Method for monitoring and evaluating chemical properties of waste aluminum shell battery in real time and related device

Abstract

The invention discloses a waste aluminum shell battery chemical performance real-time monitoring and evaluating method and a related device, and the method comprises the steps: a monitoring terminal establishes communication connection with a miniature chemical sensor in a waste aluminum shell battery, and receives a plurality of electrochemical signals collected by the miniature chemical sensor; performing signal feature extraction processing on the plurality of electrochemical signals to obtain electrochemical signal feature data; based on the battery model data of the waste aluminum shell battery, indexing to a corresponding battery monitoring and evaluation model, and inputting the electrochemical signal characteristic data into the battery monitoring and evaluation model for diagnosis and evaluation processing to obtain a monitoring and evaluation result corresponding to the waste aluminum shell battery; and performing monitoring evaluation report generation processing based on the monitoring evaluation result, and performing storage processing on the generated monitoring evaluation report according to a preset storage rule. According to the embodiment of the invention, the method achieves the accurate diagnosis and evaluation of the health state of the battery, and provides powerful support for the recovery and management of the waste aluminum shell battery.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy batteries, and in particular to a method for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries and related devices. Background Art

[0002] With the advancement of modern science and technology and the increasing emphasis on renewable energy, battery technology has developed rapidly and has become an indispensable energy source for driving electronic devices and electric vehicles. Among them, aluminum-shell batteries are widely used in electric vehicles, energy storage and other fields due to their superior energy density, long cycle life and relatively light weight. With the continuous expansion of market demand, the production and application of aluminum-shell batteries have rapidly become popular and have become the basic power source for all walks of life around the world.

[0003] Faced with the widespread use of aluminum shell batteries, the recycling and management of waste aluminum shell batteries has also become an urgent problem to be solved; the sources of aluminum shell batteries are complex, including consumer electronics used in daily life, power batteries in vehicles, etc. After use, it is often difficult to judge the internal state of these batteries by their appearance characteristics; for example, the battery may have internal short circuits, plate corrosion or slight internal detachment of electrode materials due to long-term use, and these cannot be identified by appearance inspection alone; therefore, simple visual observation alone cannot effectively distinguish between reusable aluminum shell batteries and expired batteries. Summary of the Invention

[0004] The purpose of the present invention is to overcome the shortcomings of the existing technology. The present invention provides a real-time monitoring and evaluation method and related devices for the chemical properties of waste aluminum shell batteries, which can accurately diagnose and evaluate the health status of batteries and provide strong support for the recycling and management of waste aluminum shell batteries.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries, which is applied to waste aluminum shell batteries, wherein a micro chemical sensor is provided in the waste aluminum shell batteries; the method comprises:

[0006] The monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, wherein each of the plurality of electrochemical signals is marked with a collection time and a sensor ID corresponding to the micro chemical sensor;

[0007] The monitoring terminal extracts signal features from the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals;

[0008] The monitoring terminal indexes the battery model data of the waste aluminum shell battery to the corresponding battery monitoring and evaluation model, and inputs the electrochemical signal characteristic data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery;

[0009] The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule.

[0010] Optionally, the monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, including:

[0011] The monitoring terminal obtains the battery number of the waste aluminum shell battery and generates a connection authentication request for establishing a communication connection with the micro chemical sensor based on the battery number;

[0012] When the monitoring terminal enters the signal coverage range of the micro chemical sensor, the connection authentication request is sent to the micro chemical sensor via a temporary communication connection within the signal coverage range of the micro chemical sensor;

[0013] After the micro chemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the micro chemical sensor and receives a plurality of electrochemical signals collected and uploaded by the micro chemical sensor, wherein the plurality of electrochemical signals are obtained by the micro chemical sensor when starting to collect at intervals during the charging and discharging of the waste aluminum shell battery.

[0014] Optionally, the monitoring terminal extracts signal features from the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals, including:

[0015] The monitoring terminal preprocesses the received electrochemical signals to obtain preprocessed electrochemical signals;

[0016] The pre-processed electrochemical signals are sequentially subjected to feature extraction processing of peak voltage, peak area and half-peak width to obtain electrochemical signal feature data corresponding to the electrochemical signals, the electrochemical signal feature data including peak voltage data, peak area data and half-peak width data.

[0017] Optionally, the monitoring terminal preprocesses the received electrochemical signals to obtain the preprocessed electrochemical signals, including:

[0018] The monitoring terminal identifies electrode electrochemical signals from the plurality of electrochemical signals based on a machine learning algorithm, and removes non-electrode electrochemical signals from the plurality of electrochemical signals based on the identification results to form a plurality of electrochemical signals after initial processing, wherein the machine learning algorithm is an algorithm that has been trained and converged using waveform and frequency amplitude characteristics in the electrode electrochemical signals;

[0019] The monitoring terminal performs calculation processing on the multiple electrochemical signals after initial processing to obtain expected signal values, standard deviation values, and covariance values ​​corresponding to the multiple electrochemical signals;

[0020] performing a joint probability density calculation process on each electrochemical signal using the expected signal values ​​and covariance values ​​corresponding to the plurality of electrochemical signals based on a joint probability density function to obtain a joint probability density value corresponding to each electrochemical signal;

[0021] performing electrochemical signal elimination processing based on a joint probability density value corresponding to each of the plurality of electrochemical signals and the standard deviation value to obtain the plurality of electrochemical signals after elimination;

[0022] Interpolation processing is performed on the eliminated electrochemical signals based on a linear interpolation algorithm to obtain interpolated electrochemical signals, and the interpolated electrochemical signals are used as preprocessed electrochemical signals.

[0023] Optionally, the monitoring terminal indexes the corresponding battery monitoring and evaluation model based on the battery model data of the waste aluminum shell battery, including:

[0024] The monitoring terminal obtains battery model data corresponding to the waste aluminum shell battery;

[0025] The battery model data is used to perform matching processing in a model database, and a battery monitoring and evaluation model consistent with the battery model data is indexed according to the matching result; the model database stores battery monitoring and evaluation models corresponding to several aluminum shell batteries of different battery models, and each battery monitoring and evaluation model is a model that converges on a pre-constructed digital twin network trained using electrochemical signal feature data extracted from electrochemical signals of aluminum shell batteries of corresponding models under different battery states. The pre-constructed digital twin network is formed by modifying digital twin network parameters using aluminum shell battery parameters corresponding to different battery models.

[0026] Optionally, inputting the electrochemical signal characteristic data corresponding to the plurality of electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery includes:

[0027] inputting the electrochemical signal characteristic data corresponding to the plurality of electrochemical signals into the battery monitoring and evaluation model in sequence;

[0028] After receiving the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, the battery monitoring and evaluation model performs a charge and discharge simulation evaluation process on the waste aluminum shell battery based on the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, and outputs the charge and discharge simulation evaluation result of the waste aluminum shell battery as the monitoring and evaluation result corresponding to the waste aluminum shell battery.

[0029] Optionally, the monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule, including:

[0030] The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation results according to a preset report template to obtain a monitoring and evaluation report corresponding to the waste aluminum shell battery;

[0031] The monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with the plurality of electrochemical signals, and the associated monitoring and evaluation report is stored according to a preset storage rule.

[0032] In addition, an embodiment of the present invention further provides a device for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries, which is applied to waste aluminum shell batteries, wherein a micro chemical sensor is provided in the waste aluminum shell batteries; the device comprises:

[0033] Data receiving module: used for establishing a communication connection between the monitoring terminal and the micro chemical sensor in the waste aluminum shell battery, and receiving a plurality of electrochemical signals collected by the micro chemical sensor, each of the plurality of electrochemical signals being marked with the collection time and the sensor ID corresponding to the micro chemical sensor;

[0034] Feature extraction module: used for the monitoring terminal to extract signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals;

[0035] Diagnostic evaluation module: used for the monitoring terminal to index the battery model data of the waste aluminum shell battery to the corresponding battery monitoring and evaluation model, and input the electrochemical signal characteristic data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery;

[0036] Data storage module: used for the monitoring terminal to generate a monitoring and evaluation report based on the monitoring and evaluation results, and to store the generated monitoring and evaluation report according to preset storage rules.

[0037] In addition, an embodiment of the present invention further provides a monitoring terminal comprising a processor and a memory, wherein the processor runs a computer program or code stored in the memory to implement the real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries as described in any one of the above.

[0038] In addition, an embodiment of the present invention further provides a computer-readable storage medium for storing a computer program or code. When the computer program or code is executed by a processor, the method for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries as described in any one of the above is implemented.

[0039] In an embodiment of the present invention, electrochemical signal collection is achieved by providing a micro chemical sensor on the waste aluminum shell battery; the monitoring terminal communicates with the micro chemical sensor to obtain a number of electrochemical signals; the signal characteristics of the multiple electrochemical signals are extracted and processed to obtain electrochemical signal characteristic data; the battery model data of the waste aluminum shell battery is indexed into the corresponding battery monitoring and evaluation model, and the electrochemical signal characteristic data is input into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery; a monitoring and evaluation report is generated based on the monitoring and evaluation results, and the generated monitoring and evaluation report is stored and processed according to preset storage rules; in this way, accurate diagnosis and evaluation of the health status of the battery is achieved, which provides strong support for the recycling and management of the waste aluminum shell battery, and facilitates the direct viewing or review of the monitoring and evaluation report by subsequent management users. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order 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. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 1 is a flow chart of a method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries in an embodiment of the present invention;

[0042] Figure 2 1 is a flow chart of a method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries in another embodiment of the present invention;

[0043] Figure 3Schematic diagram of the structure of the device for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries in an embodiment of the present invention;

[0044] Figure 4 It is a schematic diagram of the structural composition of the monitoring terminal in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] For example 1, please refer to Figure 1 , Figure 1 It is a flow chart of a method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries in an embodiment of the present invention.

[0047] like Figure 1 As shown, a real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries is applied to waste aluminum shell batteries, and a micro chemical sensor is provided on the waste aluminum shell batteries; the method comprises:

[0048] S101: The monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, wherein each of the plurality of electrochemical signals is marked with a collection time and a sensor ID corresponding to the micro chemical sensor;

[0049] In the specific implementation process of the present invention, the monitoring terminal establishes a communication connection with the microchemical sensor in the waste aluminum shell battery and receives a number of electrochemical signals collected by the microchemical sensor, including: the monitoring terminal obtains the battery number of the waste aluminum shell battery, and generates a connection authentication request to establish a communication connection with the microchemical sensor based on the battery number; when the monitoring terminal enters the signal coverage range of the microchemical sensor, the connection authentication request is sent to the microchemical sensor through a temporary communication connection within the signal coverage range of the microchemical sensor; after the microchemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the microchemical sensor and receives a number of electrochemical signals collected and uploaded by the microchemical sensor, wherein the several electrochemical signals are obtained by the microchemical sensor starting to collect at intervals when the waste aluminum shell battery is charged and discharged.

[0050] Specifically, the micro-electrochemical sensor is installed on the outer shell of the aluminum shell battery or in the internal probe to ensure that the sensor is in good contact with the electrode material inside the battery. It can be set in two locations. One way is to set it on the electrode surface inside the aluminum shell battery. In this way, the micro-electrochemical sensor can be integrated into the surface or near the target electrode material, which can most directly monitor the electrochemical reaction, such as embedding the sensor chip into the substrate of the electrode material, or using a special coating technology to coat the sensor material on the electrode surface. The other way is to set it in the electrolyte inside the aluminum shell battery. The micro-electrochemical sensor can be placed in the electrolyte, close to the target electrode material, and monitor the electrochemical signal through ion transmission in the electrolyte to ensure that the sensor can accurately reflect the electrochemical state of the electrode material. The micro-electrochemical sensor can be used to collect data from the aluminum shell battery. The micro-electrochemical sensor is a highly sensitive device for detecting and measuring chemical substances. The micro-electrochemical sensor is based on the principle of electrochemical reaction and detects its concentration by measuring the electrical signal generated by the target substance on the electrode surface. Electrochemical reaction refers to a chemical reaction that occurs during electron transfer. The current or potential change generated is related to the concentration of the target substance. Therefore, by measuring the changes in these electrical signals, the concentration of the target substance can be known. According to the working principle and application scenario, micro-electrochemical sensors can be divided into many types, such as conductivity type, potentiometric type and amperometric type. Among them, conductivity type sensors detect target substances by measuring the change in conductivity of the solution; potentiometric sensors detect target substances by measuring the potential difference between electrodes; and amperometric sensors detect target substances by measuring the magnitude of the current.

[0051] At the same time, there is a battery number on the waste aluminum shell battery. First, the battery number of the waste aluminum shell battery is obtained through the monitoring terminal, and then a connection authentication request for establishing a communication connection with the micro chemical sensor is generated according to the battery number; when the monitoring terminal enters the signal coverage range of the micro chemical sensor, the connection authentication request is sent to the micro chemical sensor through a temporary communication connection within the signal coverage range of the micro chemical sensor; after the micro chemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the micro chemical sensor and receives a number of electrochemical signals collected and uploaded by the micro chemical sensor, wherein the several electrochemical signals are obtained by the micro chemical sensor when starting to collect at intervals when the waste aluminum shell battery is charged and discharged; by marking the electrochemical signals according to the collection time and the sensor ID corresponding to the micro chemical sensor, the order of the electrochemical signals can be ensured to be not disordered, which is convenient for subsequent feature extraction processing and fault diagnosis and prediction of the aluminum shell battery; by marking the sensor ID, it is convenient to directly find the corresponding waste aluminum shell battery in the future, and there will be no misjudgment of the waste aluminum shell battery.

[0052] When a micro-electrochemical sensor performs detection and data collection, a threshold detection method is used. That is, a threshold value of signal strength is set. Signals above this threshold value are considered valid electrochemical signals and are collected. For example, the threshold value of signal amplitude is set to 0.01V, and only signals exceeding this threshold value are considered valid electrochemical signals.

[0053] S102: The monitoring terminal extracts signal features from the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals;

[0054] In the specific implementation process of the present invention, the monitoring terminal extracts and processes the signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals, including: the monitoring terminal preprocesses the received electrochemical signals to obtain the preprocessed electrochemical signals; and extracts and processes the peak voltage, peak area and half-peak width of the preprocessed electrochemical signals in turn to obtain electrochemical signal feature data corresponding to the electrochemical signals, and the electrochemical signal feature data includes peak voltage data, peak area data and half-peak width data.

[0055] Furthermore, the monitoring terminal pre-processes the received electrochemical signals to obtain the pre-processed electrochemical signals, including: the monitoring terminal identifies the electrode electrochemical signals in the electrochemical signals based on the machine learning algorithm, and removes the non-electrode electrochemical signals in the electrochemical signals according to the identification results to form the electrochemical signals after initial processing, wherein the machine learning algorithm is an algorithm trained and converged using the waveform and frequency amplitude characteristics in the electrode electrochemical signals; the monitoring terminal performs computational processing on the electrochemical signals after initial processing to obtain the expected signal values, standard deviations and other parameters corresponding to the electrochemical signals. difference and covariance value; based on the joint probability density function, using the expected signal value and covariance value corresponding to the several electrochemical signals to calculate the joint probability density of each electrochemical signal, and obtain the joint probability density value corresponding to each electrochemical signal; based on the joint probability density value corresponding to each electrochemical signal of the several electrochemical signals and the standard deviation value, perform electrochemical signal elimination processing to obtain several electrochemical signals after elimination; based on the linear interpolation algorithm, perform interpolation processing on the several electrochemical signals after elimination to obtain several electrochemical signals after interpolation, and use the several electrochemical signals after interpolation as several electrochemical signals after preprocessing.

[0056] Specifically, before performing electrochemical signal feature extraction on a plurality of electrochemical signals, it is first necessary to preprocess the plurality of electrochemical signals to obtain a plurality of preprocessed electrochemical signals; finally, the plurality of preprocessed electrochemical signals are subjected to feature extraction processing of peak voltage, peak area and half-peak width in turn to obtain electrochemical signal feature data corresponding to the plurality of electrochemical signals, and the electrochemical signal feature data include peak voltage data, peak area data and half-peak width data; specifically, the plurality of preprocessed electrochemical signals are represented in a linear manner, and the high point, the formed peak area and half-peak width and other data in the linear representation are calculated to obtain the electrochemical signal feature data including peak voltage data, peak area data and half-peak width data, and use them as the electrochemical signal feature data corresponding to the plurality of electrochemical signals.

[0057] Among them, during preprocessing, the electrode electrochemical signals and non-electrode interfering electrochemical signals in several electrochemical signals are first identified by a machine learning algorithm, and the non-electrode interfering electrochemical signals are removed; several electrochemical signals after initial processing are formed, and the machine learning algorithm is an algorithm after training and convergence using the waveform, frequency and amplitude characteristics in the electrode electrochemical signals; the expected calculation formula (arithmetic mean as the expected signal value), standard deviation calculation formula and covariance calculation formula are used to calculate and process the several electrochemical signals after initial processing, so as to obtain the expected signal values, standard deviation values ​​and covariance values ​​corresponding to the several electrochemical signals; and then the expected signal values, standard deviation values ​​and covariance values ​​corresponding to the several electrochemical signals are obtained by using the expected calculation formula (arithmetic mean as the expected signal value), standard deviation calculation formula and covariance calculation formula. The expected signal values ​​and covariance values ​​corresponding to several electrochemical signals call a joint probability density function to calculate the joint probability density of each electrochemical signal, thereby obtaining the joint probability density value corresponding to each electrochemical signal; then, the electrochemical signal is eliminated according to the joint probability density value and standard deviation value corresponding to each electrochemical signal of the several electrochemical signals to obtain several electrochemical signals after elimination; after eliminating a certain electrochemical signal, it is necessary to interpolate the several electrochemical signals after elimination through a linear interpolation algorithm to obtain several electrochemical signals after interpolation, and use the several electrochemical signals after interpolation as several electrochemical signals after preprocessing.

[0058] S103: The monitoring terminal indexes the battery model data of the waste aluminum shell battery to a corresponding battery monitoring and evaluation model, and inputs the electrochemical signal feature data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain a monitoring and evaluation result corresponding to the waste aluminum shell battery;

[0059] During the specific implementation of the present invention, the monitoring terminal indexes the corresponding battery monitoring and evaluation model based on the battery model data of the waste aluminum shell battery, including: the monitoring terminal obtains the battery model data corresponding to the waste aluminum shell battery; uses the battery model data to perform matching processing in the model database, and indexes the battery monitoring and evaluation model consistent with the battery model data according to the matching result; the model database stores battery monitoring and evaluation models corresponding to several aluminum shell batteries with different battery models, and each battery monitoring and evaluation model is a model that converges on a pre-constructed digital twin network trained using electrochemical signal feature data extracted from the electrochemical signals of the corresponding model of aluminum shell batteries under different battery states, and the pre-constructed digital twin network is formed by modifying the digital twin network parameters using aluminum shell battery parameters corresponding to different battery models.

[0060] Furthermore, the electrochemical signal characteristic data corresponding to the several electrochemical signals are input into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery, including: inputting the electrochemical signal characteristic data corresponding to the several electrochemical signals into the battery monitoring and evaluation model in sequence; after receiving the electrochemical signal characteristic data corresponding to the several electrochemical signals, the battery monitoring and evaluation model performs charge and discharge simulation evaluation processing of the waste aluminum shell battery based on the electrochemical signal characteristic data corresponding to the several electrochemical signals, and outputs the charge and discharge simulation evaluation results of the waste aluminum shell battery as the monitoring and evaluation results corresponding to the waste aluminum shell battery.

[0061] Specifically, in order to ensure the accuracy of battery monitoring and evaluation, it is necessary to select the corresponding battery monitoring and evaluation model according to different battery models; therefore, the monitoring terminal needs to obtain the battery model data corresponding to the waste aluminum shell battery; then the battery model data is matched in the model database, and the battery monitoring and evaluation model consistent with the battery model data is indexed according to the matching result; wherein the model database stores battery monitoring and evaluation models corresponding to several different battery models of aluminum shell batteries, and each battery monitoring and evaluation model is a model that converges on the pre-constructed digital twin network using the electrochemical signal feature data extracted from the electrochemical signals of the corresponding model of aluminum shell batteries under different battery states. The pre-constructed digital twin network is formed by modifying the digital twin network parameters using the aluminum shell battery parameters corresponding to different battery models.

[0062] After selecting the corresponding battery monitoring and evaluation model, the electrochemical signal characteristic data corresponding to the multiple electrochemical signals need to be input into the battery monitoring and evaluation model in sequence; then, after receiving the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, the battery monitoring and evaluation model performs a charge and discharge simulation evaluation process of the waste aluminum shell battery through the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, wherein the charge and discharge simulation evaluation includes estimating the battery capacity, internal resistance, power density and other performance parameters of the waste aluminum shell battery; finally, the charge and discharge simulation evaluation result of the waste aluminum shell battery is output as the monitoring and evaluation result corresponding to the waste aluminum shell battery; thereby, the corresponding monitoring and evaluation result of the waste aluminum shell battery can be obtained more accurately, thereby realizing the monitoring and evaluation of the waste aluminum shell battery.

[0063] During the diagnostic evaluation, after obtaining the battery capacity, internal resistance and power density data of the waste aluminum shell battery, the health and life span of the battery will be evaluated based on these parameters, thereby generating the corresponding monitoring and evaluation results of the waste aluminum shell battery; for example, if the internal resistance is greater than 0.5ω; the discharge capacity decay rate exceeds 50%, it can be determined that the waste aluminum shell battery has entered the scrap process and cannot be recycled, otherwise there will be uncontrollable risks; or it can be judged by capacity, that is, using a linear regression model to assume that the battery capacity decays linearly with time; the model form is as follows: C(t) = C(0) + βC(t); where C(t) is the battery capacity at time t, C(0) is the initial capacity, and β is the capacity decay rate (obtained by fitting the parameters extracted multiple times).

[0064] S104: The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule.

[0065] During the specific implementation of the present invention, the monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation results, and stores the generated monitoring and evaluation report according to preset storage rules, including: the monitoring terminal generates a monitoring and evaluation report according to a preset report template based on the monitoring and evaluation results to obtain a monitoring and evaluation report corresponding to the waste aluminum shell battery; the monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with the multiple electrochemical signals, and the associated monitoring and evaluation report is stored according to the preset storage rules.

[0066] Specifically, in order to facilitate subsequent management users to view and review the monitoring and evaluation results, the monitoring terminal needs to generate and process the monitoring and evaluation report according to the preset report template based on the monitoring and evaluation results, thereby generating a monitoring and evaluation report corresponding to the waste aluminum shell battery; then the monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with a number of electrochemical signals, and the associated monitoring and evaluation report is stored and processed according to the preset storage rules; this can facilitate the subsequent provision of an intuitive operation interface and rich data reports for management users; management users can view real-time monitoring data, battery status indications and fault warning information through the interface, and generate a detailed battery health status report to facilitate management and decision-making.

[0067] For example 2, please refer to Figure 2 , Figure 2 It is a flow chart of a method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries in another embodiment of the present invention.

[0068] like Figure 2 As shown, a real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries is applied to waste aluminum shell batteries, wherein a micro chemical sensor is provided in the waste aluminum shell batteries; the method comprises:

[0069] S201: The monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, wherein each of the plurality of electrochemical signals is marked with a collection time and a sensor ID corresponding to the micro chemical sensor;

[0070] S202: The monitoring terminal identifies electrode electrochemical signals from the plurality of electrochemical signals based on a machine learning algorithm, and removes non-electrode electrochemical signals from the plurality of electrochemical signals based on the identification results to form a plurality of electrochemical signals after initial processing, wherein the machine learning algorithm is an algorithm trained and converged using waveform and frequency amplitude features in the electrode electrochemical signals;

[0071] S203: The monitoring terminal performs calculation processing on the multiple electrochemical signals after initial processing to obtain expected signal values, standard deviation values, and covariance values ​​corresponding to the multiple electrochemical signals;

[0072] S204: performing joint probability density calculation processing on each electrochemical signal using the expected signal values ​​and covariance values ​​corresponding to the plurality of electrochemical signals based on the joint probability density function to obtain a joint probability density value corresponding to each electrochemical signal;

[0073] S205: performing electrochemical signal elimination processing based on the joint probability density value corresponding to each of the plurality of electrochemical signals and the standard deviation value to obtain the plurality of electrochemical signals after elimination;

[0074] S206: performing interpolation processing on the eliminated electrochemical signals based on a linear interpolation algorithm to obtain interpolated electrochemical signals, and using the interpolated electrochemical signals as preprocessed electrochemical signals;

[0075] S207: performing feature extraction processing on the plurality of pre-processed electrochemical signals in terms of peak voltage, peak area, and half-peak width in sequence to obtain electrochemical signal feature data corresponding to the plurality of electrochemical signals, the electrochemical signal feature data including peak voltage data, peak area data, and half-peak width data;

[0076] S208: The monitoring terminal indexes the battery model data of the waste aluminum shell battery to a corresponding battery monitoring and evaluation model, and inputs the electrochemical signal feature data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain a monitoring and evaluation result corresponding to the waste aluminum shell battery;

[0077] S209: The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule.

[0078] Specifically, the specific implementation of Example 2 can be found in Example 1, which will not be repeated here.

[0079] For example three, please refer to Figure 3 , Figure 3 It is a schematic diagram of the structural composition of the device for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries in an embodiment of the present invention.

[0080] like Figure 3 As shown, a device for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries is applied to waste aluminum shell batteries, wherein a micro chemical sensor is provided in the waste aluminum shell batteries; the device comprises:

[0081] Data receiving module 301: used for establishing a communication connection between the monitoring terminal and the micro chemical sensor in the waste aluminum shell battery, and receiving a plurality of electrochemical signals collected by the micro chemical sensor, each of the plurality of electrochemical signals being marked with the collection time and the sensor ID corresponding to the micro chemical sensor;

[0082] In the specific implementation process of the present invention, the monitoring terminal establishes a communication connection with the microchemical sensor in the waste aluminum shell battery and receives a number of electrochemical signals collected by the microchemical sensor, including: the monitoring terminal obtains the battery number of the waste aluminum shell battery, and generates a connection authentication request to establish a communication connection with the microchemical sensor based on the battery number; when the monitoring terminal enters the signal coverage range of the microchemical sensor, the connection authentication request is sent to the microchemical sensor through a temporary communication connection within the signal coverage range of the microchemical sensor; after the microchemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the microchemical sensor and receives a number of electrochemical signals collected and uploaded by the microchemical sensor, wherein the several electrochemical signals are obtained by the microchemical sensor starting to collect at intervals when the waste aluminum shell battery is charged and discharged.

[0083] Specifically, the micro-electrochemical sensor is installed on the outer shell of the aluminum shell battery or in the internal probe to ensure that the sensor is in good contact with the electrode material inside the battery. It can be set in two locations. One way is to set it on the electrode surface inside the aluminum shell battery. In this way, the micro-electrochemical sensor can be integrated into the surface or near the target electrode material, which can most directly monitor the electrochemical reaction, such as embedding the sensor chip into the substrate of the electrode material, or using a special coating technology to coat the sensor material on the electrode surface. The other way is to set it in the electrolyte inside the aluminum shell battery. The micro-electrochemical sensor can be placed in the electrolyte, close to the target electrode material, and monitor the electrochemical signal through ion transmission in the electrolyte to ensure that the sensor can accurately reflect the electrochemical state of the electrode material. The micro-electrochemical sensor can be used to collect data from the aluminum shell battery. The micro-electrochemical sensor is a highly sensitive device for detecting and measuring chemical substances. The micro-electrochemical sensor is based on the principle of electrochemical reaction and detects its concentration by measuring the electrical signal generated by the target substance on the electrode surface. Electrochemical reaction refers to a chemical reaction that occurs during electron transfer. The current or potential change generated is related to the concentration of the target substance. Therefore, by measuring the changes in these electrical signals, the concentration of the target substance can be known. According to the working principle and application scenario, micro-electrochemical sensors can be divided into many types, such as conductivity type, potentiometric type and amperometric type. Among them, conductivity type sensors detect target substances by measuring the change in conductivity of the solution; potentiometric sensors detect target substances by measuring the potential difference between electrodes; and amperometric sensors detect target substances by measuring the magnitude of the current.

[0084] At the same time, there is a battery number on the waste aluminum shell battery. First, the battery number of the waste aluminum shell battery is obtained through the monitoring terminal, and then a connection authentication request for establishing a communication connection with the micro chemical sensor is generated according to the battery number; when the monitoring terminal enters the signal coverage range of the micro chemical sensor, the connection authentication request is sent to the micro chemical sensor through a temporary communication connection within the signal coverage range of the micro chemical sensor; after the micro chemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the micro chemical sensor and receives a number of electrochemical signals collected and uploaded by the micro chemical sensor, wherein the several electrochemical signals are obtained by the micro chemical sensor when starting to collect at intervals when the waste aluminum shell battery is charged and discharged; by marking the electrochemical signals according to the collection time and the sensor ID corresponding to the micro chemical sensor, the order of the electrochemical signals can be ensured to be not disordered, which is convenient for subsequent feature extraction processing and fault diagnosis and prediction of the aluminum shell battery; by marking the sensor ID, it is convenient to directly find the corresponding waste aluminum shell battery in the future, and there will be no misjudgment of the waste aluminum shell battery.

[0085] When a micro-electrochemical sensor performs detection and data collection, a threshold detection method is used. That is, a threshold value of signal strength is set. Signals above this threshold value are considered valid electrochemical signals and are collected. For example, the threshold value of signal amplitude is set to 0.01V, and only signals exceeding this threshold value are considered valid electrochemical signals.

[0086] Feature extraction module 302: configured for the monitoring terminal to extract signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals;

[0087] In the specific implementation process of the present invention, the monitoring terminal extracts and processes the signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals, including: the monitoring terminal preprocesses the received electrochemical signals to obtain the preprocessed electrochemical signals; and extracts and processes the peak voltage, peak area and half-peak width of the preprocessed electrochemical signals in turn to obtain electrochemical signal feature data corresponding to the electrochemical signals, and the electrochemical signal feature data includes peak voltage data, peak area data and half-peak width data.

[0088] Furthermore, the monitoring terminal pre-processes the received electrochemical signals to obtain the pre-processed electrochemical signals, including: the monitoring terminal identifies the electrode electrochemical signals in the electrochemical signals based on the machine learning algorithm, and removes the non-electrode electrochemical signals in the electrochemical signals according to the identification results to form the electrochemical signals after initial processing, wherein the machine learning algorithm is an algorithm trained and converged using the waveform and frequency amplitude characteristics in the electrode electrochemical signals; the monitoring terminal performs computational processing on the electrochemical signals after initial processing to obtain the expected signal values, standard deviations and other parameters corresponding to the electrochemical signals. difference and covariance value; based on the joint probability density function, using the expected signal value and covariance value corresponding to the several electrochemical signals to calculate the joint probability density of each electrochemical signal, and obtain the joint probability density value corresponding to each electrochemical signal; based on the joint probability density value corresponding to each electrochemical signal of the several electrochemical signals and the standard deviation value, perform electrochemical signal elimination processing to obtain several electrochemical signals after elimination; based on the linear interpolation algorithm, perform interpolation processing on the several electrochemical signals after elimination to obtain several electrochemical signals after interpolation, and use the several electrochemical signals after interpolation as several electrochemical signals after preprocessing.

[0089] Specifically, before performing electrochemical signal feature extraction on a plurality of electrochemical signals, it is first necessary to preprocess the plurality of electrochemical signals to obtain a plurality of preprocessed electrochemical signals; finally, the plurality of preprocessed electrochemical signals are subjected to feature extraction processing of peak voltage, peak area and half-peak width in turn to obtain electrochemical signal feature data corresponding to the plurality of electrochemical signals, and the electrochemical signal feature data include peak voltage data, peak area data and half-peak width data; specifically, the plurality of preprocessed electrochemical signals are represented in a linear manner, and the high point, the formed peak area and half-peak width and other data in the linear representation are calculated to obtain the electrochemical signal feature data including peak voltage data, peak area data and half-peak width data, and use them as the electrochemical signal feature data corresponding to the plurality of electrochemical signals.

[0090] Among them, during preprocessing, the electrode electrochemical signals and non-electrode interfering electrochemical signals in several electrochemical signals are first identified by a machine learning algorithm, and the non-electrode interfering electrochemical signals are removed; several electrochemical signals after initial processing are formed, and the machine learning algorithm is an algorithm after training and convergence using the waveform, frequency and amplitude characteristics in the electrode electrochemical signals; the expected calculation formula (arithmetic mean as the expected signal value), standard deviation calculation formula and covariance calculation formula are used to calculate and process the several electrochemical signals after initial processing, so as to obtain the expected signal values, standard deviation values ​​and covariance values ​​corresponding to the several electrochemical signals; and then the expected signal values, standard deviation values ​​and covariance values ​​corresponding to the several electrochemical signals are obtained by using the expected calculation formula (arithmetic mean as the expected signal value), standard deviation calculation formula and covariance calculation formula. The expected signal values ​​and covariance values ​​corresponding to several electrochemical signals call a joint probability density function to calculate the joint probability density of each electrochemical signal, thereby obtaining the joint probability density value corresponding to each electrochemical signal; then, the electrochemical signal is eliminated according to the joint probability density value and standard deviation value corresponding to each electrochemical signal of the several electrochemical signals to obtain several electrochemical signals after elimination; after eliminating a certain electrochemical signal, it is necessary to interpolate the several electrochemical signals after elimination through a linear interpolation algorithm to obtain several electrochemical signals after interpolation, and use the several electrochemical signals after interpolation as several electrochemical signals after preprocessing.

[0091] Diagnostic evaluation module 303: used for the monitoring terminal to index the battery model data of the used aluminum shell battery to the corresponding battery monitoring and evaluation model, and input the electrochemical signal feature data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the used aluminum shell battery;

[0092] During the specific implementation of the present invention, the monitoring terminal indexes the corresponding battery monitoring and evaluation model based on the battery model data of the waste aluminum shell battery, including: the monitoring terminal obtains the battery model data corresponding to the waste aluminum shell battery; uses the battery model data to perform matching processing in the model database, and indexes the battery monitoring and evaluation model consistent with the battery model data according to the matching result; the model database stores battery monitoring and evaluation models corresponding to several aluminum shell batteries with different battery models, and each battery monitoring and evaluation model is a model that converges on a pre-constructed digital twin network trained using electrochemical signal feature data extracted from the electrochemical signals of the corresponding model of aluminum shell batteries under different battery states, and the pre-constructed digital twin network is formed by modifying the digital twin network parameters using aluminum shell battery parameters corresponding to different battery models.

[0093] Furthermore, the electrochemical signal characteristic data corresponding to the several electrochemical signals are input into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery, including: inputting the electrochemical signal characteristic data corresponding to the several electrochemical signals into the battery monitoring and evaluation model in sequence; after receiving the electrochemical signal characteristic data corresponding to the several electrochemical signals, the battery monitoring and evaluation model performs charge and discharge simulation evaluation processing of the waste aluminum shell battery based on the electrochemical signal characteristic data corresponding to the several electrochemical signals, and outputs the charge and discharge simulation evaluation results of the waste aluminum shell battery as the monitoring and evaluation results corresponding to the waste aluminum shell battery.

[0094] Specifically, in order to ensure the accuracy of battery monitoring and evaluation, it is necessary to select the corresponding battery monitoring and evaluation model according to different battery models; therefore, the monitoring terminal needs to obtain the battery model data corresponding to the waste aluminum shell battery; then the battery model data is matched in the model database, and the battery monitoring and evaluation model consistent with the battery model data is indexed according to the matching result; wherein the model database stores battery monitoring and evaluation models corresponding to several different battery models of aluminum shell batteries, and each battery monitoring and evaluation model is a model that converges on the pre-constructed digital twin network using the electrochemical signal feature data extracted from the electrochemical signals of the corresponding model of aluminum shell batteries under different battery states. The pre-constructed digital twin network is formed by modifying the digital twin network parameters using the aluminum shell battery parameters corresponding to different battery models.

[0095] After selecting the corresponding battery monitoring and evaluation model, the electrochemical signal characteristic data corresponding to the multiple electrochemical signals need to be input into the battery monitoring and evaluation model in sequence; then, after receiving the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, the battery monitoring and evaluation model performs a charge and discharge simulation evaluation process of the waste aluminum shell battery through the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, wherein the charge and discharge simulation evaluation includes estimating the battery capacity, internal resistance, power density and other performance parameters of the waste aluminum shell battery; finally, the charge and discharge simulation evaluation result of the waste aluminum shell battery is output as the monitoring and evaluation result corresponding to the waste aluminum shell battery; thereby, the corresponding monitoring and evaluation result of the waste aluminum shell battery can be obtained more accurately, thereby realizing the monitoring and evaluation of the waste aluminum shell battery.

[0096] During the diagnostic evaluation, after obtaining the battery capacity, internal resistance and power density data of the waste aluminum shell battery, the health and life span of the battery will be evaluated based on these parameters, thereby generating the corresponding monitoring and evaluation results of the waste aluminum shell battery; for example, if the internal resistance is greater than 0.5ω; the discharge capacity decay rate exceeds 50%, it can be determined that the waste aluminum shell battery has entered the scrap process and cannot be recycled, otherwise there will be uncontrollable risks; or it can be judged by capacity, that is, using a linear regression model to assume that the battery capacity decays linearly with time; the model form is as follows: C(t) = C(0) + βC(t); where C(t) is the battery capacity at time t, C(0) is the initial capacity, and β is the capacity decay rate (obtained by fitting the parameters extracted multiple times).

[0097] The data storage module 304 is used for the monitoring terminal to generate a monitoring and evaluation report based on the monitoring and evaluation results, and to store the generated monitoring and evaluation report according to preset storage rules.

[0098] During the specific implementation of the present invention, the monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation results, and stores the generated monitoring and evaluation report according to preset storage rules, including: the monitoring terminal generates a monitoring and evaluation report according to a preset report template based on the monitoring and evaluation results to obtain a monitoring and evaluation report corresponding to the waste aluminum shell battery; the monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with the multiple electrochemical signals, and the associated monitoring and evaluation report is stored according to the preset storage rules.

[0099] Specifically, in order to facilitate subsequent management users to view and review the monitoring and evaluation results, the monitoring terminal needs to generate and process the monitoring and evaluation report according to the preset report template based on the monitoring and evaluation results, thereby generating a monitoring and evaluation report corresponding to the waste aluminum shell battery; then the monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with a number of electrochemical signals, and the associated monitoring and evaluation report is stored and processed according to the preset storage rules; this can facilitate the subsequent provision of an intuitive operation interface and rich data reports for management users; management users can view real-time monitoring data, battery status indications and fault warning information through the interface, and generate a detailed battery health status report to facilitate management and decision-making.

[0100] An embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries according to any of the above embodiments. The computer-readable storage medium includes, but is not limited to, any type of disk (including floppy disks, hard disks, optical disks, CD-ROMs, and magneto-optical disks), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card, or optical card. In other words, the storage device includes any medium that can store or transmit information in a readable form by a device (e.g., a computer, a mobile phone), which can be a read-only memory, a disk, or an optical disk.

[0101] An embodiment of the present invention further provides a computer application program that runs on a computer and is used to execute the method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to any one of the above embodiments.

[0102] also, Figure 4 It is a schematic diagram of the structural composition of the monitoring terminal in an embodiment of the present invention.

[0103] The embodiment of the present invention also provides a monitoring terminal, such as Figure 4 The monitoring terminal includes a processor 402, a memory 403, an input unit 404, a display unit 405 and other components. Those skilled in the art will understand that Figure 4 The structural components of the monitoring terminal shown do not constitute a limitation on all devices, and may include more or fewer components than shown, or combine certain components. The memory 403 can be used to store the application 401 and various functional modules, and the processor 402 runs the application 401 stored in the memory 403, thereby executing various functional applications and data processing of the device. The memory can be an internal memory or an external memory, or include both internal and external memories. The internal memory may include a read-only memory (ROM), a programmable ROM (PROM), an electrically programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, or a random access memory. The external memory may include a hard disk, a floppy disk, a ZIP disk, a USB flash drive, a magnetic tape, etc. The memory disclosed in the present invention includes but is not limited to these types of memories. The memory disclosed in the present invention is only used as an example and not as a limitation.

[0104] The input unit 404 is used to receive input signals and keywords entered by the user. The input unit 404 may include a touch panel and other input devices. The touch panel can collect user touch operations on or near it (such as operations performed by the user using a finger, stylus, or any other suitable object or accessory on or near the touch panel) and drive the corresponding connected device according to a pre-set program; other input devices may include, but are not limited to, one or more of a physical keyboard, function keys (such as playback control keys, on / off keys, etc.), a trackball, a mouse, a joystick, etc. The display unit 405 can be used to display information entered by the user or information provided to the user, as well as various menus of the terminal device. The display unit 405 can be in the form of a liquid crystal display, an organic light-emitting diode, etc. The processor 402 is the control center of the terminal device, connecting the various parts of the entire device using various interfaces and lines. It performs various functions and processes data by running or executing software programs and / or modules stored in the memory 403 and calling data stored in the memory.

[0105] As an embodiment, the monitoring terminal includes: one or more processors 402, a memory 403, and one or more applications 401, wherein the one or more applications 401 are stored in the memory 403 and are configured to be executed by the one or more processors 402, and the one or more applications 401 are configured to execute the corresponding real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries in any one of the above embodiments.

[0106] In an embodiment of the present invention, electrochemical signal collection is achieved by providing a micro chemical sensor on the waste aluminum shell battery; the monitoring terminal communicates with the micro chemical sensor to obtain a number of electrochemical signals; the signal characteristics of the multiple electrochemical signals are extracted and processed to obtain electrochemical signal characteristic data; the battery model data of the waste aluminum shell battery is indexed into the corresponding battery monitoring and evaluation model, and the electrochemical signal characteristic data is input into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery; a monitoring and evaluation report is generated based on the monitoring and evaluation results, and the generated monitoring and evaluation report is stored and processed according to preset storage rules; in this way, accurate diagnosis and evaluation of the health status of the battery is achieved, which provides strong support for the recycling and management of the waste aluminum shell battery, and facilitates the direct viewing or review of the monitoring and evaluation report by subsequent management users.

[0107] In addition, the above is a detailed introduction to a method for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries and related devices provided in an embodiment of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries, characterized in that: Applied to waste aluminum shell batteries, a micro chemical sensor is provided on the waste aluminum shell batteries; the method comprises: The monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, wherein each of the plurality of electrochemical signals is marked with a collection time and a sensor ID corresponding to the micro chemical sensor; The monitoring terminal extracts signal features from the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals; The monitoring terminal indexes the battery model data of the waste aluminum shell battery to the corresponding battery monitoring and evaluation model, and inputs the electrochemical signal characteristic data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery; The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule.

2. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 1, characterized in that: The monitoring terminal establishes a communication connection with the micro chemical sensor in the waste aluminum shell battery and receives a plurality of electrochemical signals collected by the micro chemical sensor, including: The monitoring terminal obtains the battery number of the waste aluminum shell battery and generates a connection authentication request for establishing a communication connection with the micro chemical sensor based on the battery number; When the monitoring terminal enters the signal coverage range of the micro chemical sensor, the connection authentication request is sent to the micro chemical sensor via a temporary communication connection within the signal coverage range of the micro chemical sensor; After the micro chemical sensor verifies the received connection authentication request, the monitoring terminal establishes a communication connection with the micro chemical sensor and receives a plurality of electrochemical signals collected and uploaded by the micro chemical sensor, wherein the plurality of electrochemical signals are obtained by the micro chemical sensor when starting to collect at intervals during the charging and discharging of the waste aluminum shell battery.

3. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 1, characterized in that: The monitoring terminal extracts and processes the signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals, including: The monitoring terminal preprocesses the received electrochemical signals to obtain preprocessed electrochemical signals; The pre-processed electrochemical signals are sequentially subjected to feature extraction processing of peak voltage, peak area and half-peak width to obtain electrochemical signal feature data corresponding to the electrochemical signals, the electrochemical signal feature data including peak voltage data, peak area data and half-peak width data.

4. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 3, characterized in that: The monitoring terminal preprocesses the received electrochemical signals to obtain the preprocessed electrochemical signals, including: The monitoring terminal identifies electrode electrochemical signals from the plurality of electrochemical signals based on a machine learning algorithm, and removes non-electrode electrochemical signals from the plurality of electrochemical signals based on the identification results to form a plurality of electrochemical signals after initial processing, wherein the machine learning algorithm is an algorithm that has been trained and converged using waveform and frequency amplitude characteristics in the electrode electrochemical signals; The monitoring terminal performs calculation processing on the multiple electrochemical signals after initial processing to obtain expected signal values, standard deviation values, and covariance values ​​corresponding to the multiple electrochemical signals; performing a joint probability density calculation process on each electrochemical signal using the expected signal values ​​and covariance values ​​corresponding to the plurality of electrochemical signals based on a joint probability density function to obtain a joint probability density value corresponding to each electrochemical signal; performing electrochemical signal elimination processing based on a joint probability density value corresponding to each of the plurality of electrochemical signals and the standard deviation value to obtain the plurality of electrochemical signals after elimination; Interpolation processing is performed on the eliminated electrochemical signals based on a linear interpolation algorithm to obtain interpolated electrochemical signals, and the interpolated electrochemical signals are used as preprocessed electrochemical signals.

5. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 1, characterized in that: The monitoring terminal indexes the corresponding battery monitoring and evaluation model based on the battery model data of the waste aluminum shell battery, including: The monitoring terminal obtains battery model data corresponding to the waste aluminum shell battery; The battery model data is used to perform matching processing in a model database, and a battery monitoring and evaluation model consistent with the battery model data is indexed according to the matching result; the model database stores battery monitoring and evaluation models corresponding to several aluminum shell batteries of different battery models, and each battery monitoring and evaluation model is a model that converges on a pre-constructed digital twin network trained using electrochemical signal feature data extracted from electrochemical signals of aluminum shell batteries of corresponding models under different battery states. The pre-constructed digital twin network is formed by modifying digital twin network parameters using aluminum shell battery parameters corresponding to different battery models.

6. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 1, characterized in that: The step of inputting the electrochemical signal characteristic data corresponding to the plurality of electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery includes: inputting the electrochemical signal characteristic data corresponding to the plurality of electrochemical signals into the battery monitoring and evaluation model in sequence; After receiving the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, the battery monitoring and evaluation model performs a charge and discharge simulation evaluation process on the waste aluminum shell battery based on the electrochemical signal characteristic data corresponding to the multiple electrochemical signals, and outputs the charge and discharge simulation evaluation result of the waste aluminum shell battery as the monitoring and evaluation result corresponding to the waste aluminum shell battery.

7. The method for real-time monitoring and evaluation of chemical properties of waste aluminum shell batteries according to claim 1, characterized in that: The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation result, and stores the generated monitoring and evaluation report according to a preset storage rule, including: The monitoring terminal generates a monitoring and evaluation report based on the monitoring and evaluation results according to a preset report template to obtain a monitoring and evaluation report corresponding to the waste aluminum shell battery; The monitoring and evaluation report corresponding to the waste aluminum shell battery is associated with the plurality of electrochemical signals, and the associated monitoring and evaluation report is stored according to a preset storage rule.

8. A device for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries, characterized in that: Applicable to waste aluminum shell batteries, a micro chemical sensor is provided on the waste aluminum shell batteries; the device comprises: Data receiving module: used for establishing a communication connection between the monitoring terminal and the micro chemical sensor in the waste aluminum shell battery, and receiving a plurality of electrochemical signals collected by the micro chemical sensor, each of the plurality of electrochemical signals being marked with the collection time and the sensor ID corresponding to the micro chemical sensor; Feature extraction module: used for the monitoring terminal to extract signal features of the received electrochemical signals to obtain electrochemical signal feature data corresponding to the electrochemical signals; Diagnostic evaluation module: used for the monitoring terminal to index the battery model data of the waste aluminum shell battery to the corresponding battery monitoring and evaluation model, and input the electrochemical signal characteristic data corresponding to the multiple electrochemical signals into the battery monitoring and evaluation model for diagnostic evaluation processing to obtain the monitoring and evaluation results corresponding to the waste aluminum shell battery; Data storage module: used for the monitoring terminal to generate a monitoring and evaluation report based on the monitoring and evaluation results, and to store the generated monitoring and evaluation report according to preset storage rules.

9. A monitoring terminal comprising a processor and a memory, characterized in that: The processor runs the computer program or code stored in the memory to implement the real-time monitoring and evaluation method for the chemical properties of waste aluminum shell batteries according to any one of claims 1 to 7.

10. A computer-readable storage medium for storing a computer program or code, characterized in that: When the computer program or code is executed by a processor, the method for real-time monitoring and evaluation of the chemical properties of waste aluminum shell batteries according to any one of claims 1 to 7 is implemented.

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