Method for detecting degradation and variation of electricity storage performance of energy storage battery

Abstract

The invention discloses a power storage performance attenuation and variation detection method for an energy storage battery, and relates to the field of energy storage batteries. The method comprises the following steps: deploying a terahertz time-domain spectroscopy system and a microphone array on the surface of the energy storage battery, based on a terahertz time-domain spectroscopy system and a microphone array, acquiring a three-dimensional imaging map and a voiceprint signal of the energy storage battery at the beginning stage of charging the energy storage battery each time; creating a cloud database, and storing the three-dimensional imaging map and the voiceprint signal of the energy storage battery by using the cloud database; according to the method, terahertz time-domain spectrum three-dimensional imaging and voiceprint signal bimodal data are fused, battery global information acquisition is realized through distributed array scanning and matrix deployment, and a multi-dimensional attenuation evaluation model is constructed by combining dynamic storage and comparative analysis of a cloud database, so that the accuracy of battery attenuation evaluation is improved. A dynamic weight adjustment mechanism and ontology state information correction are introduced, so that the attenuation index estimation precision is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage batteries, and in particular to a method for detecting abnormal changes in the storage performance attenuation of energy storage batteries. Background Art

[0002] Energy storage battery performance degradation refers to the phenomenon of capacity loss and reduced charge and discharge efficiency over time as charge and discharge cycles progress. This is primarily due to electrode material loss, electrolyte decomposition, and dendrite growth, which impacts battery life and reliability.

[0003] The invention patent application with application number 202411087168.0 discloses a performance detection method for an energy storage battery, the method comprising: interactively obtaining calibrated charge and discharge parameters of a target energy storage battery, and matching a test scenario set based on the calibrated charge and discharge parameters; performing multi-scenario testing on the target energy storage battery through the test scenario set, collecting test data during the test process, and obtaining a test data set, wherein the test data set includes current data and voltage data; performing charge and discharge deviation analysis on the test data set based on the calibrated charge and discharge parameters, and generating a charge and discharge deviation coefficient set; extracting a current data set based on the test data set, wherein the current data set is sorted according to timestamps; and The current data set is used to evaluate the current stability of the test process to generate a current stability coefficient set; based on the test scenario set, the charge and discharge deviation coefficient set and the current stability coefficient set are integrated to generate a charge and discharge evaluation result, wherein the charge and discharge evaluation result is used to characterize the charge and discharge performance of the target energy storage battery. This application aims to solve the problem that "the battery performance detection method in the prior art is often limited to a single test scenario or a simple charge and discharge test, and cannot comprehensively evaluate the performance of the battery in different actual application scenarios, thereby resulting in inaccurate performance evaluation results; and, battery performance testing usually generates a large amount of data, and the prior art lacks effective data processing and analysis methods, which makes it difficult to accurately evaluate the comprehensive performance of the battery."

[0004] However, existing technologies for detecting energy storage battery performance degradation and abnormal changes still mostly rely on the data collected during the battery's charge and discharge process, which limits the accuracy of detection. Therefore, a method for detecting storage performance degradation of energy storage batteries is proposed. Summary of the Invention

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method for detecting the degradation and abnormal variation of the storage performance of an energy storage battery, which can effectively solve the problems of the prior art.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention discloses a method for detecting storage performance degradation and abnormal variation of an energy storage battery, comprising: A terahertz time-domain spectroscopy system and a microphone array are deployed on the surface of the energy storage battery, and based on the terahertz time-domain spectroscopy system and the microphone array, a three-dimensional imaging map and a voiceprint signal of the energy storage battery are collected at the beginning of each energy storage battery charging stage; a cloud database is created, and the three-dimensional imaging map and the voiceprint signal of the energy storage battery are stored in the cloud database; the energy storage performance attenuation rate of the energy storage battery is evaluated respectively according to the three-dimensional imaging map and the voiceprint signal of the energy storage battery stored in the cloud database; the energy storage performance attenuation rate evaluation results of the energy storage battery corresponding to the three-dimensional imaging map and the voiceprint signal of the energy storage battery are obtained, and the energy storage performance attenuation index of the energy storage battery is comprehensively estimated based on the two evaluation results; the energy storage battery body state information collected during the collection process of the three-dimensional imaging map and the voiceprint signal of the energy storage battery is used to correct the energy storage performance attenuation index of the energy storage battery; the correction results of the energy storage performance attenuation index of each energy storage battery are recorded, and a threshold for determining the abnormality of the energy storage performance attenuation of the energy storage battery is set. When the difference between the correction results of two adjacent records exceeds the threshold for determining the abnormality of the energy storage performance attenuation of the energy storage battery, it is determined that there is an abnormality in the energy storage performance attenuation of the energy storage battery.

[0007] Furthermore, the terahertz time-domain spectroscopy system, when deployed on the surface of an energy storage battery, complies with: A distributed array scanning architecture is used, with no fewer than two sets of terahertz transmitting / receiving probes installed on the top and side surfaces of the energy storage battery. The probes are fixed 10 to 15 cm from the battery casing via adjustable brackets. The transmitting end uses a fiber-coupled terahertz pulse source, and the receiving end is equipped with a high-sensitivity Schottky diode detector. The probes operate synchronously, and the probe scanning path moves along a preset serpentine trajectory, with a single scan covering more than 90% of the casing area. When the microphone array is deployed on the surface of the energy storage battery, it complies with: Microphones are deployed in a matrix along the long sides and top of the energy storage battery. Microphones are fixed on each side in a 3×3 or 4×4 array. The microphones deployed in the matrix avoid all interference sources, including the energy storage battery heat dissipation holes and wiring terminals. The microphones are at least 5 cm away from the battery heat dissipation holes and at least 15 cm away from the wiring terminals. Among them, the microphone array is equipped with a synchronous clock, and each microphone in the microphone array operates synchronously through the synchronous clock. The continuous collection time of the three-dimensional imaging map of the energy storage battery and the voiceprint signal each time is fixed and unified.

[0008] Furthermore, when storing the three-dimensional imaging map and voiceprint signal of the energy storage battery, the cloud database marks the collection timestamp for each three-dimensional imaging map and voiceprint signal of the energy storage battery, and the cloud database sorts and stores the three-dimensional imaging map and voiceprint signal of the energy storage battery based on the marked content; The energy storage battery three-dimensional imaging map and voiceprint signal acquisition process synchronously collect the energy storage battery body state information, including: charging curve inflection point slope, temperature field gradient change rate; Among them, the status information of the energy storage battery itself is sent synchronously to the cloud database, and is bound and stored with the corresponding energy storage battery three-dimensional imaging map and voiceprint signal based on the acquisition time.

[0009] Furthermore, when there are at least two sets of three-dimensional imaging maps and voiceprint signals of the energy storage battery stored in the cloud database, the evaluation operation of the energy storage battery storage performance attenuation rate is performed once each time the three-dimensional imaging maps and voiceprint signals of the energy storage battery are updated and stored. When evaluating the energy storage battery storage performance attenuation rate, the latest two sets of three-dimensional imaging maps and voiceprint signals of the energy storage battery are retrieved from the cloud database; The energy storage battery storage performance attenuation rate is evaluated by the three-dimensional imaging atlas of the energy storage battery and is subject to the following conditions: ; Where: is the decay rate; is the maximum dielectric constant difference of the battery core area in the two imagings; It is the standard dielectric constant benchmark value of new energy storage batteries; The effective volume of the battery active material is calculated by spatially reconstructing two three-dimensional imaging maps; It is a new energy storage battery active material volume benchmark; is the total number of global voxels in the 3D imaging atlas; is the terahertz energy response value of the i-th voxel in the two imagings; The energy baseline value of the corresponding voxel of the new energy storage battery; in, The calculation logic is the same. The calculation is as follows: ; Where: is the number of active substance voxels in the three-dimensional imaging atlas; is the three-dimensional volume of the j-th voxel; It is an indicator function, which takes the value 1 if the condition in the brackets is met, otherwise it takes the value 0; is the dielectric constant of the jth voxel in the latest imaging; is the dielectric constant threshold of the active material.

[0010] Furthermore, the energy storage battery storage performance attenuation rate is evaluated by the voiceprint signal and obeys: ; Where: is the decay rate; are the energy attenuation coefficient, frequency distortion rate, and complexity imbalance index; is the total energy of the two voiceprint signals at the initial stage of charging; The peak frequencies of the two voiceprint signals in the 500Hz-2kHz frequency range; is the complexity of the two voiceprint signals; in, , the initial stage of charging is defined as 0~10 seconds.

[0011] Furthermore, the energy storage battery storage performance attenuation index estimation logic is: ; Where: is the energy storage performance attenuation index of the energy storage battery; is the weight; Among them, the weight The sum is 1 and all are positive numbers, the weight The configuration has dynamic value adjustment logic: When the fluctuation amplitude of the three-dimensional imaging atlas evaluation results for three consecutive times is smaller than the voiceprint signal, The value is set to 0.6-0.7, The corresponding value is 0.3-0.4; otherwise, Take 0.6-0.7, Take 0.3-0.4. At the same time, combined with the maximum slope of the charging curve inflection point in the collected energy storage battery status information, if the absolute value of this slope exceeds 20% of the standard value of a new battery, the weight of the one with the higher current weight will be reduced by 0.1, and the other weight will be increased by 0.1 accordingly.

[0012] Furthermore, the correction logic of the energy storage battery storage performance attenuation index is expressed as: ; Where: is the proportionality coefficient; The maximum slope of the inflection point of the energy storage battery charging curve; is the average slope of the inflection point of the energy storage battery charging curve; The minimum and maximum values ​​of the temperature field gradient change rate when the energy storage battery is charging; in, The sum is 1 and both are greater than zero, and when the energy storage battery is fast charged, a<b, and when the energy storage battery is normally charged, a≥b.

[0013] Furthermore, when recording the correction results of the energy storage battery power storage performance attenuation index, each correction result of the energy storage battery power storage performance attenuation index is marked with a corresponding correction timestamp, and the correction results of the energy storage battery power storage performance attenuation index are sorted based on the timestamps marked to form a list of correction results of the energy storage battery power storage performance attenuation index; Wherein, each time the energy storage battery storage performance attenuation index correction result list updates the energy storage battery storage performance attenuation index correction result, the determination operation of whether the energy storage battery storage performance attenuation is abnormal is performed once.

[0014] Furthermore, when the storage performance of the energy storage battery is determined to be abnormal, the energy storage battery ends the current charging task and feeds back the three-dimensional imaging map and voiceprint signal currently collected by the energy storage battery to the energy storage battery management end user.

[0015] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: The present invention provides a method for detecting abnormal attenuation of the storage performance of energy storage batteries. During execution, the method integrates terahertz time-domain spectroscopy three-dimensional imaging and voiceprint signal bimodal data, and realizes full-domain battery information collection through distributed array scanning and matrix deployment. Combined with dynamic storage and comparative analysis of cloud databases, a multi-dimensional attenuation assessment model is constructed. The dynamic weight adjustment mechanism and body state information correction introduced by the method significantly improve the accuracy of attenuation index estimation, and is adaptable to different scenarios such as fast charging and conventional charging. At the same time, through the adjacent data difference threshold judgment, it can capture sudden changes in storage performance in real time, provide early warning of abnormal attenuation, effectively avoid the risk of battery failure, extend the service life, and provide safety monitoring protection for energy storage batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0017] Figure 1 The present invention is a flow chart of a method for detecting the degradation and abnormal variation of the storage performance of an energy storage battery. DETAILED DESCRIPTION

[0018] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. 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.

[0019] The present invention will be further described below with reference to the embodiments.

[0020] Example: A method for detecting the degradation and abnormal change of the storage performance of an energy storage battery in this embodiment is as follows: Figure 1 Shown, including: Deploy a terahertz time-domain spectroscopy system and a microphone array on the surface of the energy storage battery to collect the three-dimensional imaging map and voiceprint signal of the energy storage battery at the beginning of each energy storage battery charging stage based on the terahertz time-domain spectroscopy system and the microphone array; When deployed on the surface of energy storage batteries, the terahertz time-domain spectroscopy system complies with: A distributed array scanning architecture is used, with no fewer than two sets of terahertz transmitting / receiving probes installed on the top and side surfaces of the energy storage battery. The probes are fixed 10 to 15 cm from the battery casing via adjustable brackets. The transmitting end uses a fiber-coupled terahertz pulse source, and the receiving end is equipped with a high-sensitivity Schottky diode detector. The probes operate synchronously, and the probe scanning path moves along a preset serpentine trajectory, with a single scan covering more than 90% of the casing area. When the microphone array is deployed on the surface of the energy storage battery, it complies with: Microphones are deployed in a matrix pattern along the long sides and top of the energy storage battery. Microphones are fixed on each side in a 3×3 or 4×4 array. The matrix-deployed microphones avoid all interference sources, including the energy storage battery cooling holes and wiring terminals. Microphones must be at least 5 cm away from the battery cooling holes and at least 15 cm away from the wiring terminals. The microphone array is equipped with a synchronous clock, and each microphone in the microphone array operates synchronously through the synchronous clock. The continuous acquisition time of the energy storage battery three-dimensional imaging map and voiceprint signal each time is fixed and unified; When storing the three-dimensional imaging map and voiceprint signal of the energy storage battery, the cloud database marks the collection timestamp of each three-dimensional imaging map and voiceprint signal of the energy storage battery, and the cloud database sorts and stores them based on the marked content of the three-dimensional imaging map and voiceprint signal of the energy storage battery; During the acquisition of the energy storage battery's three-dimensional imaging map and voiceprint signal, the energy storage battery's body status information is collected synchronously, including: the slope of the charging curve inflection point and the temperature field gradient change rate; Among them, the energy storage battery status information is synchronously sent to the cloud database and stored in conjunction with the corresponding energy storage battery three-dimensional imaging map and voiceprint signal based on the acquisition time; Create a cloud database and use it to store the three-dimensional imaging maps and voiceprint signals of energy storage batteries; The energy storage battery's power storage performance attenuation rate is evaluated based on the three-dimensional imaging map and voiceprint signal of the energy storage battery stored in the cloud database; The evaluation of the energy storage battery's power storage performance attenuation rate is performed when there are at least two sets of three-dimensional imaging maps and voiceprint signals of the energy storage battery stored in the cloud database. The evaluation is performed once each time the three-dimensional imaging maps and voiceprint signals of the energy storage battery are updated and stored. When evaluating the energy storage battery's power storage performance attenuation rate, the latest two sets of three-dimensional imaging maps and voiceprint signals of the energy storage battery are retrieved from the cloud database. The energy storage battery storage performance attenuation rate is evaluated by the three-dimensional imaging map of the energy storage battery and follows: ; Where: is the decay rate; is the maximum dielectric constant difference of the battery core area in the two imagings; It is the standard dielectric constant benchmark value of new energy storage batteries; The effective volume of the battery active material is calculated by spatially reconstructing two three-dimensional imaging maps; It is a new energy storage battery active material volume benchmark; is the total number of global voxels in the 3D imaging atlas; is the terahertz energy response value of the i-th voxel in the two imagings; The energy baseline value of the corresponding voxel of the new energy storage battery; The above formula is based on continuously acquired three-dimensional imaging maps, integrating the maximum dielectric constant difference in the core area of ​​the battery, the change in the effective volume of the active material, and the difference in the voxel terahertz energy response. It is compared with the new battery benchmark value to calculate the decay rate. The multi-dimensional integration of the microscopic characteristics of terahertz imaging overcomes the limitations of single-metric evaluation and achieves accurate quantification of energy storage performance degradation, thereby improving the comprehensiveness and sensitivity of the assessment. in, The calculation logic is the same as For example: ; Where: is the number of active substance voxels in the three-dimensional imaging atlas; is the three-dimensional volume of the j-th voxel; It is an indicator function, which takes the value 1 if the condition in the brackets is met, otherwise it takes the value 0; is the dielectric constant of the jth voxel in the latest imaging; is the dielectric constant threshold of the active material; It should be noted that corresponds to the number of voxels representing the battery's active material, and Different from , used to represent the number of global voxels in the three-dimensional imaging atlas; active material voxels refer to voxels whose dielectric constant exceeds the set threshold, representing the active material area inside the battery that participates in the electrochemical reaction; and global voxels refer to all voxels in the entire three-dimensional imaging atlas, including all material areas such as active materials, electrolytes, diaphragms, and current collectors. In terahertz imaging, different materials have different dielectric constant response characteristics. By setting the active material dielectric constant threshold, voxels of electrochemically active materials can be distinguished. The volume changes of these voxels directly reflect the degree of attenuation of the battery's energy storage performance. In this embodiment, n represents the voxels corresponding to all materials inside the battery (active materials, electrolytes, diaphragms, current collectors, etc.); m represents the voxels whose dielectric constant is greater than or equal to the active material dielectric constant threshold. The number of voxels.

[0021] The energy storage battery storage performance attenuation rate is evaluated by voiceprint signals and follows: ; Where: is the decay rate; are the energy attenuation coefficient, frequency distortion rate, and complexity imbalance index; is the total energy of the two voiceprint signals at the initial stage of charging; The peak frequencies of the two voiceprint signals in the 500Hz-2kHz frequency range; is the complexity of the two voiceprint signals; in, ,The initial stage of charging is defined as 0~10 seconds; The above formula uses the total energy change of the voiceprint signal in the initial charging stage, the peak frequency offset of the key frequency band of 500Hz-2kHz, and the difference in signal complexity to extract the energy attenuation coefficient, frequency distortion rate and complexity imbalance index, and comprehensively calculate the attenuation rate. It effectively mines the internal chemical reaction and structural vibration information of the battery contained in the voiceprint signal as a non-invasive supplementary indicator, complementing the imaging data and improving the multi-physics field information fusion of attenuation assessment. Obtain the energy storage battery's three-dimensional imaging map and the energy storage battery's energy storage performance attenuation rate evaluation results corresponding to the voiceprint signal, and comprehensively estimate the energy storage battery's energy storage performance attenuation index based on the two evaluation results; The estimation logic of the energy storage battery storage performance attenuation index is: ; Where: is the energy storage performance attenuation index of the energy storage battery; is the weight; Among them, the weight The sum is 1 and all are positive numbers, the weight The configuration has dynamic value adjustment logic: When the fluctuation amplitude of the three-dimensional imaging atlas evaluation results for three consecutive times is smaller than the voiceprint signal, The value is set to 0.6-0.7, The corresponding value is 0.3-0.4; otherwise, Take 0.6-0.7, Take 0.3-0.4. At the same time, combined with the maximum slope of the charging curve inflection point in the collected energy storage battery status information, if the absolute value of the slope exceeds 20% of the standard value of a new battery, the weight of the one with the higher current weight will be reduced by 0.1, and the other weight will be increased by 0.1 accordingly; When calculating the energy storage battery's storage performance attenuation index, the above formula uses dynamic weighting to weight the attenuation rates of three-dimensional imaging and voiceprint assessment. The weighting is dynamically adjusted based on the fluctuation amplitude of the two and the slope of the charging curve inflection point to achieve optimal integration of multi-source attenuation information. The introduction of this dynamic weighting mechanism gives a higher proportion to more stable and reliable assessment sources. At the same time, the weighting is adjusted in real time based on the charging characteristics, allowing the attenuation index to adapt to the assessment needs under different conditions, thereby improving the representativeness of the index. The energy storage battery's storage performance attenuation index is corrected by applying the energy storage battery's three-dimensional imaging map and the energy storage battery's body state information collected during the voiceprint signal acquisition process; The correction logic of the energy storage battery storage performance attenuation index is expressed as: ; Where: is the proportionality coefficient; The maximum slope of the inflection point of the energy storage battery charging curve; is the average slope of the inflection point of the energy storage battery charging curve; The minimum and maximum values ​​of the temperature field gradient change rate when the energy storage battery is charging; in, The sum is 1, and both are greater than zero, and when the energy storage battery is fast charged, a<b, and when the energy storage battery is normally charged, a≥b; The above correction formula combines the slope of the charging curve inflection point and the rate of change of the temperature field gradient to correct the original attenuation index using a proportional coefficient. The weights a and b are adjusted according to the fast charging / conventional charging mode. The operating status of the battery itself is incorporated into the correction, and the characteristic differences under different charging modes are considered. This makes the corrected index more suitable for actual usage scenarios and enhances the environmental adaptability and accuracy of attenuation change detection. Record the correction results of each energy storage battery storage performance attenuation index, set the energy storage battery storage performance attenuation abnormality judgment threshold, and when the difference between two adjacent recorded correction results exceeds the energy storage battery storage performance attenuation abnormality judgment threshold, it is determined that the energy storage battery storage performance attenuation is abnormal; When recording the correction results of the energy storage battery power storage performance attenuation index for each time, mark the corresponding correction timestamp for each correction result of the energy storage battery power storage performance attenuation index for each time, and sort the correction results of the energy storage battery power storage performance attenuation index for each time based on the timestamps marked to form a list of the correction results of the energy storage battery power storage performance attenuation index; Wherein, each time the energy storage battery storage performance attenuation index correction result list updates the energy storage battery storage performance attenuation index correction result, the determination operation of whether the energy storage battery storage performance attenuation is abnormal is performed once; When the energy storage performance of the energy storage battery is judged to be abnormal, the energy storage battery ends the current charging task and feeds back the three-dimensional imaging map and voiceprint signal currently collected by the energy storage battery to the user of the energy storage battery management end.

[0022] In this embodiment, the above method combines terahertz imaging with voiceprint signals to accurately assess the energy storage battery's performance degradation. Dual-dimensional data collection and cloud-based storage and analysis, combined with the correction of the battery's state information, improve the accuracy of the degradation index assessment. Dynamic threshold determination can promptly detect performance degradation anomalies, provide early warning, avoid failures, extend battery life, ensure stable operation of the energy storage system, and reduce maintenance costs. It is applicable to various energy storage scenarios.

[0023] The following is an example of an application of the method in the above embodiment: A certain energy storage power station applied this test method to a No. 1 lithium iron phosphate energy storage battery (the standard dielectric constant in a brand new state is 8.2, and the active material volume is 120 cm³). The specific process is as follows: 1. Equipment Deployment and Data Collection A terahertz time-domain spectroscopy system and microphone array are deployed on the surface of battery No. 1: the terahertz system adopts a distributed array scanning architecture, with two sets of transmitting / receiving probes installed on the top and side of the battery, fixed 12 cm from the battery casing through an adjustable bracket. The transmitting end is a fiber-coupled terahertz pulse source, and the receiving end is equipped with a high-sensitivity Schottky diode detector. Each probe scans synchronously according to a preset serpentine trajectory, and a single scan covers 92% of the shell area; the microphone array is distributed in a 4×4 matrix along the long side and top surface of the battery, avoiding the heat dissipation holes (6 cm away) and the terminal blocks (16 cm away), and is equipped with a synchronized clock to ensure synchronous operation.

[0024] At the beginning of each charging phase (the continuous acquisition time is fixed at 30 seconds), three-dimensional imaging maps and voiceprint signals are collected, and the battery status information (charging curve inflection point slope, temperature field gradient change rate) is collected synchronously.

[0025] 2. Data Storage and Attenuation Rate Assessment Create a cloud database and store the collected data with timestamps. When the database accumulates 2 or more sets of data, evaluate the decay rate after each data update: The first charge (T1) collected a 3D imaging map A1 and a voiceprint signal B1, while the second charge (T2) collected A2 and B2. The attenuation rate corresponding to the 3D imaging was evaluated based on A1 and A2: the maximum dielectric constant difference in the battery core region between the two images was 0.8, the difference in the effective volume of the active material was 2 cm³, and the sum of the differences between the terahertz energy response values ​​and the baseline value for 5000 voxels was 500. The calculated attenuation rate corresponding to the 3D imaging was 0.07.

[0026] The attenuation rate corresponding to the voiceprint is evaluated based on B1 and B2: the total energy ratio of the two voiceprint signals in 0-10 seconds is 0.95, the peak frequency offset in the 500Hz-2kHz frequency band is 100Hz, and the complexity difference is 0.1. After calculation, the attenuation rate corresponding to the voiceprint is 0.06.

[0027] 3. Estimation and Correction of Decay Index Comprehensive attenuation rate estimation: Since the fluctuation range of the first three 3D imaging evaluation results is smaller than that of the voiceprint signal, the 3D imaging weight is taken as 0.6 and the voiceprint weight is taken as 0.4, and the calculated attenuation index is 0.0678.

[0028] Correction: Simultaneously collected battery status information indicates that this was normal charging. The maximum slope of the charging curve at the inflection point was 1.1 times the standard value for a new battery, and the average slope was 0.8 times the maximum slope. The temperature field gradient rate of change had a minimum of 0.5°C / s and a maximum of 1.5°C / s. The proportional coefficients a and b were 0.6 and 0.4 (a ≥ b). After calculation and correction, the attenuation exponent was 0.06.

[0029] 4. Abnormality Determination Record the attenuation index after each correction: The corrected result of T2 is 0.03, and the corrected result of T3 is 0.06 (the difference with T2 is 0.03, which does not exceed the set threshold of 0.04 and is judged to be normal); The corrected T4 result was 0.073 (the difference from T3 was 0.013, which did not exceed the threshold and was judged to be normal); When T5 is charging, A5 and B5 are collected, and the attenuation rate corresponding to the three-dimensional imaging is evaluated to be 0.25, the attenuation rate corresponding to the voiceprint is 0.23, and the comprehensive estimated attenuation index is 0.238; combined with the body status information (conventional charging, the maximum slope of the inflection point of the charging curve is 2.1 times the standard value of a new battery, the minimum temperature field gradient change rate is 0.8℃ / s and the maximum is 2.5℃ / s), after correction, the attenuation index is 0.246.

[0030] The difference between the correction results at T5 and T4 is 0.173, exceeding the set threshold of 0.1, indicating that battery 1's energy storage performance is abnormally degraded. At this point, the battery terminates the current charging task and reports A5 and B5 to the management terminal.

[0031] In summary, during the execution of the method in the above embodiment, by fusing terahertz time-domain spectroscopy three-dimensional imaging and voiceprint signal dual-modal data, distributed array scanning and matrix deployment are used to realize full-domain information collection of the battery, and combined with dynamic storage and comparative analysis of the cloud database, a multi-dimensional attenuation assessment model is constructed. The dynamic weight adjustment mechanism and body state information correction introduced by it significantly improve the estimation accuracy of the attenuation index, and are adapted to different scenarios of fast charging and conventional charging. At the same time, through the judgment of the difference threshold of adjacent data, it can capture sudden changes in storage performance in real time, give early warning of abnormal attenuation, effectively avoid the risk of battery failure, extend the service life, and provide safety monitoring protection for energy storage batteries.

[0032] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for detecting the degradation and abnormal change of the storage performance of an energy storage battery, characterized in that: include: Deploy a terahertz time-domain spectroscopy system and a microphone array on the surface of the energy storage battery to collect the three-dimensional imaging map and voiceprint signal of the energy storage battery at the beginning of each energy storage battery charging stage based on the terahertz time-domain spectroscopy system and the microphone array; Create a cloud database and use it to store the three-dimensional imaging maps and voiceprint signals of energy storage batteries; The energy storage battery's power storage performance attenuation rate is evaluated based on the three-dimensional imaging map and voiceprint signal of the energy storage battery stored in the cloud database; Obtain the energy storage battery's three-dimensional imaging map and the energy storage battery's energy storage performance attenuation rate evaluation results corresponding to the voiceprint signal, and comprehensively estimate the energy storage battery's energy storage performance attenuation index based on the two evaluation results; The energy storage battery's storage performance attenuation index is corrected by applying the energy storage battery's three-dimensional imaging map and the energy storage battery's body state information collected during the voiceprint signal acquisition process; Record the correction results of the energy storage battery's storage performance attenuation index for each time, set a threshold for determining an abnormality in the energy storage battery's storage performance attenuation, and determine that the energy storage battery's storage performance attenuation is abnormal when the difference between the correction results of two adjacent records exceeds the threshold for determining an abnormality in the energy storage battery's storage performance attenuation.

2. A method for detecting storage performance degradation and abnormality of an energy storage battery according to claim 1, characterized in that: The terahertz time-domain spectroscopy system, when deployed on the surface of an energy storage battery, complies with: A distributed array scanning architecture is used, with no fewer than two sets of terahertz transmitting / receiving probes installed on the top and side surfaces of the energy storage battery. The probes are fixed 10 to 15 cm from the battery casing via adjustable brackets. The transmitting end uses a fiber-coupled terahertz pulse source, and the receiving end is equipped with a high-sensitivity Schottky diode detector. The probes operate synchronously, and the probe scanning path moves along a preset serpentine trajectory, with a single scan covering more than 90% of the casing area. When the microphone array is deployed on the surface of the energy storage battery, it complies with: Microphones are deployed in a matrix along the long sides and top of the energy storage battery. Microphones are fixed on each side in a 3×3 or 4×4 array. The microphones deployed in the matrix avoid all interference sources, including the energy storage battery heat dissipation holes and wiring terminals. The microphones are at least 5 cm away from the battery heat dissipation holes and at least 15 cm away from the wiring terminals. Among them, the microphone array is equipped with a synchronous clock, and each microphone in the microphone array operates synchronously through the synchronous clock. The continuous collection time of the three-dimensional imaging map of the energy storage battery and the voiceprint signal each time is fixed and unified.

3. The method for detecting the degradation and abnormal change of the storage performance of an energy storage battery according to claim 1, characterized in that: When storing the three-dimensional imaging map and voiceprint signal of the energy storage battery, the cloud database marks the collection timestamp for each three-dimensional imaging map and voiceprint signal of the energy storage battery, and the cloud database sorts and stores the three-dimensional imaging map and voiceprint signal of the energy storage battery based on the marked content; The energy storage battery three-dimensional imaging map and voiceprint signal acquisition process synchronously collect the energy storage battery body state information, including: charging curve inflection point slope, temperature field gradient change rate; Among them, the status information of the energy storage battery itself is sent synchronously to the cloud database, and is bound and stored with the corresponding energy storage battery three-dimensional imaging map and voiceprint signal based on the acquisition time.

4. The method for detecting the degradation and abnormal change of the storage performance of an energy storage battery according to claim 1, characterized in that: The evaluation of the energy storage battery's electrical storage performance attenuation rate is performed once each time the energy storage battery's three-dimensional imaging maps and voiceprint signals are updated and stored, when there are at least two sets of energy storage battery three-dimensional imaging maps and voiceprint signals stored in the cloud database. When evaluating the energy storage battery's electrical storage performance attenuation rate, the latest two sets of energy storage battery three-dimensional imaging maps and voiceprint signals are retrieved from the cloud database; The energy storage battery storage performance attenuation rate is evaluated by the three-dimensional imaging atlas of the energy storage battery and is subject to the following conditions: ； Where: is the decay rate; is the maximum dielectric constant difference of the battery core area in the two imagings; It is the standard dielectric constant benchmark value of new energy storage batteries; The effective volume of the battery active material is calculated by spatially reconstructing two three-dimensional imaging maps; It is a new energy storage battery active material volume benchmark; is the total number of global voxels in the 3D imaging atlas; is the terahertz energy response value of the i-th voxel in the two imagings; The energy baseline value of the corresponding voxel of the new energy storage battery; in, The calculation logic is the same. The calculation is as follows: ； Where: is the number of active substance voxels in the three-dimensional imaging atlas; is the three-dimensional volume of the j-th voxel; It is an indicator function, which takes the value 1 if the condition in the brackets is met, otherwise it takes the value 0; is the dielectric constant of the jth voxel in the latest imaging; is the dielectric constant threshold of the active material.

5. The method for detecting the degradation and abnormal change of the storage performance of an energy storage battery according to claim 3, characterized in that: The energy storage battery storage performance attenuation rate is evaluated by the voiceprint signal and obeys: ； Where: is the decay rate; are the energy attenuation coefficient, frequency distortion rate, and complexity imbalance index; is the total energy of the two voiceprint signals at the initial stage of charging; The peak frequencies of the two voiceprint signals in the 500Hz-2kHz frequency range; is the complexity of the two voiceprint signals; in, , the initial stage of charging is defined as 0~10 seconds.

6. The method for detecting the degradation and abnormal change of the storage performance of an energy storage battery according to claim 5, characterized in that: The energy storage battery storage performance attenuation index estimation logic is: ； Where: is the energy storage performance attenuation index of the energy storage battery; is the weight; Among them, the weight The sum is 1 and all are positive numbers, the weight The configuration has dynamic value adjustment logic: When the fluctuation amplitude of the three-dimensional imaging atlas evaluation results for three consecutive times is smaller than the voiceprint signal, The value is set to 0.6-0.7, The corresponding value is 0.3-0.4; otherwise, Take 0.6-0.7, Take 0.3-0.4; at the same time, combined with the maximum slope of the inflection point of the charging curve in the collected energy storage battery status information, if the absolute value of the slope exceeds 20% of the standard value of a new battery, the weight of the one with a higher current proportion will be reduced by 0.1, and the other weight will be increased by 0.1 accordingly.

7. The method for detecting the degradation and abnormal change of the storage performance of an energy storage battery according to claim 1, characterized in that: The correction logic of the energy storage battery storage performance attenuation index is expressed as: ； Where: is the proportionality coefficient; The maximum slope of the inflection point of the energy storage battery charging curve; is the average slope of the inflection point of the energy storage battery charging curve; The minimum and maximum values ​​of the temperature field gradient change rate when the energy storage battery is charging; in, The sum is 1 and both are greater than zero, and when the energy storage battery is fast charged, a<b, and when the energy storage battery is normally charged, a≥b.

8. The method for detecting storage performance degradation and abnormality of an energy storage battery according to claim 1, characterized in that: When recording the energy storage battery power storage performance attenuation index correction results, each energy storage battery power storage performance attenuation index correction result is marked with a corresponding correction timestamp, and the energy storage battery power storage performance attenuation index correction results are sorted based on the timestamps marked with each energy storage battery power storage performance attenuation index correction result to form an energy storage battery power storage performance attenuation index correction result list; Wherein, each time the energy storage battery storage performance attenuation index correction result list updates the energy storage battery storage performance attenuation index correction result, the determination operation of whether the energy storage battery storage performance attenuation is abnormal is performed once.

9. The method for detecting storage performance degradation and abnormality of an energy storage battery according to claim 1, characterized in that: When the storage performance of the energy storage battery is determined to be abnormal, the energy storage battery ends the current charging task and feeds back the three-dimensional imaging map and voiceprint signal currently collected by the energy storage battery to the energy storage battery management end user.

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