Sodium-ion battery health state evaluation system and method for energy storage application

Abstract

The invention relates to the technical field of battery detection, in particular to a sodium ion battery health state evaluation system and method for energy storage application, and the system comprises a data collection module, a data preprocessing module, a data storage module, a battery state evaluation module and a data analysis module. The data acquisition module is used for acquiring current data of the sodium ion battery in real time; the data preprocessing module is used for preprocessing the current data; the data storage module is used for storing the preprocessed current data; the battery state evaluation module is used for acquiring target current data of the sodium-ion battery in each historical energy cycle stage in the data storage module, and calculating a first battery degradation coefficient of the sodium-ion battery in the current energy cycle stage based on the target current data; and the data analysis module is used for calculating a real-time health state coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient. The evaluation accuracy of the health state of the battery can be ensured.

Description

Technical Field

[0001] The present invention relates to the field of battery detection technology, and in particular to a sodium ion battery health status assessment system and method for energy storage applications. Background Art

[0002] As the global demand for clean energy continues to grow, sodium-ion batteries are gradually gaining attention as an important technology to replace traditional lithium-ion batteries. Sodium-ion battery state of health (SOH) assessment is to evaluate the performance degradation and remaining service life of the battery by monitoring parameters such as battery capacity and internal resistance. For large-scale energy storage systems, SOH assessment can predict the remaining time and performance degradation of the battery to ensure the stability and reliability of the system.

[0003] Existing sodium-ion battery health status assessment methods simulate the charging and discharging process, analyze the dynamic characteristics of the battery, and combine the current-voltage change characteristics to evaluate the health status and identify potential faults; however, since the energy storage efficiency decay process of sodium-ion batteries is affected by multiple nonlinear factors, traditional linear models are difficult to accurately describe the complex energy storage efficiency decay mechanism of batteries, resulting in deviations in the relationship between actual current and battery health status, thereby affecting the accurate assessment of battery health status. Summary of the invention

[0004] In order to solve the technical problem that the traditional linear model is difficult to accurately describe the complex energy storage efficiency decay mechanism of the battery, resulting in a deviation in the relationship between the actual current and the battery health state, thereby affecting the accurate assessment of the battery health state, the purpose of the present invention is to provide a sodium ion battery health state assessment system and method for energy storage applications. The technical solutions adopted are as follows: In a first aspect, the present invention provides a sodium ion battery health status assessment system for energy storage applications, the system comprising: a data acquisition module, a data preprocessing module, a data storage module, a battery status assessment module and a data analysis module; The data acquisition module is connected to the positive and negative electrodes of the sodium ion battery and is used to collect current data of the sodium ion battery in real time; The data preprocessing module is connected to the data acquisition module and is used to preprocess the current data, wherein the preprocessing at least includes data cleaning and denoising; The data storage module is connected to the data preprocessing module and is used to store the preprocessed current data; The battery state evaluation module is connected to the data storage module, and is used to obtain the target current data of the sodium ion battery in each historical energy cycle stage in the data storage module, and calculate the first battery degradation coefficient of the sodium ion battery in the current energy cycle stage based on the target current data; The data analysis module is connected to the battery status evaluation module, and the data analysis module is used to calculate the real-time health status coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient, and the real-time health status coefficient is used to characterize the health status of the sodium ion battery in the current energy cycle stage, and the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than a preset health threshold and the battery is discarded, or the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health is greater than or equal to the preset health threshold.

[0005] Optionally, the system further includes: a health data visualization module and an alarm module; The health data visualization module and the alarm module are respectively connected to the data analysis module, the health data visualization module is used to display the real-time health status coefficient in real time, and the alarm module is used to issue an alarm prompt of abnormal health status of the sodium ion battery when it is judged that the real-time health status coefficient is greater than a preset threshold.

[0006] In a second aspect, an embodiment of the present invention further provides a sodium ion battery health status assessment method for energy storage applications, the method being applied to a sodium ion battery health status assessment system for energy storage applications as described in any one of the first aspects, the method comprising: Obtain target current data of sodium-ion batteries at each historical energy cycle stage; Calculating a first battery degradation factor of the sodium ion battery in a current energy cycle stage based on the target current data; The first battery degradation coefficient is sent to a data analysis module, so that the data analysis module calculates the real-time health status coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient, wherein the real-time health status coefficient is used to characterize the health status of the sodium ion battery in the current energy cycle stage, and the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than a preset health threshold and the battery is discarded, or the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health is greater than or equal to the preset health threshold.

[0007] Optionally, calculating a first battery degradation coefficient of the sodium ion battery in a current energy cycle stage based on the target current data includes: Determining an evaluation parameter of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage; A first battery degradation factor of the sodium ion battery in a current energy cycle stage is calculated based on the evaluation parameters.

[0008] Optionally, the evaluation parameter includes a current health state degradation coefficient; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Calculating a first degradation indicator of a state of health and a second degradation indicator of a state of health of the sodium ion battery at each of the historical energy cycle stages according to the target current data of the sodium ion battery at each of the historical energy cycle stages; Based on the first health state degradation indicator and the second health state degradation indicator, a current health state degradation degree coefficient of the sodium ion battery in each of the historical energy cycle stages is calculated.

[0009] Optionally, the calculating, according to the target current data of the sodium ion battery in each of the historical energy cycle stages, a first degradation indicator of the state of health and a second degradation indicator of the state of health of the sodium ion battery in each of the historical energy cycle stages, comprises: Determine a first fitting curve of battery charging current and a second fitting curve of battery discharging current based on target current data of the sodium ion battery in each of the historical energy cycle stages; Extracting a first data point of a data peak in the first fitting curve and a second data point of a data peak in the second fitting curve; Performing data point matching on the first data point and the second data point to obtain a set of corresponding points between all peaks; Determining the Euclidean distance variance of each corresponding point in the corresponding point set as the first degradation indicator of the health state of the sodium ion battery in the corresponding historical energy cycle stage; Based on the maximum points and the minimum points on the first fitting curve and the second fitting curve, respectively determine the upper envelope and the lower envelope of the first fitting curve and the second fitting curve; The absolute value of the phase difference between the upper envelope and the lower envelope of the same fitting curve and the frequency domain data corresponding to the upper envelope is determined as the second degradation indicator of the health state of the sodium ion battery in the corresponding historical energy cycle stage.

[0010] Optionally, the calculating, based on the first health state degradation indicator and the second health state degradation indicator, a current health state degradation degree coefficient of the sodium ion battery in each of the historical energy cycle stages includes: Normalizing the first health state degradation index and the second health state degradation index of the sodium ion battery at the same historical energy cycle stage respectively; The product of the normalized first health state degradation index and the second health state degradation index is calculated, and the product is determined as the current health state degradation degree coefficient of the sodium ion battery in the corresponding historical energy cycle stage.

[0011] Optionally, the evaluation parameters include a target slope of a line between a discharge end time point of each of the historical energy cycle stages and a charge end time point of the next historical energy cycle stage, and a depth of discharge coefficient between a discharge end time point of each of the historical energy cycle stages and a charge end time point of the next historical energy cycle stage; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Determine, according to the target current data of the sodium ion battery in each historical energy cycle stage, the discharge end time point of the sodium ion battery in each historical energy cycle stage, and the charging end time point of the sodium ion battery in each historical energy cycle stage corresponding to the next historical energy cycle stage; Determining the slope of a line between the discharge end time point and the charge end time point as the target slope; A first time interval between the discharge end time point and the charge end time point is determined as the deep discharge coefficient.

[0012] Optionally, the evaluation parameters include internal structure damage coefficient; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Based on the target current data of the sodium ion battery in each of the historical energy cycle stages, determining a first fitting curve of the battery charging current, a second fitting curve of the battery discharging current, and a discharge end time point of the sodium ion battery in each of the historical energy cycle stages; Constructing a window area for each maximum point in the first fitting curve and the second fitting curve; Calculating the current turbulence characteristic coefficient of each window area, and determining the maximum value point corresponding to the maximum current turbulence characteristic coefficient among the plurality of maximum value points as the target maximum value point; Determine the time node of the target maximum value point as the optimal efficiency end node of the sodium ion battery corresponding to the historical energy cycle stage; The second time interval distance between the optimal efficiency end node and the discharge end time point is determined as the internal structure damage coefficient of the sodium ion battery corresponding to the historical energy cycle stage.

[0013] Optionally, the calculating of the current disorder characteristic coefficient of each window area includes: Determine window area information of each of the window areas, the window area information at least including a set of extreme value points contained in the window area, a slope of each extreme value point in the set of extreme value points at the first fitting curve or the second fitting curve, and an occurrence probability of each extreme value point in the set of extreme value points in the target current data, the extreme value points including maximum value points and minimum value points; A current disorder characteristic coefficient of each window area is calculated based on the window area information.

[0014] The present invention has the following beneficial effects: through the technical solution provided by the present invention, by analyzing the target current data of the sodium-ion battery during the charging and discharging process at each historical energy cycle stage, the first battery degradation coefficient of the sodium-ion battery in the current energy cycle stage is calculated in real time, and the health state of the sodium-ion battery is determined based on the first battery degradation coefficient. When calculating the first battery degradation coefficient, the present invention can comprehensively consider multiple nonlinear factors in the process of energy storage efficiency decline of the sodium-ion battery, overcome the limitations of traditional linear models in describing complex battery decline mechanisms, avoid the deviation between current and battery health state, and thus improve the accuracy of sodium-ion battery health assessment.

[0015] It should be understood that the above general description and the following detailed description are only exemplary and explanatory and cannot limit the present invention. Other features and advantages of the present invention will be described in detail in the following specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1A schematic diagram of the system structure of a sodium ion battery health status assessment system for energy storage applications provided by one embodiment of the present invention; Figure 2 A schematic diagram of a flow chart of a sodium ion battery health status assessment method provided by one embodiment of the present invention; Figure 3 A schematic diagram of time nodes of a sodium ion battery charge and discharge process provided by one embodiment of the present invention; Figure 1 middle: 1-Data acquisition module; 2-Data preprocessing module; 3-Data storage module; 4-Battery status assessment module; 5-Data analysis module; 6-Health data visualization module; 7-Alarm module. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of a sodium ion battery health status assessment system and method for energy storage applications proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0020] The following is a detailed description of a sodium ion battery health status assessment system and method for energy storage applications provided by the present invention in conjunction with the accompanying drawings.

[0021] See also Figure 1, which shows a system structure diagram of a sodium ion battery health status assessment system for energy storage applications provided by an embodiment of the present invention, the system includes: a data acquisition module 1, a data preprocessing module 2, a data storage module 3, a battery status assessment module 4 and a data analysis module 5; the data acquisition module 1 is connected to the positive and negative electrodes of the sodium ion battery, and is used to collect the current data of the sodium ion battery in real time. Among them, the current data can be the real-time current signal of the positive and negative electrodes of the sodium ion battery, and the data acquisition module 1 may include a Hall effect sensor and a data recorder. The Hall effect sensor is respectively connected to the positive and negative electrodes of the sodium ion battery group, and is used to collect the real-time current signal of the positive and negative electrodes of the sodium ion battery according to a preset sampling frequency (such as once per second), and send the real-time current signal to the data recorder for recording. The data preprocessing module 2 is connected to the data acquisition module 1, and the data acquisition module 1 can upload the real-time collected current data of the sodium ion battery to the data preprocessing module 2 through a data transmission technology such as a controller area network (CAN) bus, and the data preprocessing module 2 is used to preprocess the current data, and the preprocessing at least includes data cleaning and denoising. Specifically, interpolation, deletion and other processing methods can be used to clean the original current data to ensure the accuracy of subsequent data analysis. In order to reduce the impact of noise caused by data fluctuations, a smoothing algorithm can be used to process the original current data to make the data change more smoothly. The data storage module 3 is connected to the data preprocessing module 2, and is used to store the preprocessed current data; the battery state evaluation module 4 is connected to the data preprocessing module 2 and the data storage module 3, and the battery state evaluation module 4 can be used to obtain the target current data of the sodium ion battery in each historical energy cycle stage in the data storage module 3, and calculate the first battery degradation coefficient of the sodium ion battery in the current energy cycle stage based on the target current data; the data analysis module 5 is connected to the battery state evaluation module 4, and the data analysis module 5 is used to calculate the real-time health state coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient. The real-time health state coefficient is used to characterize the health state of the sodium ion battery in the current energy cycle stage, and the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than a preset health threshold and the battery is discarded, or the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health is greater than or equal to the preset health threshold. Among them, the preset health threshold is the critical point for judging whether the sodium ion battery is healthy or not. When the battery degradation coefficient of the sodium ion battery is less than the preset health threshold, the health state of the sodium ion battery can be judged to be abnormal; when the battery degradation coefficient of the sodium ion battery is greater than or equal to the preset health threshold, the health state of the sodium ion battery can be judged to be normal. The numerical value of the preset health threshold can be set according to the sodium ion battery model and the actual application scenario, and is not specifically limited here.

[0022] In specific application scenarios, such as Figure 1 As shown, the sodium-ion battery health status assessment system for energy storage applications may also include: a health data visualization module 6 and an alarm module 7; the health data visualization module 6 and the alarm module 7 are respectively connected to the data analysis module 5, and the health data visualization module 6 is used to display the real-time health status coefficient in real time, so as to facilitate the visual management of relevant personnel. The alarm module 7 is used to issue an alarm prompt of abnormal health status of the sodium-ion battery when it is judged that the real-time health status coefficient is greater than a preset threshold, so that relevant personnel can promptly check and repair the sodium-ion battery. Among them, the preset threshold can be set according to the actual application scenario, such as 0.5; the alarm prompt may include but is not limited to at least one of light prompt, vibration prompt, audio prompt, video prompt, and SMS prompt.

[0023] After introducing the application scenarios of the embodiments of the present application, the technical solution of the present application will be described in detail below: Figure 2 The present invention provides a flow chart of a sodium ion battery health status assessment method for energy storage applications. The method can be executed by a battery status assessment module in a sodium ion battery health status assessment system for energy storage applications, but is not limited thereto. Figure 2 As shown, the method may include the following steps: Step 110: Obtain target current data of the sodium ion battery in each historical energy cycle stage.

[0024] In the actual use of sodium-ion batteries, they will experience multiple charges and discharges, and each complete charge and discharge process is an energy cycle stage. These energy cycle stages are arranged in chronological order, which constitute the energy cycle stage record of the sodium-ion battery. For example, a sodium-ion battery starts with the first charge and goes through the first discharge, which is the first energy cycle stage; then it is charged and discharged for the second time, which is the second energy cycle stage, and so on. These different stages together constitute the historical energy cycle stage of the sodium-ion battery. The historical energy cycle stage specifically refers to all the complete charge and discharge processes that the sodium-ion battery has experienced before the current time point, reflecting the working status of the sodium-ion battery at different historical time points. The target current data refers to the current signal collected for the positive and negative electrodes of the sodium-ion battery in each historical energy cycle stage. The target current data consists of the battery charging current in the charging stage and the battery discharging current in the discharging stage. The battery charging current is regarded as a positive current and the battery discharging current is regarded as a negative current.

[0025] For the embodiment of the present disclosure, the battery status evaluation module can dynamically obtain the target current data of the sodium ion battery at each historical energy cycle stage from the data storage module during the application process of the sodium ion battery, so as to analyze the health status of the sodium ion battery in real time based on the target current data.

[0026] Step 120: Calculate a first battery degradation factor of the sodium ion battery in the current energy cycle stage based on the target current data.

[0027] In specific application scenarios, the energy conversion efficiency of sodium-ion batteries generally changes with changes in battery voltage. In order to optimize the service life of the battery, a good energy management strategy should ensure that the battery operates within the optimal voltage range, thereby maintaining the best energy conversion efficiency and extending its cycle life in the energy storage system. When a sodium-ion battery is degraded, its health will gradually deteriorate during a single charge and discharge process. In addition, frequent deep discharges will aggravate the damage to the internal structure of the battery, thereby causing the battery capacity to decay and the cycle life to be shortened, further deteriorating the overall health of the sodium-ion battery. For the disclosed embodiment, the first battery degradation coefficient of the sodium-ion battery in the current energy cycle stage can be calculated based on the target current data, so as to calculate the difference between the first battery degradation coefficient and the corresponding second battery degradation coefficient of the same type of healthy or unhealthy sodium-ion battery, so as to determine the current health status of the sodium-ion battery.

[0028] For the embodiment of the present disclosure, calculating the first battery degradation coefficient of the sodium ion battery in the current energy cycle stage based on the target current data in step 120 may include the following steps: Step 120 - 1 : Determine the evaluation parameters of the sodium ion battery in each historical energy cycle stage according to the target current data of the sodium ion battery in each historical energy cycle stage.

[0029] Among them, the evaluation parameters include at least the current health state degradation coefficient, the target slope of the line between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage, the depth of discharge coefficient between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage, and the internal structure damage coefficient.

[0030] For the embodiment of the present disclosure, when the evaluation parameters include the current health state degradation degree coefficient, the embodiment step 120-1 may include: calculating the first health state degradation index and the second health state degradation index of the sodium ion battery in each historical energy cycle stage according to the target current data of the sodium ion battery in each historical energy cycle stage; based on the first health state degradation index and the second health state degradation index, calculating the current health state degradation degree coefficient of the sodium ion battery in each historical energy cycle stage.

[0031] Specifically, when calculating the first degradation index of the health state and the second degradation index of the health state of the sodium ion battery in each historical energy cycle stage according to the target current data of the sodium ion battery in each historical energy cycle stage, the least squares method can be used to obtain the first fitting curve of the battery charging current and the second fitting curve of the battery discharging current of the sodium ion battery in each historical energy cycle stage. During the charging and discharging process of a healthy sodium ion battery, the current and voltage change steadily; however, as the battery deteriorates, the internal resistance increases and the chemical reaction efficiency decreases, causing the charging and discharging curves to become steeper, which is manifested as more disordered and lacking regularity in the current and voltage fluctuations. Based on this, it is possible to identify whether there is a significant decline in the health state of the sodium ion battery in the current historical energy cycle stage. Specifically, a peak detection algorithm can be used to extract all data peaks in the first fitting curve and the second fitting curve, and the data points of all data peaks in the first fitting curve and the second fitting curve are matched by a dynamic time warping algorithm (DTW) to obtain a set of corresponding points between all peaks. Then, the variance of the Euclidean distance of each corresponding point in the corresponding point set is calculated as the first degradation index of the health state of the sodium ion battery in the current historical energy cycle stage. , the larger the value of the first degradation index of the health state, the greater the disorder fluctuation of the sodium ion battery in the historical energy cycle stage, and the worse the battery health state. In the specific energy cycle process, as the sodium ion battery ages, the internal resistance increases, resulting in a slower rate of voltage change during the charge and discharge process. At the same time, the increase in internal resistance causes a hysteresis in the response between current and voltage, and the current-voltage relationship during the charge and discharge process becomes no longer synchronized. Based on this, the maximum and minimum points on the first fitting curve and the second fitting curve can be determined, and all the maximum and minimum points are connected respectively to obtain the upper envelope and lower envelope of the first fitting curve and the second fitting curve. Further, the first time domain data of the first fitting curve with respect to the upper envelope, the second time domain data of the second fitting curve with respect to the upper envelope can be determined, and the first time domain data and the second time domain data are integrated to obtain complete upper envelope time domain data; and the third time domain data of the first fitting curve with respect to the lower envelope, the fourth time domain data of the second fitting curve with respect to the lower envelope are determined, and the third time domain data and the fourth time domain data are integrated to obtain complete lower envelope time domain data. Then, the Fast Fourier Transform (FFT) algorithm can be used to convert the upper envelope time domain data and the lower envelope time domain data into frequency domain data respectively, and the phase information of the upper and lower envelope frequency domain data can be obtained. , , and use trigonometric functions to convert the phase information into data and calculate , The absolute value of the difference between: In the formula, Represents the second degradation index of the health status of the sodium-ion battery at a certain historical energy cycle stage. The larger the value, the more serious the hysteresis between the current and voltage response of the sodium-ion battery at this historical energy cycle stage, that is, the scale performance of the sodium-ion battery at this historical energy cycle stage is significantly reduced; , They are the phase information of the upper and lower envelope frequency domain data respectively.

[0032] Correspondingly, when calculating the first degradation indicator of the state of health and the second degradation indicator of the state of health of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage, the steps of the embodiment may include: determining a first fitting curve of the battery charging current and a second fitting curve of the battery discharging current based on the target current data of the sodium ion battery at each historical energy cycle stage; extracting a first data point of a data peak in the first fitting curve and a second data point of a data peak in the second fitting curve; performing data point matching on the first data point and the second data point to obtain a corresponding point set between all peaks; determining the Euclidean distance variance of each corresponding point in the corresponding point set as the first degradation indicator of the state of health of the sodium ion battery at the corresponding historical energy cycle stage; determining the upper envelope and the lower envelope of the first fitting curve and the second fitting curve respectively based on the maximum value points and the minimum value points on the first fitting curve and the second fitting curve; determining the absolute value of the phase difference value of the frequency domain data corresponding to the upper envelope and the lower envelope of the same fitting curve as the second degradation indicator of the state of health of the sodium ion battery at the corresponding historical energy cycle stage.

[0033] Specifically, when calculating the current health state degradation coefficient of the sodium ion battery in each historical energy cycle stage based on the first health state degradation index and the second health state degradation index, the following can be used: The function normalizes the first degradation index and the second degradation index of the health state of the sodium-ion battery in the same historical energy cycle stage, unifies the dimensions for subsequent data calculation. Then, the first degradation index and the second degradation index of the health state of the sodium-ion battery in the specific energy cycle stage can be comprehensively considered to measure the current health state degradation degree coefficient of the sodium-ion battery in the specific energy cycle stage. : In the formula, is the current health state degradation coefficient of the sodium ion battery at a certain historical energy cycle stage; It is the first degradation indicator of the health status of sodium-ion batteries at this historical energy cycle stage; It is the second degradation indicator of the health status of sodium-ion batteries at this historical energy cycle stage.

[0034] Accordingly, the steps of the embodiment may include: normalizing the first degradation indicator of the health state and the second degradation indicator of the health state of the sodium ion battery in the same historical energy cycle stage respectively; calculating the product of the normalized first degradation indicator of the health state and the second degradation indicator of the health state, and determining the product as the current health state degradation degree coefficient of the sodium ion battery in the corresponding historical energy cycle stage.

[0035] For the embodiment of the present disclosure, when the evaluation parameters include the target slope of the line between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage, and the depth of discharge coefficient between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage, as follows: Figure 3 As shown, the target current data of sodium-ion batteries for energy storage applications in all historical energy cycle stages can be obtained. The target current data of all historical energy cycle stages include all charging time nodes and discharging time nodes, which constitute the time node sequence set A and set B. The time node after each sodium-ion battery charging process is completed is connected with the nearest discharge process completion time node in the time series. Figure 3 middle, Represents the end time of charging of sodium-ion battery, represents the end time of discharge of the sodium-ion battery. For a complete energy cycle process, is the discharge shelf time after a discharge. In actual operation, sodium-ion batteries for energy storage applications have longer and shorter discharge shelf times (for example, and ), respectively indicating whether there is a deep discharge (deep discharge refers to discharging the battery to a level close to its lowest voltage, which may damage the internal structure of the battery, leading to battery capacity decay and shortened cycle life) in the current energy cycle stage of the sodium ion battery. If the discharge is left idle for a long time, there is no deep discharge, otherwise there is deep discharge. For the embodiments of the present disclosure, it can be based on Figure 3 , determine the end time of discharge of the sodium ion battery in each historical energy cycle stage, and the end time of charge of the sodium ion battery in each historical energy cycle stage corresponding to the next historical energy cycle stage, and then connect the end time of discharge and the end time of charge (such as and ) is determined as the target slope , the time between the discharge end time point and the charge end time point (such as and ) is determined as the depth of discharge coefficient D. The smaller the value, the deeper the sodium ion battery is discharged at this stage.

[0036] Accordingly, when the evaluation parameters include the target slope of the line between the discharge end time point of each historical energy cycle stage and the charge end time point of the next historical energy cycle stage, and the depth of discharge coefficient between the discharge end time point of each historical energy cycle stage and the charge end time point of the next historical energy cycle stage, the embodiment step 120-1 may include: determining the discharge end time point of the sodium ion battery in each historical energy cycle stage and the charge end time point of the sodium ion battery in each historical energy cycle stage corresponding to the next historical energy cycle stage according to the target current data of the sodium ion battery in each historical energy cycle stage; determining the slope of the line between the discharge end time point and the charge end time point as the target slope; and determining the first time interval distance between the discharge end time point and the charge end time point as the depth of discharge coefficient.

[0037] For the embodiment of the present disclosure, when the evaluation parameters include the internal structure damage coefficient, the least squares method can be used to obtain the first fitting curve of the battery charging current and the second fitting curve of the battery discharging current of the sodium-ion battery in each historical energy cycle stage, and obtain the discharge time node contained in the target current data of each historical energy cycle stage. Then, any maximum point in the first fitting curve and the second fitting curve can be divided into window areas. Specifically, any maximum point can be used as the starting point, and the step size is 10 data points to construct the window area. When there are insufficient data points, all remaining data points can be regarded as the same area. Further, the frequency of occurrence of all extreme points (including maximum points and minimum points) in the window area in the overall target flow data can be obtained separately. , and the slope k of the extreme point at the corresponding fitting curve, and then based on the frequency of occurrence of all extreme points (including maximum points and minimum points) in the overall target flow data , and the slope k of the extreme point at the fitting curve, calculate the current disorder characteristic coefficient of each window area: In the formula, Represents the first stage of sodium-ion battery energy cycle in a certain historical energy cycle The current disorder characteristic coefficient of the window area corresponding to the maximum point; Representative The maximum value points correspond to the set of extreme value points in the window area; Represents a set of extreme points The An extreme point, Represents the The slope of the extreme point on the first fitting curve or the second fitting curve, Represents the The frequency of occurrence of extreme points in the overall target traffic data. Is a multiplication symbol, which means to perform multiplication operation on the following expressions. The larger the value, the more dramatic the change of the current data in the local stage of the battery cycle process, and the extreme points corresponding to these dramatic changes rarely appear in the previous flow data. This shows that the current data in this local stage shows significant abnormal and disordered fluctuations, and the battery energy conversion efficiency in the corresponding process stage is low.

[0038] Furthermore, the multiple current turbulence characteristic coefficients corresponding to the multiple maximum points can be sorted by numerical value, and the maximum point with the largest corresponding current turbulence characteristic coefficient among the multiple maximum points can be determined as the target maximum point; the time node of the target maximum point can be determined as the optimal efficiency end node of the sodium ion battery in the corresponding historical energy cycle stage. .like Figure 3 As shown in the figure, the time between the optimal efficiency end node and the discharge end time point in each historical energy cycle stage (such as , , ) is determined as the internal structure damage coefficient L of the sodium-ion battery in the corresponding historical energy cycle stage.

[0039] Accordingly, when the evaluation parameter includes the internal structure damage coefficient, the embodiment step 120-1 may include: determining a first fitting curve of the battery charging current, a second fitting curve of the battery discharging current, and a discharge end time point of the sodium ion battery in each historical energy cycle stage based on the target current data of the sodium ion battery in each historical energy cycle stage; constructing a window area for each maximum point in the first fitting curve and the second fitting curve; calculating the current turmoil characteristic coefficient of each window area, and determining the maximum point with the largest current turmoil characteristic coefficient among multiple maximum points as the target maximum point; determining the time node of the target maximum point as the optimal efficiency end node of the sodium ion battery in the corresponding historical energy cycle stage; and determining the second time interval distance between the optimal efficiency end node and the discharge end time point as the internal structure damage coefficient of the sodium ion battery in the corresponding historical energy cycle stage.

[0040] Specifically, when calculating the current turbulence characteristic coefficient of each window area, the implementation steps may include: determining the window area information of each window area, the window area information at least including a set of extreme points contained in the window area, the slope of each extreme point in the extreme point set at the first fitting curve or the second fitting curve, the probability of occurrence of each extreme point in the extreme point set in the target current data, the extreme points including maximum points and minimum points; and calculating the current turbulence characteristic coefficient of each window area based on the window area information.

[0041] Step 120 - 2 : Calculate a first battery degradation factor of the sodium ion battery in the current energy cycle stage based on the evaluation parameters.

[0042] After step 120-1 of the embodiment, the evaluation parameters in each historical energy cycle stage can be obtained, including at least the current health state degradation degree coefficient , the target slope of the line between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage , the depth discharge coefficient D between the discharge end time point of each historical energy cycle stage and the charging end time point of the next historical energy cycle stage, and the internal structure damage coefficient L.

[0043] The evaluation parameters in each historical energy cycle stage can be further substituted into the battery degradation coefficient calculation formula to calculate the first battery degradation coefficient of the sodium-ion battery in the current energy cycle stage. The formula characteristic description of the battery degradation coefficient calculation formula is: In the formula, Represents the first cell degradation factor of the sodium-ion battery at the current energy cycle stage; Represents a collection of all complete historical energy cycle stages in the monitoring sodium-ion battery historical data; represent The collection A complete historical energy cycle stage; Represents the ratio of the target slope to the depth of discharge coefficient, Represents the average value of the above ratio for all historical energy cycle stages in the set of historical energy cycle stages; Representative The target slope of the line between the discharge end time point in a complete historical energy cycle stage and the charging end time point in the next historical energy cycle stage; Representative The depth of discharge coefficient between the end time of discharge in a complete historical energy cycle stage and the end time of charging in the next historical energy cycle stage, Sodium-ion batteries represent The current health status degradation coefficient of a complete historical energy cycle stage; Sodium-ion batteries represent The internal structure damage coefficient of a complete historical energy cycle stage.

[0044] Step 130: Send the first battery degradation coefficient to the data analysis module, so that the data analysis module calculates the real-time health status coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient. The real-time health status coefficient is used to characterize the health status of the sodium ion battery in the current energy cycle stage.

[0045] The second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than the preset health threshold and the battery is discarded. Alternatively, the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health degree is greater than or equal to the preset health threshold The specific calculation process of the second battery degradation coefficient can refer to the relevant descriptions in steps 110 and 120 of the above embodiment, which will not be repeated here. The battery degradation coefficient is The health status of this type of sodium-ion battery is considered to be 0, and the battery degradation factor is The health state of this type of sodium-ion battery is deemed to be 1; as a possible implementation method, the degree of difference between the battery degradation coefficient of the monitored sodium-ion battery and the battery degradation coefficient of the same type of sodium-ion battery with a health state of 1 can be determined, and the real-time health state coefficient of the sodium-ion battery is calculated based on the degree of difference; as another possible implementation method, the degree of difference between the battery degradation coefficient of the monitored sodium-ion battery and the battery degradation coefficient of the same type of sodium-ion battery with a health state of 0 can be determined, and the real-time health state coefficient of the sodium-ion battery is calculated based on the degree of difference. In this application, the second possible implementation method is taken as an example to illustrate the technical solution in this application, but it does not constitute a specific limitation. Specifically, the following formula can be used to calculate the real-time health state coefficient of the sodium-ion battery based on the degree of difference between the battery degradation coefficient of the monitored sodium-ion battery and the battery degradation coefficient of the same type of sodium-ion battery with a health state of 0: In the formula, Represents the real-time health status coefficient of the sodium-ion battery. When it is 0, it means that the health state of the sodium ion battery is poor. When it is 1, it means that the sodium-ion battery is relatively healthy; Represents the first cell degradation factor of the sodium-ion battery at the current energy cycle stage; The second battery degradation factor representing the same type of sodium-ion battery with a health state of 0; Represents the degree of difference in the health status of the two sodium-ion batteries; represents the linear normalization function.

[0046] In summary, the embodiments of the present invention provide a sodium ion battery health status assessment system and method for energy storage applications. The present invention calculates the first battery degradation coefficient of the sodium ion battery in the current energy cycle stage in real time by analyzing the target current data of the sodium ion battery during the charging and discharging process in each historical energy cycle stage, and determines the health status of the sodium ion battery based on the first battery degradation coefficient. When calculating the first battery degradation coefficient, the present invention can comprehensively consider multiple nonlinear factors in the process of sodium ion battery energy storage efficiency decay, overcome the limitations of traditional linear models in describing complex battery decay mechanisms, avoid the deviation between current and battery health status, and thus improve the accuracy of sodium ion battery health assessment.

[0047] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0049] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A sodium ion battery health status assessment system for energy storage applications, characterized in that: The system includes: a data acquisition module, a data preprocessing module, a data storage module, a battery status evaluation module and a data analysis module; The data acquisition module is connected to the positive and negative electrodes of the sodium ion battery and is used to collect current data of the sodium ion battery in real time; The data preprocessing module is connected to the data acquisition module and is used to preprocess the current data, wherein the preprocessing at least includes data cleaning and denoising; The data storage module is connected to the data preprocessing module and is used to store the preprocessed current data; The battery state evaluation module is connected to the data storage module, and is used to obtain the target current data of the sodium ion battery in each historical energy cycle stage in the data storage module, and calculate the first battery degradation coefficient of the sodium ion battery in the current energy cycle stage based on the target current data; The data analysis module is connected to the battery status evaluation module, and the data analysis module is used to calculate the real-time health status coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient, and the real-time health status coefficient is used to characterize the health status of the sodium ion battery in the current energy cycle stage, and the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than a preset health threshold and the battery is discarded, or the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health is greater than or equal to the preset health threshold.

2. The sodium ion battery health status assessment system for energy storage applications according to claim 1, characterized in that: The system also includes: a health data visualization module and an alarm module; The health data visualization module and the alarm module are respectively connected to the data analysis module, the health data visualization module is used to display the real-time health status coefficient in real time, and the alarm module is used to issue an alarm prompt of abnormal health status of the sodium ion battery when it is judged that the real-time health status coefficient is greater than a preset threshold.

3. The sodium ion battery health status assessment system for energy storage applications according to claim 1, characterized in that: The calculating, based on the target current data, a first battery degradation coefficient of the sodium ion battery in the current energy cycle stage comprises: Determining an evaluation parameter of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage; A first battery degradation factor of the sodium ion battery in a current energy cycle stage is calculated based on the evaluation parameters.

4. The sodium ion battery health status assessment system for energy storage applications according to claim 3, characterized in that: The evaluation parameters include a current health state degradation coefficient; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Calculating a first degradation indicator of a state of health and a second degradation indicator of a state of health of the sodium ion battery at each of the historical energy cycle stages according to the target current data of the sodium ion battery at each of the historical energy cycle stages; Based on the first health state degradation indicator and the second health state degradation indicator, a current health state degradation degree coefficient of the sodium ion battery in each of the historical energy cycle stages is calculated.

5. The sodium ion battery health status assessment system for energy storage applications according to claim 4, characterized in that: The step of calculating the first health state degradation index and the second health state degradation index of the sodium ion battery in each of the historical energy cycle stages according to the target current data of the sodium ion battery in each of the historical energy cycle stages comprises: Determining a first fitting curve of a battery charging current and a second fitting curve of a battery discharging current based on target current data of the sodium ion battery at each of the historical energy cycle stages; Extracting a first data point of a data peak in the first fitting curve and a second data point of a data peak in the second fitting curve; Performing data point matching on the first data point and the second data point to obtain a set of corresponding points between all peaks; Determining the Euclidean distance variance of each corresponding point in the corresponding point set as the first degradation indicator of the health state of the sodium ion battery in the corresponding historical energy cycle stage; Based on the maximum value points and the minimum value points on the first fitting curve and the second fitting curve, respectively determine the upper envelope and the lower envelope of the first fitting curve and the second fitting curve; The absolute value of the phase difference between the upper envelope and the lower envelope of the same fitting curve and the frequency domain data corresponding to the upper envelope is determined as the second degradation indicator of the health state of the sodium ion battery in the corresponding historical energy cycle stage.

6. The sodium ion battery health status assessment system for energy storage applications according to claim 4, characterized in that: The step of calculating the current health state degradation coefficient of the sodium ion battery at each of the historical energy cycle stages based on the first health state degradation indicator and the second health state degradation indicator includes: Normalizing the first health state degradation index and the second health state degradation index of the sodium ion battery at the same historical energy cycle stage respectively; The product of the normalized first health state degradation index and the second health state degradation index is calculated, and the product is determined as the current health state degradation degree coefficient of the sodium ion battery in the corresponding historical energy cycle stage.

7. The sodium ion battery health status assessment system for energy storage applications according to claim 3, characterized in that: The evaluation parameters include the target slope of the line between the discharge end time point of each historical energy cycle stage and the charge end time point of the next historical energy cycle stage, and the depth of discharge coefficient between the discharge end time point of each historical energy cycle stage and the charge end time point of the next historical energy cycle stage; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Determine, according to the target current data of the sodium ion battery in each historical energy cycle stage, the discharge end time point of the sodium ion battery in each historical energy cycle stage, and the charging end time point of the sodium ion battery in each historical energy cycle stage corresponding to the next historical energy cycle stage; Determining the slope of a line between the discharge end time point and the charge end time point as the target slope; A first time interval between the discharge end time point and the charge end time point is determined as the deep discharge coefficient.

8. The sodium ion battery health status assessment system for energy storage applications according to claim 3, characterized in that: The evaluation parameters include internal structure damage coefficient; Determining the evaluation parameters of the sodium ion battery at each historical energy cycle stage according to the target current data of the sodium ion battery at each historical energy cycle stage includes: Based on the target current data of the sodium ion battery in each of the historical energy cycle stages, determining a first fitting curve of the battery charging current, a second fitting curve of the battery discharging current, and a discharge end time point of the sodium ion battery in each of the historical energy cycle stages; Constructing a window area for each maximum point in the first fitting curve and the second fitting curve; Calculating the current turbulence characteristic coefficient of each window area, and determining the maximum value point corresponding to the maximum current turbulence characteristic coefficient among the plurality of maximum value points as the target maximum value point; Determine the time node of the target maximum value point as the optimal efficiency end node of the sodium ion battery corresponding to the historical energy cycle stage; The second time interval distance between the optimal efficiency end node and the discharge end time point is determined as the internal structure damage coefficient of the sodium ion battery corresponding to the historical energy cycle stage.

9. The sodium ion battery health status assessment system for energy storage applications according to claim 8, characterized in that: The calculating of the current disorder characteristic coefficient of each window area includes: Determine window area information of each of the window areas, the window area information at least including a set of extreme value points contained in the window area, a slope of each extreme value point in the set of extreme value points at the first fitting curve or the second fitting curve, and an occurrence probability of each extreme value point in the set of extreme value points in the target current data, the extreme value points including maximum value points and minimum value points; A current disorder characteristic coefficient of each window area is calculated based on the window area information.

10. A sodium ion battery health status assessment method for energy storage applications, characterized in that: The method is applied to the sodium ion battery health status assessment system for energy storage applications according to any one of claims 1 to 9, and the method comprises: Obtain target current data of sodium-ion batteries at each historical energy cycle stage; Calculating a first battery degradation factor of the sodium ion battery in a current energy cycle stage based on the target current data; The first battery degradation coefficient is sent to a data analysis module, so that the data analysis module calculates the real-time health status coefficient of the sodium ion battery based on the first battery degradation coefficient and the second battery degradation coefficient, wherein the real-time health status coefficient is used to characterize the health status of the sodium ion battery in the current energy cycle stage, and the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery corresponding to the same type of sodium ion battery when the health is less than a preset health threshold and the battery is discarded, or the second battery degradation coefficient is the battery degradation coefficient of the sodium ion battery when the health is greater than or equal to the preset health threshold.

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