System and method for estimating the remaining value of used batteries in safe and healthy conditions

Abstract

The systems and methods described herein relate to estimating the remaining value of used batteries for reuse purposes by deriving a safe state using a healthy state and derivative calculation of measured impedance. [Solution] In one embodiment, the method includes the step of measuring the impedance of a spent battery using test equipment at a target temperature and a target state of charge (SOC), where the target temperature and target SOC are related to the chemical activity of the spent battery. The method also includes the step of removing interference sources by calculating the first derivative of the real part of the impedance. The method also includes the step of estimating a residual value from a safe state and a healthy state derived in response to changes in the first derivative within a frequency band. The method also includes the step of transmitting the residual value to a device when the residual value satisfies the parameters, and allowing the device to draw power from the spent battery during reuse operation.

Description

Technical Field

[0001] Technical Field The subject matter described in this specification generally relates to estimating the residual value of used batteries, and more particularly, to estimating the residual value using the derivative calculation of the safety state and the soundness state for reuse purposes.

Background Art

[0002] Background A system for driving a vehicle with a traction battery is a clean and sustainable alternative to the use of fossil fuels. An electric vehicle (EV) powered by a battery can reduce fuel costs and maintenance costs in addition to reducing greenhouse gas emissions, thereby improving the economic aspects for consumers. However, disposing of a traction battery can be environmentally harmful due to the metal materials. For example, if a lithium-ion battery is in a landfill, toxic chemicals such as cobalt, nickel, and manganese can leak into the soil and water. Many traction batteries use a liquid electrolyte that may cause a fire in a landfill or recycling facility. Therefore, the environmental advantages of traction batteries in EVs become environmentally reactive harms at the end of the product life (end-of-life: EoL).

[0003] In various implementations, systems can reuse traction batteries for so-called second-life applications once they reach their End-of-Life (EoL). For example, a traction battery can generate enough power to serve as a backup power source for residential applications. However, traction batteries inevitably degrade and become internally degraded during their initial deployment, affecting their health, which can limit their reuse potential. Internal degradation includes metallic plating, which occurs when lithium ions are deposited on the anode as metallic lithium during battery charging. This plating significantly reduces battery performance by decreasing the amount of lithium available for energy storage, increases internal resistance, and can increase safety hazards due to short circuits. Furthermore, a challenge for systems detecting this plating is that it occurs microscopically within the cell, requiring specialized and expensive equipment. Therefore, reusing traction batteries presents problems with the difficulty and cost of detecting physical and chemical degradation, which reduces their applications and increases the risk to reuse opportunities. [Overview of the project] [Problems that the invention aims to solve]

[0004] overview In one embodiment, an exemplary system and method relates to estimating the remaining value of a used battery for reuse purposes by deriving a safe state using a health state and derivative calculation of measured impedance. In various implementations, the system reuses battery packs that have reached the end of their life (EoL) when they originally power electric vehicles (EVs), homes, etc. Used batteries may have their potential uses for a second life limited by degradation caused by recharging or physical damage during transport that poses a safety hazard during reuse (e.g., collisions, road debris). The system recycles battery packs that have reuse potential from among unknown defects that occur internally and are difficult to diagnose. For example, battery packs obtained from EVs that have been rapidly charged and exposed to low temperatures may have metallic plating. The system may also disassemble used batteries using complex machinery to detect plating on contacts related to the battery cells. Disassembly may damage delicate components and controllers near the battery cells. For example, disassembling a battery pack to diagnose plating using scanning electron microscopy (SEM) and nuclear magnetic resonance (NMR) can damage internal sensors, controllers, and cell packaging. This can lead to physical and chemical degradation, creating conditions that make battery reuse risky, and detecting these conditions may require disassembly, adding complexity. [Means for solving the problem]

[0005] Therefore, in one embodiment, the estimation system predicts the remaining capacity of a spent battery for reuse and second-life applications by deriving health and safety states using first-order derivative calculations of impedance. In one method, the estimation system uses first-order derivative calculations to identify features for diagnosing safety and metal plating at the module level rather than the cell level, thereby reducing testing costs and complexity. Here, the functional state representing the remaining capacity can also be derived directly from the health and safety states. The health state indicates the remaining capacity of the spent battery. Furthermore, the estimation system reduces complexity by eliminating linear and constant interference sources within the module using non-invasive instruments and external measurements. This avoids damage to the internal cells and delicate equipment of the spent battery.

[0006] Furthermore, interference sources may exhibit first-order derivative values ​​from impedance measurements that are unchanging and negligible (e.g., zero). Detection accuracy and sensitivity are further improved by estimation systems that measure impedance in frequency bands corresponding to the internal architecture of spent batteries where interference sources are dominant and prominent. Thus, estimation systems reliably detect the remaining value of spent batteries using module-level derivative calculations with non-invasive techniques, and identify reuse applications for spent batteries that reduce environmental waste.

[0007] In one embodiment, an estimation system is disclosed for predicting and estimating the remaining value of a spent battery for reuse purposes by deriving a safe state using a health state and a derivative calculation of the measured impedance. The estimation system includes a memory containing instructions, which, when executed by a processor, cause the processor to measure the impedance of the spent battery at a target temperature and a target SOC using test equipment, where the target temperature and target SOC are associated with the chemical activity of the spent battery. The instructions also include instructions to remove interference sources by calculating the first derivative of the real part of the impedance. The instructions also include instructions to estimate the remaining value from the safe and health states derived in response to changes in the first derivative within a frequency band. The instructions also include instructions to transmit the remaining value to a device, which then draws power from the spent battery during reuse operation.

[0008] In one embodiment, a non-temporary computer-readable medium is disclosed for estimating the remaining value of a spent battery for reuse purposes by deriving a safe state using a health state and a derivative calculation of the measured impedance. The non-temporary computer-readable medium, when executed by a processor, includes instructions that cause the processor to perform one or more functions. The instructions include instructions that cause a test instrument to measure the impedance of the spent battery at a target temperature and a target SOC, the target temperature and target SOC being related to the chemical activity of the spent battery. The instructions also include instructions that cause interference sources to be removed by calculating the first derivative of the real part of the impedance. The instructions also include instructions that cause the remaining value to be estimated from the safe and health states derived in response to the change in the first derivative within a frequency band. The instructions also include instructions that cause the remaining value to be sent to a device and that cause the device to draw power from the spent battery during reuse operation. The instructions that cause the remaining value to be sent to a device and that cause the device to draw power from the spent battery during reuse operation may be executed when the remaining value satisfies parameters.

[0009] In one embodiment, a method is disclosed for estimating the remaining value of a spent battery for reuse purposes by deriving a safe state using a health state and a derivative calculation of the measured impedance. In one embodiment, the method includes the step of measuring the impedance of the spent battery at a target temperature and a target SOC using test equipment, the target temperature and target SOC being related to the chemical activity of the spent battery. The method also includes the step of removing interference sources by calculating the first derivative of the real part of the impedance. The method also includes the step of estimating the remaining value from the safe state and health state derived in response to the change in the first derivative within a frequency band. The method also includes the step of transmitting the remaining value to a device when the parameters are met, and having the device draw power from the spent battery during reuse operation.

[0010] Brief explanation of the drawing The accompanying drawings incorporated herein and constituting part thereof illustrate various systems, methods, and other embodiments of the present disclosure. Element boundaries illustrated in the drawings (e.g., boxes, groups of boxes, or other shapes) will be understood to represent one embodiment of the boundary. In some embodiments, one element may be designed as multiple elements, or multiple elements may be designed as one element. In some embodiments, an element shown as an internal component of another element may be realized as an external component, and vice versa. Furthermore, elements may not be drawn to scale. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows one embodiment of an estimation system related to estimating the remaining value of a used battery for reuse purposes by deriving a safe state using the health state and derivative calculation of the measured impedance. [Figure 2A]This figure shows an example of detecting plating, measuring the health status, and predicting the remaining value of a used battery. [Figure 2B] This figure shows an example of detecting plating, measuring the health status, and predicting the remaining value of a used battery. [Figure 2C] This figure shows an example of detecting plating, measuring the health status, and predicting the remaining value of a used battery. [Figure 3A] This figure shows examples of interference sources that the estimation system can mitigate and eliminate using first derivative calculations. [Figure 3B] This figure shows examples of interference sources that the estimation system can mitigate and eliminate using first derivative calculations. [Figure 4] This figure shows one embodiment of a method related to estimating the remaining value from the safety state derived in response to the health state and the change in the first derivative. [Modes for carrying out the invention]

[0012] Detailed explanation Systems, methods, and other embodiments relating to estimating the remaining value of spent batteries for reuse purposes by deriving a safe state using the healthy state and derivative calculation of measured impedance are disclosed herein. In various implementations, systems for testing healthy and safe conditions (e.g., metal plating) for battery reuse require measurements obtained from complex instruments. Metal plating is an internal condition in which a surface layer is formed on the anode due to improper intercalation of ions into the anode material, thereby compromising safety. In the case of lithium batteries powering electric vehicles (EVs), the surface layer is lithium ions accumulating on the anode surface, which interferes with current output and reduces overall power generation. High-frequency electrochemical impedance spectroscopy (HF-EIS) instruments measure cell-level plating in relation to systems for estimating battery interference (e.g., contact interference, metal plating, etc.) from metallic materials (e.g., lithium ions). These instruments are expensive, and measurements for detecting plating face challenges. This is because batteries have tightly integrated hardware and battery cells, and unlike short circuits in the internal circuitry, direct access is restricted. Disassembling them to directly access the cells could involve damaging used batteries, thus preventing their reuse.

[0013] Alternatively, systems using non-destructive techniques such as ultrasonic testing to test integrity and safety conditions require sophisticated equipment that can hinder test compliance. Furthermore, alternative systems that perform measurements at the module level face challenges related to interference from structural changes in the battery pack (e.g., case deformation, accidental damage, physical holes, etc.). Therefore, systems that test used batteries for integrity and safety conditions to estimate remaining life present challenges related to sophisticated equipment and detection techniques involving invasive disassembly, which hinders their reuse.

[0014] Therefore, in one embodiment, the estimation system estimates the remaining value of a used battery by deriving the safety state using the calculation of the first derivative of the real part from the health state and impedance. The remaining value may indicate the opportunity for a second life and reuse of the used battery (e.g., an electric vehicle (EV) battery). For example, the remaining value is a functional state that is directly related to the safety state and health state. Furthermore, the estimation system can measure the health state (e.g., charge capacity) and use the first derivative calculation to identify features for diagnosing the safety state and metal plating at the module level rather than the cell level. A module may be located within the battery pack of an EV and may include multiple cells, cell arrays, etc., that exhibit a potentially degraded state due to power supply to a device (e.g., an EV). In this way, the estimation system can accurately derive the remaining value of cells in a used battery from the first derivative of the real part while avoiding invasive and complex testing.

[0015] In various implementations, the estimation system selects a test frequency band such that it includes the cell layout and chemical characteristics of the spent battery as factors. For example, the frequency band exceeds the frequency associated with increased chemical decomposition and increased ion (e.g., lithium-ion) response, which improves the test robustness for the spent battery. Furthermore, the estimation system identifies and includes temperature and state of charge (SOC) as factors to measure impedances such that the first derivative calculation of impedance emphasizes and enhances the plating effect. Alternatively, the estimation system uses first derivative calculations to calculate the safe state for cells, cell arrays, etc., to remove specific interference sources (e.g., contact interference, inductive interference, etc.) that are unchanging and negligible (e.g., zero) from the module level. This allows for non-invasive and accurate external identification of terminal plating, degradation, etc., within the spent battery, avoiding decomposition using changes in the first derivative value of impedance, thereby improving the test.

[0016] Furthermore, estimating residual value from a safe state may require extracting operational quality related to specific safety-related characteristics of the used battery. These safety-related characteristics may include SOC, temperature, induction, etc. Therefore, the estimation system can reliably and accurately estimate the residual value and safety of used batteries for reuse purposes from first-derivative calculations, while employing non-invasive methods that reduce the complexity of testing and component damage.

[0017] In certain implementations, the systems shown in Figures 1-4 also include various elements. In various embodiments, it will be understood that the system may have fewer elements than those shown in Figures 1-4. The system may have any combination of the various elements shown in Figures 1-4. Furthermore, the system may have additional elements in addition to those shown in Figures 1-4. In some configurations, the system may be implemented without one or more of the elements shown in Figures 1-4. Although the various elements are shown as being located within the system in Figures 1-4, it will be understood that one or more of these elements may be located outside the system. Furthermore, the illustrated elements may be physically separated by a wide distance. In addition, it will be noted that, for the sake of brevity and clarity of the examples, reference numbers are repeated in separate figures where necessary to indicate corresponding or similar elements. Furthermore, the description outlines numerous specific details to enable a full understanding of the embodiments described herein. However, those skilled in the art will understand that the embodiments described herein can be implemented using various combinations of these elements.

[0018] Referring to Figure 1, one embodiment of an estimation system 100 is shown, relating to estimating the remaining value of a spent battery for reuse purposes by deriving a safe state using the sound state and derivative calculation of the measured impedance. In one method, a system for monitoring and identifying internal growth of Li metal deposition is essential to derive and identify the state of safety (SOS) of a lithium-ion battery. Internal growth is a factor related to increasing safe reuse applications by lowering the thermal runaway temperature of the lithium-ion battery. The estimation system 100 and measurement module 130 can measure the impedance of the spent battery at target temperature and target SOC using test equipment along these lines. For example, the target temperature and target SOC are associated with levels indicating the robust chemical activity of the spent battery. Furthermore, the estimation system 100 removes interference sources by calculating the first derivative of the real part from the impedance. This allows the estimation system to output the safe state indicating metal plating and the remaining value of the spent battery (e.g., residual functionality, power reliability, etc.) at the module level, while avoiding impedance tracking. In this example, impedance tracking may require a system to measure impedance in order to obtain internal sensor data that is not available from third-party manufacturers. Impedance tracking may also require access to manufacturing details and manufacturing schematics that are restricted due to proprietary rights.

[0019] Furthermore, the estimation system 100 estimates a residual value from a safety state and a sound state derived according to a change in a first derivative within a frequency band for a used battery. For example, the frequency band exceeds a frequency accompanied by an increase in chemical decomposition and a robust ion (e.g., lithium ion) response increased to test the used battery. When the residual value satisfies the parameters, another system can reuse the used battery to power a device. For example, when the residual value satisfies the parameters, the estimation system 100 transmits the residual value to the device, and during reuse operation, the device draws power from the used battery.

[0020] In FIG. 1, the estimation system 100 is shown as including a processor 110 and a memory 120. In one embodiment, the memory 120 stores a measurement module 130 that acquires data regarding a used battery from test equipment, test sensors, and the like. For example, the measurement module 130 generally includes instructions that function to control the processor 110 to receive data input from one or more sensors of the test equipment. For example, the test equipment measures impedance and measures a response using hardware that applies a minimum alternating current (AC) signal to a module, a cell, and the like. Such test equipment can accurately output detailed information regarding the internal resistance and reactance of a battery such as a high-voltage battery used by an EV.

[0021] In one implementation example, the memory 120 is a random-access memory (RAM), a read-only memory (ROM), a hard disk drive, a flash memory, or other suitable memory for storing the measurement module 130. The measurement module 130 is, for example, computer-readable instructions that cause the processor 110 to execute various functions disclosed herein when executed by the processor 110. Further, in one embodiment, the estimation system 100 includes a data store 140 that operates as a database. The database is, in one embodiment, an electronic data structure stored in the memory 120 or another data store, and is composed of routines executable by the processor 110 for performing analysis of the stored data, providing the stored data, organizing the stored data, etc. Thus, in one embodiment, the data store 140 stores data used by the measurement module 130 when performing various functions.

[0022] In another example, the data store 140 includes battery characteristics 150 and impedance 160. The battery characteristics 150 may include data related to one of the state of charge (SOC), temperature, state of health, state of degradation (state of health: SOH), remaining capacity, charge capacity, and safety state of the used battery. The test equipment can measure the state of health using the acquired sensor data related to the used battery stored as the battery characteristics 150. For example, the sensor data includes output voltage, operating temperature, and impedance at low temperature.

[0023] As further described below, the estimation system 100 includes test equipment that measures the impedance at the module level for a used battery and performs calculations involving the first derivative of that impedance. This makes it possible to eliminate interference sources with first derivative characteristics for impedance that are unchanging and negligible (e.g., zero). This also makes it possible to estimate the remaining value from the health and safety status of one or more cells within a module of a used battery without invasive disassembly or the use of expensive diagnostic equipment, thereby reducing the complexity of the system.

[0024] In another embodiment, the battery characteristics 150 may include a safety state indicating plating within cells, cell arrays (e.g., 12 cells), modules, etc., inside the spent battery, and a frequency band in which the plating is prominent. The safety state may include extracting the operational quality with respect to specific safety-related characteristics of the spent battery (e.g., SOC, temperature, induction, etc.). The plating may include forming a metallic layer on the anode surface of the cell due to improper intercalation of lithium ions into the anode material and accumulation of lithium ions on the anode surface. Here, the frequency band may be above a frequency associated with increased chemical decomposition and an increased ion response corresponding to the spent battery. The battery characteristics 150 may also include safety state-related parameters indicating that one of the cells and modules within the spent battery has undetected plating on the anode surface related to a threshold (e.g., current output, voltage output, etc.).

[0025] Battery characteristic 150 may include a State of Charge (SOC), which is one of the charge and discharge levels associated with chemical degradation. Furthermore, battery characteristic 150 may include a functional state for a used battery using safety and health states. For example, the functional state may be the remaining value of a used battery as a power source in a reuse application. As will be further explained below, the remaining value or functional state can be directly correlated to the safety and health states of a used battery. In one method, the estimation system 100 outputs the remaining value by multiplying the safety value by the health value. In this way, the system can use these outputs to identify lithium deposition from the remaining value. If lithium deposition is present, the used battery is no longer safe for use in second-life applications and potential reuse opportunities.

[0026] Impedance 160 can include a measure inverse to that of electric current, expressed using complex-valued generalizations and ohms (Ω) units. Therefore, impedance is similar to resistance in a direct current (DC) system. In AC systems, impedance incorporates reactance, resulting from frequency-dependent contributions from capacitance and inductance. Thus, impedance in an AC system is further measured in Ω units by the equation Z = V / I, where V and I are frequency-dependent.

[0027] Referring further to Figure 1, the estimation system 100 and measurement module 130 include instructions to the processor 110 to detect physical and chemical changes related to the internal state of the battery (e.g., lithium-ion battery) from impedance measurements. In one method, the frequency band for impedance measurement exceeds the frequencies where the ion response inside the battery is dominant (e.g., 100 Hz, 1 kHz, 1 MHz, etc.). This allows the estimation system 100 to accurately diagnose the cause of impedance changes from the first derivative and impedance values ​​for frequencies such as variable frequencies f1 to f2. The diagnosis may include one of the following: safety status, presence of lithium metal deposition, lithium plating in at least one cell of the battery, and residual value. For example, residual value is one of the functional status and state of function (SOF) associated with the used battery, and indicates the degree to which the used battery is usable as a power source in reuse applications. For example, reuse applications are one of industrial reuse, residential reuse, and commercial reuse for used batteries. A residual value exceeding minimum parameters, thresholds, etc., may indicate that one or more cells in the used battery have poorly plated or no metal plating at all, thereby increasing the opportunity for reuse rather than recycling and generating waste. Otherwise, the residual value may indicate that the used battery is unsuitable and unsafe for reuse and that it must be recycled.

[0028] Furthermore, varying degrees of residual value can indicate potential uses for reuse. For example, average residual value indicates that a used battery is reliably usable as a backup power source for residential use. In this application, the requirements regarding the safety and quality of service (QoS) may have been reduced. In critical applications, a high residual value may be required for used batteries. This could include used batteries in hospital main power supplies, powering medical equipment, or powering chemical plants. Alternatively, SOF can be expressed by weighting SOS by SOH to form equation (1). SOF = α × SOH × SOS Equation (1) Here, variable α may be a weighting coefficient that depends on one of the following: the battery's chemical properties, cell structure, casing material, application environment, or usage environment (e.g., commercial backup power supply, electric vehicle). Therefore, variable α can be included as an additional factor in relation to SOF for a used battery, in addition to SOH, thereby improving the decision to reuse. For example, estimation system 100 uses safety status, weighting coefficient, and SOH to calculate the functional status, SOF, etc., for a used battery. Functional status may indicate the remaining value of the used battery as a power source in reuse applications.

[0029] In equation (1), SOH can represent either the remaining capacity or the charge capacity of the used battery. SOH can also be reuse-dependent using a class. For example, a class for vehicle reuse requires a high SOH (e.g., 90%) for charge capacity, while a lower SOH (e.g., 80%) may be acceptable for residential reuse. In one method, the estimation system 100 derives SOH from the average temperature using the output voltage, average operating temperature, and impedance. Thus, the estimation system 100 can reliably output either a safe state indicating degradation such as metal plating, or a remaining value for the used battery. This allows the system to identify whether the used battery is suitable for reuse applications and specific target applications. Otherwise, the system generates a recycling plan from the output because the used battery is defective and too worn to be repaired.

[0030] Further methods include estimation systems 100 that target optimal temperature, SOC, and impedance to calculate residual values ​​and detect a safe state. For example, estimation system 100 that measures impedance at target temperature and SOC parameters improves the effectiveness of detecting plating, calculating a safe state, and deriving residual values ​​using first derivative calculations. These parameter targets may depend on the internal architecture, cell layout (e.g., stacked layers, parallel cells, rolled cells, etc.), and chemical profile of the spent battery. Estimation system 100 can adapt these parameter targets during impedance measurements for spent batteries to further improve calculation accuracy.

[0031] Furthermore, in another method, the estimation system 100 selects a frequency band depending on the cell layout and internal architecture of the spent battery (e.g., cylindrical cells, laminated sheets, etc.). As described above, the frequency band can be associated with test equipment that measures impedance from the spent battery when the ion response within the cell is dominant. In addition, the estimation system 100 and the measurement module 130 can use the frequency band to filter out wear interference and measurement noise (e.g., sensor interference) from the spent battery. In this way, the estimation system 100 can accurately diagnose the cause of impedance changes from measured values ​​and real parts of the first derivative for a given cell, while reducing the complexity of testing and calculation at the module level.

[0032] Referring to Figures 2A to 2C, examples of plating detection, health status measurement, and prediction of remaining value for used batteries are shown. The estimation system 100 can calculate one or more of the following first derivatives using impedance measurements from a used battery. Specifically, these first derivatives include the first derivative of the real part from the impedance value, the first derivative of the imaginary part from the impedance value, the difference between the real parts of the first derivative of the impedance value between two frequency points, the difference between the imaginary parts of the first derivative of the impedance value between two frequency points, the real part of the impedance value, and the imaginary part of the impedance value. For example, the two frequency points are variable frequencies f1 to f2 within a frequency band, representing the increase in chemical decomposition and ionic response associated with the used battery. This allows the estimation system 100 to reliably and non-invasively detect internal degradation and plating at the module level using first derivative calculations. In the embodiment, there are two frequency points, but any number of frequency points may be used for the impedance calculations described herein. Furthermore, derivative calculations can be performed by filtering impedance measurements for noise by intelligently selecting the frequency band considering the battery architecture and profile. The first derivative is also a practical and low-cost method for filtering high-frequency interference from sources described below. Unlike the second derivative, the first derivative is noise-resistant to certain types of interference.

[0033] Alternatively, the estimation system 100 improves its effectiveness in detecting degradation by measuring impedance at target temperature and SOC, and in calculating residual values ​​using first derivative calculations. These targets may depend on the internal architecture and chemical properties of the spent battery. Furthermore, the characteristics exhibited by the first derivative of the real part from impedance allow the estimation system 100 to target metal deposition and degradation (e.g., chemical degradation, physical degradation, etc.) by reducing interference sources. Correspondingly, the estimation system 100 can accurately calculate the SOF for the spent battery during testing from interference sources associated with one of the cells, modules, cell arrays, etc., within the spent battery.

[0034] Another example involves the estimation system 100 detecting internal degradation in one of the battery cells and modules and calculating the remaining value externally. This technique avoids invasive and complex testing that requires disassembly. Here, the first derivative is used to neutralize, eliminate, remove, or mitigate contact interference for the used battery during impedance measurements in a selected frequency band. Contact interference (e.g., iron contact, copper contact) can originate from internal cells within the battery module that experience loosening, tightening, etc., of the coupling between terminals, contact tabs, etc. In some cases, interference from terminal contacts is irrelevant to the frequency response.

[0035] The difference between the real parts of the first derivative of the impedance values ​​between two frequency points allows for the neutralization, mitigation, elimination, or removal of inductive interference (e.g., iron-based induction). Inductive interference from iron, and contact interference associated with one of the cells, modules, or cell arrays within the spent battery, may also represent other sources of interference. The estimation system 100, which converts the real parts of the impedance to percentage values, can further minimize inductive interference (e.g., eddy currents) when detecting degradation and calculating the remaining value. This also allows for highlighting changes resulting from metal plating by observing linear relationships and reducing calculations through monotonically increasing relationships rather than higher-level tasks. Furthermore, in one embodiment, the estimation system 100 includes an analytical algorithm that extracts contextual parameters related to the spent battery. For example, the estimation system 100 includes the difference between the real parts of the first derivative of the impedance values ​​between two frequency points and contextual parameters as factors when selecting a threshold for safety status. The first derivative can be compared to the threshold to measure the resolution level. Here, the system analyzing the remaining value can diagnose other defects in addition to internal degradation, plating, etc. In one method, the threshold is associated with the plating level in relation to specific battery chemical properties (e.g., lithium-ion), usage profile (e.g., harsh weather, rough terrain, aggressive driving, etc.). In this way, the estimation system 100 improves the reliability and accuracy of the safety status and remaining value output by intelligently selecting the threshold.

[0036] Alternatively, the estimation system 100 estimates one of the safety status, SOF, and physical degradation of a spent battery by calculating eddy interference. Here, the estimation system 100 can utilize a linear relationship derived from the first derivative of the real part related to the impedance measurement. This allows the estimation system 100 to diagnose physical degradation as one of material wear, solid electrolyte interphase (SEI) growth, or eddy currents due to induced interference, while avoiding complexity of the test task and test equipment. This may involve the estimation system 100 calculating eddy interference for an interference source using a linear relationship derived from the first derivative of the real part related to the measured impedance. The estimation system 100 can identify the plating of terminals in a spent battery by comparing the difference between multiple values ​​(e.g., two) of the first derivative within a frequency band to a threshold, identify the plating using test equipment without disassembling the cells associated with the spent battery, and calculate the safety status using the degree of plating.

[0037] In the specific examples described herein, the estimation system 100 identifies the plating of terminals in a used battery from the difference between two values ​​of the first derivative within a frequency band, using test equipment, without disassembling the cells associated with the used battery. Furthermore, the estimation system 100 can calculate the safety status of a used battery without impedance tracking from the time of manufacture, provided that cycling parameters are met. For example, cycling parameters represent the number of cycles the used battery will experience and extreme operating temperatures. In this way, the estimation system 100 can output a remaining value and safety status for the used battery, indicating its usability as a power source in reuse applications.

[0038] Referring to Figure 2A, the estimation system 100 calculates the change in the first derivative of the real part between various interference sources 2101-2103 over various frequencies related to the impedance measurement. Here, the test equipment can acquire impedance measurements from the used battery pack at the module level externally and non-invasively for calculations by the estimation system 100. This technique avoids damage that would occur in connection with disassembly when accessing the battery cells to measure the interference sources 2101-2103.

[0039] Interference source 2101 may represent plating associated with one of the cells, modules, etc., within the used battery. Interference source 2102 may represent contact interference, contact interference plating, etc., associated with one of the battery modules, cells, etc. For example, contact interference arises from an internal cell within a battery module that is subjected to loosening, tightening, etc., for coupling between terminals. Interference source 2103 may represent a metallic material outside the used battery that affects one of the battery modules, cells, etc., within the used battery. In these examples, the impedance change of the first derivative with respect to the real part between two or more frequency points may indicate the interference source and the degree of its association. Furthermore, the estimation system 100 for the Y axis at 220 can perform a conversion to a percentage value. This conversion further minimizes contact interference and emphasizes impedance changes from metallic plating (e.g., Li plating) to improve plating detection by the estimation system 100.

[0040] Figure 2B shows Chart 230 comparing the relationship between SOH (e.g., residual charge) and the change in the real part from impedance measurements associated with a spent battery. Here, the above change can be between impedances at a frequency point of 20 MHz, expressed as milliohms (mΩ). In this example, the measurement module 130 measures SOH at 60 degrees Celsius and a C rate of 0.5 C. The C rate represents the capacity of 1 ampere-hour (Ah) and the fact that a fully charged battery at temperature x should output 1 A per hour. By reducing chemical reactions, the output current is limited and the effective C rate decreases while a spent battery is operating at low temperatures. However, both very high and very low temperatures can damage the spent battery and accelerate internal degradation, which can raise safety concerns.

[0041] In Chart 230, the estimation system 100 identifies limited plating and degradation at 60 degrees Celsius, a C rate of 0.5 C, and a high SOH using first-order derivative calculations for impedance. In another example, the estimation system 100 detects internal degradation and plating within the module at 20 degrees Celsius and a C rate of 4 C, when SOH is limited, using first-order derivative calculations for the real part of impedance measurements. Thus, Chart 230 shows that the real part of impedance can be boosted at lower temperatures than at higher temperatures among various C rates indicating potential degradation, plating, etc.

[0042] Furthermore, Chart 240 shows that the measurement module 130 detects that SOH decreases when the difference between the real parts of the impedances increases due to a 20MHz frequency band, increment, etc. This frequency analysis differs from the frequency range used by the estimation system 100 for internal degradation (e.g., plating). On the other hand, the measurement module 130 detects an increase in SOH when the real part of the impedance increases at a specific value of 20MHz. In one method, SOH estimation using 20MHz impedance is unrelated to SOS and plating detection. However, SOH estimation can improve the derivation of SOF by using the same impedance analyzer to perform SOS estimation using derivative calculations and SOH estimation due to 20MHz changes. Therefore, the estimation system 100 can include these effects as factors when detecting degradation and calculating the remaining value for used batteries.

[0043] In various implementation examples, Figure 2C shows the raw value of the first derivative for the real part obtained from impedance measurements using test equipment. Here, the estimation system 100 and measurement module 130 derive raw values ​​from various batteries and compare the first derivative value for the real part with a threshold 250. As previously mentioned, the estimation system 100 can extract contextual parameters for used batteries, and the difference between these contextual parameters and the real part of the first derivative of the impedance value can be included as factors when selecting the threshold. Here, the threshold 250 may indicate the degree to which the safe condition and remaining value allow for reuse of the used battery. For this reason, the threshold 250 may be a plating level associated with one of the following: battery chemical properties (e.g., lithium-ion), usage profile (e.g., harsh weather, rough driving, etc.).

[0044] For example, the untreated value over time for battery 260 remains below the threshold 250, indicating that battery 260 has a high residual value and is free of plating. Therefore, the system has the opportunity to reuse used batteries in a wide variety of applications. Since the first derivative value for the real part of the impedance is near the threshold 250, battery 270 may be reusable outside of mission-critical applications (e.g., residential). This also indicates a limited residual value and any undetected internal potential plating. Furthermore, since the untreated value of the first derivative is above the threshold 250, the output of the estimation system 100 may indicate recycling of battery 280. Here, battery 280 may have one or more cells with metallic plating and other degradation (e.g., chemical degradation, physical degradation, etc.) to such an extent that its reuse would be impractical and dangerous. The estimation system 100 can also predict that battery 280 has minimal residual value for reuse applications.

[0045] Figures 3A and 3B illustrate an example of estimation system 100 that reduces and removes interference sources from measured impedance using first-order derivative calculations. As previously mentioned, estimation system 100 can aim to predict one of metal deposition and safety status by reducing interference sources for a spent battery during testing using the first-order derivative of the real part of the measured impedance. Safety status may require extracting operational quality with respect to specific safety-related features (e.g., SOC, temperature, induction, etc.) associated with the spent battery. Interference sources can be associated with one of the cells, modules, cell arrays, etc., within the spent battery. Here, estimation system 100 can avoid invasive and complex testing by detecting interference sources for internal cells from the outside at the module level using first-order derivative calculations. Furthermore, estimation system 100, which measures impedance at target temperatures and SOCs exhibiting high chemical reactivity, can improve the effectiveness of detecting degradation (e.g., chemical degradation, physical degradation, etc.) and residual values ​​using first-order derivative calculations. For example, the target SOC is 20% for low-priority residential reuse applications, but 85% for extremely important applications. The SOC target may depend on the internal architecture and chemical properties of the spent battery. As mentioned above, the estimation system 100 can include SOC as a factor when testing spent batteries and can adapt the target for reuse applications, thereby further improving calculation accuracy.

[0046] By calculating the first derivative, contact interference from the used battery can be neutralized, mitigated, eliminated, or removed during impedance measurement across a selected frequency band. This contact interference may originate from internal cells within the battery module, which are subject to loosening, tightening, etc., for coupling between terminals easily measurable within the frequency band. In Figure 3A, for example, the estimation system 100 mitigates contact interference when measuring impedance from a used battery. Here, the battery has a negative terminal 310 and a positive terminal 320 as contact tabs between internal cells, modules, etc. As mentioned above, contact interference may originate from internal cells within the battery module, which are subject to loosening, tightening, etc., for coupling 330 between terminals, contact tabs, etc. The estimation system 100 may suffer a decrease in accuracy regarding impedance measurements due to contact interference. Therefore, the first derivative, which removes contact interference from the used battery during impedance measurement, improves the accuracy and reliability of detecting battery degradation and estimating remaining value and safety status.

[0047] In Figure 3A, the estimation system 100 can convert the real part of the impedance to a percentage value to minimize induced interference from eddy currents. This conversion can also magnify variations due to metal plating by observing a linear relationship. Another advantage of this technique is that it reduces computational complexity and avoids higher-order calculations by monotonically increasing relationships. Furthermore, the estimation system 100 and measurement module 130 can necessarily filter out wear interference and measurement noise (e.g., sensor interference) from the spent battery by targeting specific frequency bands during measurement. Including specific structures of the spent battery as factors helps in targeting these frequency bands. For example, impedance measurements by the estimation system 100 are affected below a certain frequency by spent batteries having one of the following: cylindrically wound cells, stacked plates, etc. Therefore, the estimation system 100 measuring above a certain frequency can eliminate wear and aging interference by including the battery structure as a factor.

[0048] In another example, the estimation system 100 associates battery chemistry with measurement frequency. Certain battery chemistry has operating tolerances that affect interference sources. For example, in the case of lithium-ion batteries, the operating tolerance is 100 kHz. Therefore, contact and inductive interference from iron sources may be most prominent and amplified above 100 kHz. In this way, the estimation system 100 can filter out irrelevant interference sources, target specific interference sources with impedance measurements above a certain frequency, and calculate the first derivative from the measurement curve over various frequency points.

[0049] Figure 3B shows that the change in the real part of the first derivative of the impedance value between multiple (e.g., two) frequency points can neutralize, mitigate, eliminate, or remove inductive interference (e.g., iron-based induction). Here, an external object 350, such as a metal or magnetic object, causes inductive interference with internal cells, modules, cell arrays, etc., during impedance measurement. For example, internal cells may include materials such as aluminum or stainless steel that inductively couple with the external object 350 near the spent battery. This coupling can also occur with polymers, plastics, etc., used as housings and shields for battery modules. Therefore, the estimation system 100 that eliminates inductive interference can improve calculations of residual values ​​and safety conditions, including wear-related defects.

[0050] As an additional feature, the estimation system 100 detects mechanical deformation and displacement by the module of a used battery from inductive interference between an external object 350 and a contact tab. This may include detecting cell displacement within the module of the used battery. Mechanical deformation can be caused by vehicle-involved collisions, accidents, external forces, impacts, module displacement, geometric cell changes, etc. Similar to plating and other degradation, the estimation system 100 identifies and detects mechanical deformation and cell displacement while avoiding invasive techniques that could damage the battery hardware. In one example, the estimation system 100 detects mechanical deformation and cell displacement at the module level of a used battery from inductive interference between an external object 350 (e.g., a metal object) and a contact tab within the module, while avoiding disassembling the used battery to access the battery cells.

[0051] Charts 3401 and 3402 show the relationship between the real part of the impedance measurement and deposition on the cell contacts (e.g., metal plating). Here, curves 3201 and 3202 represent the actual impedance for the positive terminal 320. Curves 3101 and 3102 represent the actual impedance for the negative terminal 310. As shown in charts 3401 and 3402, factors that can change the impedance appear as degradation (e.g., plating) and interference with the SOH estimation. Therefore, by calculating the derivative, impedance changes caused by contact interference, inductive interference (e.g., induction from iron bases), etc., can be removed to accurately estimate the safety state, SOS, etc. Furthermore, since the impedance change caused by SOS may be relatively small or less than that caused by a specific interference source, the estimation system 100 can estimate SOS by removing and mitigating specific interferences.

[0052] In another example, deposition due to contact interference has a first derivative value that is more pronounced at higher frequencies in Chart 3401 than in Chart 3402. Furthermore, induced interference from an external object containing iron and exhibiting magnetic properties has a constant first derivative. In either case, the estimation system 100 can reliably detect deposition, safety status, and remaining values ​​at frequencies that amplify and emphasize degradation and plating related to used batteries, frequencies above a certain frequency, etc., thereby improving accuracy.

[0053] The estimation system 100 includes additional extensions for predicting residual values ​​and safety status from impedance measurements and health status. For example, the estimation system 100 measures the health status using test equipment with sensor data acquired for the used battery, where the sensor data may include output voltage, operating temperature, and impedance at low temperatures. Furthermore, a safety status that satisfies parameters (e.g., ion deposition, contact thickness, etc.) may include labeling the safety status characteristics as one of eddy currents from inductive interference and material wear, with material wear including SEI growth on battery cells associated with the used battery. Thus, the estimation system 100 can accurately and non-invasively estimate the safety status and residual values ​​of cells in a used battery from the real values ​​of the first derivative and identify reuse applications for the used battery.

[0054] Referring to Figure 4, a flowchart of Method 400 is shown, which relates to estimating residual values ​​from safety and health states derived in response to changes in the first derivative. Method 400 will be explained from the perspective of the estimation system 100 in Figure 1. Although Method 400 is explained in combination with the estimation system 100, please understand that Method 400 is not limited to being implemented within the estimation system 100, but is merely an example of a system in which Method 400 can be implemented.

[0055] In 410, the measurement module 130 measures the impedance of the spent battery at target temperature and SOC. As previously mentioned, in one embodiment, the estimation system 100 measures impedance at target temperature and SOC to improve the effectiveness of detecting plating, calculating the safe state, and deriving the remaining value using first derivative calculations. In one method, these targets depend on the internal architecture, cell layout (e.g., stacked layers, parallel cells, rolled cells, etc.), and chemical profile of the spent battery. In another example, the estimation system 100 adapts the impedance measurements of the spent battery to the changes in the above targets to further improve calculation accuracy.

[0056] Furthermore, the above targets may depend on the internal architecture and chemical properties of the spent battery. The first real derivative of the impedance between the above targets exhibits a characteristic that enables the estimation system 100 to accurately detect metal deposition and degradation (e.g., chemical degradation, physical degradation, etc.) and reduce interference sources. Correspondingly, the estimation system 100 can use the targets to accurately calculate the remaining value of the spent battery during testing from interference sources associated with one of the cells, modules, cell arrays, etc., within the spent battery.

[0057] In 420, the estimation system 100 eliminates interference sources by calculating the first derivative of the real part of the impedance. The difference between the real parts of the first derivative of the impedance values ​​at multiple frequency points allows for the neutralization, mitigation, elimination, or removal of inductive interference (e.g., iron-based induction). Inductive interference from magnetic metals (e.g., iron) and contact interference associated with one of the cells, modules, or cell arrays in a used battery may represent other interference sources.

[0058] Furthermore, the estimation system 100, which converts the real part of the impedance to a percentage value, can further minimize induced interference such as eddy currents when detecting degradation and calculating the remaining value. This also makes it possible to emphasize changes caused by metal plating by observing linear relationships. In this way, the estimation system 100 reduces calculations from monotonically increasing relationships rather than higher-level tasks.

[0059] As described above, in one embodiment, the estimation system 100 includes an analysis algorithm for extracting contextual parameters related to the used battery. For example, when selecting a threshold for the safe state, the estimation system 100 includes the difference between the real parts of the first derivative of the impedance value between two frequency points and the contextual parameters as factors. The first derivative of the real part from the impedance can be compared to the threshold. Here, the system analyzing the remaining value can diagnose other defects in addition to internal degradation, plating, etc. In one method, the threshold is associated with the plating level related to specific battery chemical properties (e.g., lithium-ion), usage profile (e.g., harsh weather, rough terrain, rough driving, etc.). In this way, the estimation system 100 improves the reliability and accuracy of the safe state and remaining value output by intelligently selecting the threshold.

[0060] As described above, the estimation system 100 estimates one of the safety status, SOF, and physical degradation of a spent battery by calculating eddy interference. Here, the estimation system 100 can utilize a linear relationship derived from the first derivative of the real part related to impedance measurements. This allows the estimation system 100 to diagnose physical degradation as one of eddy currents due to material wear, SEI growth, and induced interference, while avoiding complexity in the testing process. This may include the estimation system 100 calculating eddy interference for an interference source using a linear relationship derived from the first derivative of the real part related to the measured interference. The estimation system 100 can identify the plating of terminals in a spent battery by comparing the difference between two values ​​of the first derivative within a frequency band to a threshold, identify the plating using standard testing equipment without disassembling the cells associated with the spent battery, and calculate the safety status using the degree of plating.

[0061] In various implementations, the estimation system 100 identifies the plating of terminals in a used battery from the difference between two or more first derivatives within a frequency band, using test equipment, without disassembling the cells associated with the used battery. Furthermore, the estimation system 100 can calculate the safety status of a used battery without impedance tracking from the time of manufacture.

[0062] In 430, the estimation system 100 estimates the remaining value from the safety and health states derived in response to changes in the first derivative. For example, the remaining state is SOF, which is SOS weighted by SOH, where SOH may represent one of the remaining capacity or charge capacity of the used battery. In one method, the estimation system 100 derives SOH from the average temperature using the output voltage, average operating temperature, and impedance. Thus, the estimation system 100 can reliably output one of the following: a safety state indicating degradation such as metal plating, or a remaining value for the used battery. This allows the system to identify whether the used battery is suitable for reuse and specific target applications. Otherwise, the system generates a recycling plan from the output, as the used battery is defective and too worn to be repaired. Therefore, the estimation system 100 can output a remaining value for the used battery, indicating its usability as a power source in reuse applications.

[0063] Detailed embodiments are disclosed herein. However, it should be understood that the disclosed embodiments are intended as examples. Accordingly, certain structural and functional details disclosed herein should not be construed as limiting, but merely as the basis for the claims and as representative grounds for teaching those skilled in the art to adopt various aspects of this specification in substantially any appropriately detailed structure. Furthermore, the terms and phrases used herein are not intended to be limiting, but are intended to illustrate feasible implementations. Various embodiments are shown in Figures 1 to 4, but these embodiments are not limited to the illustrated structures or applications.

[0064] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of feasible implementations of systems, methods, and computer program products according to various embodiments. In this regard, blocks in a flowchart or block diagram may represent modules, segments, or parts of code and contain one or more executable instructions for implementing a particular logical function. Note that in some alternative implementations, the functions described in a block may be performed in a different order than shown in the figure. For example, two blocks shown consecutively may actually be executed substantially simultaneously, or these blocks may sometimes be executed in reverse order depending on the functions involved.

[0065] The systems, components, and / or processes described above can be implemented in hardware or in combination of hardware and software, and can be implemented centrally in a single processing system or in a distributed form in which various elements are distributed across several interconnected processing systems. Any type of processing system or other device adapted to perform the methods described herein is suitable. A typical combination of hardware and software may be a processing system having computer-readable program code that, when loaded and executed, controls the processing system to perform the methods described herein.

[0066] Systems, components, and / or processes can also be embedded in computer-readable storage devices such as computer program products or other data program storage devices, and can perform the methods and processes described herein by tangibly embodying a program of machine-readable and machine-executable instructions. These elements can also be embedded in application products, which have features that enable the implementation of the methods described herein and, when loaded into a processing system, can perform these methods.

[0067] Furthermore, the configurations described herein may take the form of a computer program product embodied in one or more computer-readable media in which computer-readable program code is embodied (e.g., stored). Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The term "computer-readable storage medium" means a non-temporary storage medium. A computer-readable storage medium may be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any preferred combination of those described above. More specific examples (non-exclusive list) of computer-readable storage media would include portable computer diskettes, hard disk drives (HDDs), solid-state drives (SSDs), ROMs, EPROMs, or flash memory, portable compact disc read-only memory (CD-ROMs), digital versatile discs (DVDs), optical storage devices, magnetic storage devices, or any preferred combination of those described above. In the context of this specification, a computer-readable storage medium can be any tangible medium on which a program can be embedded or stored for use by or with an instruction execution system, apparatus, or device.

[0068] In general, modules as used herein include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular data type. In further embodiments, memory generally stores the modules mentioned. Memory associated with a module may be a processor, RAM, ROM, flash memory, or a buffer or cache embedded in another suitable electronic storage medium. In further embodiments, modules envisioned by this disclosure are implemented as ASICs, as hardware components of a system on a chip (SoC), as programmable logic arrays (PLAs), or as another suitable hardware component incorporating a defined set of configurations (e.g., instructions) for performing the disclosed functions.

[0069] Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, cable, radio frequency (RF), or any preferred combination thereof. Computer program code for performing operations for this configuration may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java®, Smalltalk®, and C++, and conventional procedural programming languages ​​such as the C programming language or similar languages. The program code may run entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it may be connected to an external computer (for example, via the Internet using an Internet Service Provider).

[0070] As used herein, the term “one” is defined as one or more. As used herein, the term “plural” is defined as two or more. As used herein, the term “another” is defined as at least two or more. As used herein, the terms “contain” and / or “have” are defined as “equipped with” (i.e., open terms). As used herein, the phrase “at least one of… and…” refers to and encompasses any combination of one or more of the listed related items. For example, the phrase “at least one of A, B, and C” includes A, B, C, or any combination thereof (e.g., AB, AC, BC, or ABC).

[0071] The embodiments described herein can be embodied in other forms without departing from their spirit or essential attributes. Therefore, the appended claims, rather than the above-described specification, should be used to indicate the scope of this specification.

Claims

1. It is an estimation system, It has a memory for storing instructions, and when an instruction is executed by the processor, the processor The command includes instructions to measure the impedance of a used battery using test equipment at a target temperature and a target state of charge (SOC), wherein the target temperature and target SOC are related to the chemical activity of the used battery, and further, An instruction to remove the interference source by calculating the first derivative of the real part of the impedance, An instruction to estimate the remaining value from the safety state and sound state derived in accordance with the change in the first derivative within the frequency band, An estimation system including, when the remaining value satisfies a parameter, a command to cause the device to transmit the remaining value and to cause the device to draw power from the used battery during reuse operation.

2. The instruction to estimate the remaining value further, An instruction to calculate eddy interference for the interference source using the linear relationship derived from the first derivative, A command to identify the plating on the terminals in the used battery by comparing the difference between two values ​​of the first derivative within the frequency band with a threshold, and to identify the plating using the test equipment without disassembling the cells associated with the used battery, The estimation system according to claim 1, further comprising a command to calculate the safety status using the degree of plating.

3. The instruction to estimate the remaining value further, The command includes causing the test equipment to measure the health status using the acquired sensor data relating to the used battery, wherein the sensor data includes the output voltage, the operating temperature, and the impedance at the reduced temperature, and further, The estimation system according to claim 2, which includes an instruction to output the remaining value by multiplying the safety status value, the health status value, and the weighting coefficient value related to the internal structure of the used battery.

4. The estimation system according to claim 1, wherein the instruction for the safety state to satisfy the parameters further includes an instruction for labeling the characteristics of the safety state as one of material wear and eddy currents due to inductive interference, wherein the material wear includes solid electrolyte interphase (SEI) growth on the battery cells associated with the spent battery.

5. The instructions further include causing the detection of mechanical deformation and cell displacement at the module level of the used battery from inductive interference between a metallic object and contact tabs associated with the battery module, wherein the mechanical deformation is associated with a vehicle-involved collision, and the module level does not involve disassembling the used battery to access the battery cells, and further, The estimation system according to claim 1, comprising an instruction to calculate the safety status of the used battery without impedance tracking from the time of manufacture of the used battery, provided that the cycling parameters are met.

6. A command to specify the temperature and SOC according to the cell layout of the used battery, The estimation system according to claim 1, further comprising a command to filter wear interference to the used battery using impedance values ​​from the frequency band.

7. The interference sources are inductive interference from iron and contact interference related to one of the cells and modules in the used battery. The estimation system according to claim 1, wherein the SOC is one of the charge level and discharge level related to chemical degradation.

8. The aforementioned health status is a state of health (SOH) that indicates one of the remaining capacity or charge capacity of the used battery. The remaining value is one of the functional state and state of function (SOF) related to the used battery, and the remaining value indicates the degree to which the used battery can be used as a power source for reuse purposes. The estimation system according to claim 1, wherein the reuse application is one of industrial reuse, residential reuse, and commercial reuse of the used battery.

9. The aforementioned safety condition indicates the plating within the cells of the module located inside the used battery. The aforementioned frequency band exceeds the frequency associated with increased chemical decomposition and increased ion response corresponding to the used battery. The estimation system according to claim 1, wherein the parameter indicates that one of the cells and modules in the used battery has undetected plating associated with a threshold on the surface of the anode.

10. A non-temporary computer-readable medium containing instructions, When the aforementioned instruction is executed by the processor, the processor will: The command includes instructions to have a test instrument measure the impedance of a used battery at a target temperature and a target SOC, wherein the target temperature and the target SOC are related to the chemical activity of the used battery, and further, An instruction to remove the interference source by calculating the first derivative of the real part of the impedance, An instruction to estimate the remaining value from the safety state and sound state derived in accordance with the change in the first derivative within the frequency band, A non-temporary computer-readable medium including, when the remaining value satisfies a parameter, an instruction to cause the device to transmit the remaining value and to cause the device to draw power from the used battery during reuse operation.

11. The instruction to estimate the remaining value further, An instruction to calculate eddy interference for the interference source using the linear relationship derived from the first derivative, A command to identify the plating on the terminals in the used battery by comparing the difference between two values ​​of the first derivative within the frequency band with a threshold, and to identify the plating using the test equipment without disassembling the cells associated with the used battery, A non-temporary computer-readable medium according to claim 10, comprising an instruction to calculate the safety state using the degree of plating.

12. It is a method, The process includes the step of measuring the impedance of a used battery at a target temperature and target state of charge (SOC) using test equipment, wherein the target temperature and target SOC are related to the chemical activity of the used battery, and further, The steps include: removing the interference source by calculating the first real derivative of the impedance; A step of estimating the remaining value from the safety state and sound state derived in accordance with the change in the first derivative within the frequency band, A method comprising the steps of: transmitting the remaining value to a device when the remaining value satisfies the parameters; and allowing the device to draw power from the used battery during reuse operation.

13. The step of estimating the residual value further includes: A step of calculating the eddy interference for the interference source using the linear relationship derived from the first derivative, The steps include: identifying the plating of the terminals in the used battery by comparing the difference between two values ​​of the first derivative within the frequency band with a threshold, and identifying the plating without disassembling the cells associated with the used battery using the test equipment; The method according to claim 12, further comprising the step of calculating the safety state using the degree of plating.

14. The step of estimating the residual value further includes: The step includes measuring the health status of the used battery using the acquired sensor data, wherein the sensor data includes the output voltage, the operating temperature, and the impedance at the reduced temperature, and further, The method according to claim 13, further comprising the step of outputting the remaining value by multiplying the safety status value, the health status value, and the weighting coefficient value related to the internal structure of the used battery.

15. The method according to claim 12, wherein the step of satisfying the parameters for the safety condition further includes labeling the characteristics of the safety condition as one of material wear and eddy currents due to inductive interference, wherein the material wear includes solid electrolyte interphase (SEI) growth on the battery cells associated with the spent battery.

16. The further steps include detecting mechanical deformation and cell displacement at the module level of the used battery from inductive interference between a metallic object and contact tabs associated with the battery module, wherein the mechanical deformation is associated with a vehicle-involved collision, and the module level does not involve disassembling the used battery to access the battery cells, and further, The method according to claim 12, further comprising the step of calculating the safety status for the used battery without impedance tracking from the time of manufacture of the used battery, provided that the cycling parameters are met.

17. The steps include determining the temperature and SOC according to the cell layout of the used battery, The method according to claim 12, further comprising the step of filtering out wear interference to the used battery using impedance values ​​from the frequency band.

18. The interference sources are inductive interference from iron and contact interference related to one of the cells and modules in the used battery. The method according to claim 12, wherein the SOC is one of the charge level and discharge level associated with chemical degradation.

19. The aforementioned health status is a state of health (SOH) that indicates one of the remaining capacity or charge capacity of the used battery. The remaining value is one of the functional state and functional state (SOF) related to the used battery, and the remaining value indicates the degree to which the used battery can be used as a power source for reuse purposes. The method according to claim 12, wherein the reuse use is one of industrial reuse, residential reuse, and commercial reuse of the used battery.

20. The aforementioned safety condition indicates the plating within the cells of the module located inside the used battery. The aforementioned frequency band exceeds the frequency associated with increased chemical decomposition and increased ion response corresponding to the used battery. The method according to claim 12, wherein the parameter indicates that one of the cells and modules in the used battery has undetected plating associated with a threshold on the surface of the anode.

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