomaly judgment module is electrically connected to the input end of the thermal runaway warning module.

9. The battery operation management system based on multi-parameter fusion analysis according to claim 8, characterized in that: The data acquisition module includes a current data acquisition unit and a temperature data acquisition unit; the current data acquisition unit is used to acquire current data during battery operation; the temperature data acquisition unit is used to acquire temperature data during battery operation; The historical data analysis module includes a current data screening unit and a thermal runaway current analysis set construction unit; the current data screening unit is used to screen current data that meets the thermal runaway current monitoring conditions; the thermal runaway current analysis set construction unit is used to construct a thermal runaway current data set according to the screening conditions; The current fluctuation analysis module includes a current fluctuation maximum value extraction unit and a current anomaly analysis and correction unit; the current fluctuation maximum value extraction unit is used to extract the maximum value in the current fluctuation data; The current anomaly analysis and correction unit is used to correct the thermal runaway current data set and identify current anomalies.

10. The battery operation management system based on multi-parameter fusion analysis according to claim 8, characterized in that: The current anomaly judgment module includes a temperature gradient calculation unit and a temperature accumulation energy calculation unit; The temperature gradient calculation unit is used to calculate the temperature change rate of the battery during operation; the temperature accumulation energy calculation unit is used to calculate the temperature accumulation energy of the battery based on the temperature gradient; The thermal runaway warning module includes a temperature accumulation energy threshold setting unit and a thermal runaway warning unit; the temperature accumulation energy threshold setting unit is used to set the temperature accumulation energy threshold according to the operating parameters of the battery; the thermal runaway warning unit is used to issue a thermal runaway warning signal when the temperature accumulation energy exceeds the threshold.

Images