System and method for time-series analysis of noise occurrence signals for battery charging

Abstract

Aspects of the present disclosure analyze one or more signals including both uncorrelated random signals and related information about electrochemical and / or electrodynamic processes occurring within the battery; the battery for charging, discharging, storage, and other uses and / or other aspects of controlling charging, discharging, and battery management are characterized based on the one or more signals.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is related to and claims priority under 35 U.S.C. §119(e) from U.S. patent application No. 63 / 324,505, entitled “Noise,” filed on March 28, 2022, the entire contents of which are incorporated herein by reference for all purposes. Technical Field

[0003] Aspects of the present disclosure analyze one or more signals that include both uncorrelated random signals and relevant information about electrochemical and / or electrokinetic processes occurring within a battery; characterize the battery for charging, discharging, storage, and other uses based on the signals and / or control charging, discharging, and other aspects of battery management. Background Art

[0004] Battery-powered devices have proliferated and become ubiquitous. Device manufacturers continue to demand improved performance of batteries, especially when batteries are introduced into devices with relatively high current demands and power requirements. At the same time, consumers demand longer battery life, longer time between charges, and shorter charging times. Thus, there is a constant need to improve the way batteries are managed, charged, and discharged to enhance performance. It is with these observations, as well as other factors, that the various aspects of the present disclosure have been conceived. Summary of the invention

[0005] Aspects of the present disclosure relate to a method comprising: accessing a noise signal from a battery, wherein the noise signal comprises uncorrelated noise and correlated signal data; and filtering the noise signal to isolate the correlated signal data. The method further relates to processing the correlated signal data to identify at least one of an electrochemical process or an electrokinetic process within the battery. In various possible embodiments, the noise signal is a voltage measurement or a current measurement at the battery. The signal may also be accessed from a memory. The noise signal may also be a measurement generated from at least one of a current measurement and a voltage measurement, such as an impedance measurement (determination).

[0006] The signal may be obtained during a balanced state of the battery, which may be during charging or discharging, or the signal may be obtained from a probe signal. A balanced state of the battery may be considered and occurs during a period of zero net change of the battery. The signal may also be obtained at a transient state of the battery, which may be associated with a charging signal or a discharging signal. The method may further include filtering the noise data, such as by means of a domain transform or other filtering technique, to identify relevant signal data. The domain transform may be one of a partial domain transform or a fractional domain transform.

[0007] The relevant signal data may be associated with plating and / or dendrite formation and growth. More generally, the relevant signal data may be associated with electrodynamic behavior in the battery. Thus, the systems and methods discussed herein may be useful for identifying electrodynamic behavior of the battery. Conversely, the irrelevant signal data may be thermal and may be considered noise, and thus removing the thermal information may help isolate the relevant signal data.

[0008] In various possible aspects, processing the associated signal data may involve identifying bifurcations, where the bifurcations indicate the start of additional electrochemical or electrokinetic processes, such as embedding as an additional process after plating.

[0009] The method may further involve changing a charging parameter (or a discharging parameter) based on the identification of an electrochemical or electrokinetic process within the battery.

[0010] Another aspect of the present disclosure relates to a method comprising: filtering a signal of an electrochemical device comprising unrelated data and relevant data about an electrochemical process or an electrokinetic process of the electrochemical device to identify relevant data containing information about the electrochemical process or the electrokinetic process; and changing a charging parameter based at least in part on the identification of a bifurcation in the filtered signal. The electrochemical device may be a battery, and the signal may be obtained, e.g., measured, during charging or discharging. Depending on the type of charging signal, the changed charging parameter may be a charging rate, a charging voltage, and / or a duty cycle. The charging parameter may also include a harmonic component of the charging signal.

[0011] These and other aspects of the disclosure are described in further detail below. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a diagram of a detection signal, which may also be a shaped charging signal, showing transient times A when data may be sampled for further processing and steady-state times B and / or C when data may also be sampled for further processing.

[0013] Figure 2 is Figure 1 An example of a signal captured at transient time A.

[0014] Figure 3 are examples of bifurcation diagrams and Lyapunov constant diagrams that are generated according to aspects of the present disclosure and reflect electrochemical battery cell processes and electrokinetic battery cell processes, as well as a portion of the information and actions associated therewith.

[0015] Figure 4is an example of a computer system that can be used to implement the methods discussed herein. DETAILED DESCRIPTION

[0016] Various aspects of the present disclosure relate to a new understanding that electrokinetic and electrochemical processes in electrochemical systems, particularly rechargeable batteries, can be identified based on what is typically considered discardable data. In a general sense, "noise" in an electrical system is considered to consist of unrelated, completely random signal data, and is typically ignored or efforts are made to suppress or remove it. However, in the present application, signals that are typically considered noisy are understood to contain information that can be associated with events occurring in a battery. The detection of such events and the processing of such signals can be further used, either individually or in combination, to change various actions on the battery, such as charging or discharging. Although various aspects of the present disclosure are discussed primarily in the context of battery charging and discharging, various aspects of the present disclosure are also applicable to other environments including electroplating systems.

[0017] The term "battery" in the art and herein may be used in various ways and may refer to individual cells having anodes and cathodes separated by solid or liquid electrolytes, as well as collections of such cells connected in various arrangements. A battery or battery cell is a form of electrochemical device. A battery typically includes repeating units of a countercharge source and electrode layers separated by an ion-conductive barrier, which is often a liquid or polymer film saturated with an electrolyte. These layers are made thin so that multiple units can occupy the volume of the battery, thereby increasing the available power of the battery per stacked unit. Although many examples applicable to batteries are discussed herein, it should be understood that the described systems and methods may be applied to many different types of batteries, from individual cells to batteries involving different possible interconnections of cells, such as cells connected in parallel, in series, and in parallel and in series. For example, the systems and methods discussed herein may be applied to a battery pack comprising many cells arranged to provide a defined group voltage, output current, and / or capacity. Furthermore, the embodiments discussed herein can be applied to different types of electrochemical devices, such as various different types of lithium batteries, including but not limited to lithium metal and lithium ion batteries, lead acid batteries, various types of nickel batteries, and solid-state batteries, to name a few. The various embodiments discussed herein can also be applied to different structural battery arrangements, such as button or "coin" type batteries, cylindrical cells, pouch cells, and prismatic cells.

[0018] First, the capture from the battery may appear as a noisy unfiltered signal, or a carefully filtered signal. For example, the system may include one or more filters designed to filter out easily identifiable hardware or other forms of auxiliary noise. In other words, one or more filters may be set or defined to remove signal data that is known to be related to hardware and environmental contributions (e.g., thermal effects) and not related to battery dynamics such as internal battery electrodynamics. The signal may be captured during steady state (equilibrium). The signal may also be captured in the presence of a detection signal. The detection signal may be a dedicated detection signal, or it may be a charging signal. The signal may also be captured during discharge. In a specific example, the detection signal is a charging signal and includes a transient portion and a steady state portion.

[0019] Figure 1 An example charging signal is shown, which includes a transient portion at A and a relatively steady-state portion at B and C. The detection signal may similarly have a transient portion and / or a steady-state portion. In this diagram, the y-axis is a voltage in the range of about 0 volts (relative to the open circuit at the battery terminal) to about 5 volts for many traditional single lithium-ion cells with an open circuit voltage of about 4.2 volts, but it may be higher; however, the y-axis may also be a current and display a similar waveform. The upper voltage limit depends on a number of factors, and the examples here are provided only for relative reference. As seen at positions B and C, the signal is at a steady-state voltage, even if it only lasts about 0.25ms. In contrast, at position A, the signal drops rapidly from a first steady state to a lower second steady state in about 0.25ms, with the transition region between the steady states being transient. Data may be captured at time A and / or time B and / or time C. It is worth noting that the charging signal here is tailored to not include any sharp high-frequency charging edges associated with pulse charging, which would take the form of a square wave with approximately 90 degree transitions (shown in dashed lines for comparison purposes) and is not considered pulse charging. However, the techniques discussed herein can be used to modify pulse charging signals. Data can also be captured at other points, where A, B, and C are only examples. In the example signal, A is the point immediately after the charging current stops but when the charging voltage begins to drop to zero after the charging current stops. Point B is a point after the charging current and charging voltage are approximately zero and before the subsequent charging energy starts. C indicates the active control and excitation point of the current and voltage.

[0020] Figure 2 is a graphical representation of the signal captured at point A. The data captured at point B will be of similar quality, although will contain information associated with a temporary steady state rather than transient processes within the cell. Similarly, the data at point C will contain information about processes associated with electrical activity occurring within the cell simultaneously with a particular current and potential.

[0021] More specifically and as described above, a correlated signal disguised as uncorrelated noise is included in the noise occurrence data. This correlated data is captured using uncorrelated information. The correlated (deterministic) signal is associated with the electrochemical and electrokinetic processes occurring in the battery. Thus, and in accordance with various aspects of the present disclosure, a large amount of useful information can be obtained by isolating the relevant information, associating the information with some events occurring in the battery, and / or subsequently taking action on the information and event correlation to change the charging, discharging, characterization parameters or other actions for or about the battery. Traditionally, it has not been recognized that there is a correlation between electrochemical information and electrokinetic information and the correlated signal features hidden in complex noise. Similarly, there has not been any attempt to use such information to manage electrical energy for charging or discharging batteries, electroplating or other purposes.

[0022] In one example, during equilibrium (steady state), when there is no charging or discharging of the battery, some electrochemical processes occur, such as involving ion diffusion, intercalation, and deintercalation. Typically, there is no net change associated with such equilibrium activity. Nonetheless, these steady-state processes are reflected in and can be identified from the correlation signal, which can be isolated from and otherwise detected in the measured signal.

[0023] In another example, a related signal within the broader data signal may reflect lithium plating and can be used to identify such events. Lithium plating can cause dendrite growth and other problems. During charging, lithium ions from the cathode are inserted into the anode in a process known as intercalation. At the same time, lithium can plate the anode, which is undesirable and can cause various problems, including capacity degradation and increased internal cell resistance. Dendrite growth can be associated with capacity degradation and further lead to short circuit conditions, which can cause battery failure. There are some known causes for plating, including charging at a rate that exceeds the rate at which some ions can be intercalated (a rate that is considered too high) and charging at a temperature that is too low for ions to be effectively intercalated. In addition to changing the charging signal, when it is determined that plating has begun, the system can also wait until the temperature increases to an acceptable threshold to resume charging.

[0024] According to aspects of the present disclosure, it has been further discovered that plating, including dendrite formation and growth, can also be caused or exacerbated by uncontrolled charging signal noise, particularly by relatively high frequency charging signal noise. This noise may originate from processes within the cell, from external sources such as nearby electrical components or radiation signals, or from frequent alternations between net charge and discharge states, among other sources. Uncontrolled charging signal noise is considered to be associated with electrodynamic effects and conductive path concentrations in the anode, cathode and / or associated current collectors. The conductive paths induced by electrodynamic noise may subsequently cause local current concentrations, leading to plating and dendrite formation. Therefore, aspects of the present disclosure are directed to identifying such conditions and counteracting or otherwise mitigating the uncontrolled noise.

[0025] To address some or all of these issues and others, a particular aspect of the present disclosure involves identifying plating within an unchanged or carefully altered (e.g., filtered, as discussed above) signal, and further may involve changing some conditions (e.g., some aspects of the charging signal) to reduce or eliminate plating. The ability to detect plating in relevant data (which may be part of an otherwise noisy signal with unrelated data) may be based at least in part on the recognition that plating and dendrite formation and growth are three-dimensional and sometimes fractal in nature. Filtering the signal data to isolate or otherwise identify relevant content, and subsequent further processing that may involve various evaluations of a statistical and deterministic nature may be used to identify plating and take action on it.

[0026] In terms of charge state and as described above with respect to plating, charging involves diffusion of ions from the cathode to the anode. As the charge state rises, the diffusion pattern changes with the available ions in the cathode, and the intercalation activity at the anode decreases. This activity reflects data from the battery related to both electrochemical and electrokinetic processes in the correlation signal within the signal, and can therefore be identified according to the techniques discussed herein.

[0027] Although many processes are at work within the battery when it is being charged, in one example, a beneficial and possibly normal and harmless process within the battery involves diffusion of ions from the cathode to the anode. As mentioned above, plating and dendrite growth may occur under some adverse charging conditions. In another case, when the battery approaches a fully charged state, the diffusion process from the cathode to the anode decreases as the available lithium inventory decreases. The energy that is usually used to charge the battery healthily may then be turned to plating. In conventional processes, since the electrodynamics of diffusion and plating are related and occur continuously, the two processes are extremely difficult to distinguish, and the beginning of plating is extremely difficult to distinguish from healthy charge transfer reactions. However, in one aspect of the present disclosure, relevant data during charging is processed to identify bifurcations. The beginning of bifurcation indicates the beginning of different processes within the data. In the case of extracting relevant data from a data signal during charging, the method may involve generating a bifurcated data set (usually displayed as a bifurcation diagram) and identifying the occurrence of bifurcations. Causing bifurcations may indicate changes from healthy diffusion during charging and transitions to additional processes such as plating, indicating at the bifurcation that charging energy is being used for both charging and plating. Thus, upon identifying a bifurcation, the system may alter the charging signal, such as by reducing the charging current, reducing the charging voltage, reducing both the charging current and charging voltage, changing the duty cycle, changing the pulse characteristics, or making other charging signal changes.

[0028] Healthy cathode phase changes may also occur during charging. This change can also be identified by bifurcation. Evaluating the state of charge or taking action on information during charging can be based on various parameters, such as identifying the start of plating and identifying cathode phase changes, alone or in multiple combinations. For example, in the presence of a bifurcation associated with the start of plating, the charging signal can be reduced (e.g., reducing the charging current), as noted above, thereby reducing the charging energy, to have the effect of stopping plating. The system can then evaluate or assume that plating has stopped, and continue to analyze relevant data until the start of another bifurcation, and then repeat the process (changing charging parameters). It should be recognized that the process can be performed in conjunction with SOC evaluation or voltage level evaluation or other additional information sets to identify when charging is complete, such as 100%.

[0029] Non-uniform plating and dendrite growth, etc. can be understood as being essentially fractal. In addition, some processes and other battery processes that are essentially fractal are considered to be undesirable, while other processes can be considered to be normal and non-destructive or otherwise undesirable. Thus, the relevant data in the signal can be generally characterized as fractal, which leads to the same opportunity to process the data, and then the data is associated with some undesirable or favorable processes in the battery cell. In addition, when the relevant signal is isolated from the actual noise in the signal, various statistical analysis techniques can be used to process the relevant signal, some of which are directly related or tangentially related to impedance and electrochemical physics, while other techniques are different from impedance-based parameters and reflect a wider range of electrodynamics. Many examples are possible, including generating bifurcated data as discussed above and generating Lyapunov exponents. This can be related to the state of charge, health state, instantaneous degradation, temperature distribution, voltage, current, impedance and other useful metrics. Processing the relevant signal alone or in various processing combinations will produce information indicating various desired or otherwise normal electrochemical processes and electrodynamic processes and undesirable processes.

[0030] Figure 3 is an example of a bifurcation diagram. In this example, the y-axis is voltage, but the same analysis can be performed using current or impedance as well as other calculated, derived or reference values ​​or combinations of values. The x-axis is the state of charge (SOC). In general, the Lyapunov is a parameter of behavior that can be used to identify and define relevant information within otherwise meaningless data. Positive values ​​indicate increasingly irrelevant behavior. Negative values ​​indicate periodic behavior. Values ​​close to or at zero indicate the beginning of chaotic behavior, while a trend across zero at least indicates a bifurcation in the measured parameter. Truly irrelevant data, such as noise or thermal processes, are reflected by large positive values. In Figure 3 In the graph, the current is held at 2C during a full charge cycle to show how the Lyapunov starts with a periodic feature and then quickly becomes chaotic. The positive values ​​last for a short period of time, during which the activity in the cell, especially at the electrodes, is irregular as parts of the electrode surface transition to a new electron exchange mechanism. This phenomenon is measured almost instantaneously and would be completely unobservable in traditional impedance-based analysis forms. As noted above, bifurcations can imply the beginning of two or more parallel paths in the data. At SOC above 20%, the beginning of the second path is identified. In this graph, the path continues to 100% SOC to indicate the sensitivity of the battery. In practice, the detection of bifurcations during charging will cause a rapid adjustment of the charging signal, such as a decrease in current or voltage, which will terminate the lithium plating path. This method, alone or in combination with other analyses, can be used to detect the beginning of lithium plating that occurs in parallel with intercalation associated with healthy charging and ion diffusion. The combined multiple parameters can be used to identify key behaviors of any battery chemistry, size or architecture, and electrochemical systems in general.

[0031] The information itself is valuable in characterizing the battery and is valuable in controlling the charge or discharge of the battery, as well as having other values, such as the healthy generation of the battery (a process that is neither charging nor discharging in the traditional sense). The information can also be applied to charge or discharge control. For example, detecting the early onset of plating and modifying the charging signal to avoid early onset of plating contributes to longer battery cycle life, battery capacity, charge rate, capacity utilization, and battery safety. Detection of the charging state has many similar advantages, including higher battery capacity utilization, effective charge rate control, discharge control, longer cycle life, and overall battery safety.

[0032] refer to Figure 4 , a detailed description of an example computing system 400 having one or more computing units that can implement various systems and methods discussed herein is provided. The computing system 400 may be part of a controller, may be in operative communication with various embodiments discussed herein, may run various operations related to the methods discussed herein, may run offline to process various data for characterizing a battery, and may be part of an overall system discussed herein. In any possible embodiment, there may be more or fewer components of the system 400. In a system for characterizing a battery or a battery type, a similar system may be involved, because the system may be configured to implement various charging signals, process and analyze noise signals, and take action on them. A user interface may also be involved to obtain input about the type of battery being characterized. In some applications, such as power tools, relatively small mobile devices such as electric bicycles, and some mobile computing applications, fewer or otherwise more streamlined systems may be used. In some applications, system components of a broader system may be shared, such as in a mobile "smart" phone or tablet computer.

[0033] The computing system 400 may process the various signals discussed herein (e.g., Figure 1 , 2) and / or may provide various signals discussed herein. For example, battery measurement information that is not associated with any particular interpretation, or ambiguous or incorrect interpretations using other methods such as electrochemical impedance spectroscopy, nonlinear electrochemical impedance spectroscopy, equivalent circuit models, empirically derived neural network-based models, or models based primarily on thermal and electrochemical physics, may be provided to this computing system 400. The system may run transformations on the information and analyze the information. The system may use the information to characterize the battery, or may control some processes, such as charging or discharging. It should be understood that the specific embodiments of these devices may be different possible specific computing architectures, all of which are not specifically discussed herein, but will be understood by those of ordinary skill in the art. It should be further understood that the computer system may be considered and / or include an ASIC, FPGA, microcontroller, or other computing arrangement. In such various possible embodiments, more or fewer components discussed below may be included, interconnected, and otherwise changed, as those of ordinary skill in the art will understand.

[0034] The computer system 400 may be a computing system capable of executing a computer program product to perform a computer process. Data and program files may be input into the computer system 400, which reads the files and executes the programs therein. Figure 4 4. Some of the elements of computer system 400 are shown in FIG. 4, including one or more hardware processors 402, one or more data storage devices 404, one or more memory devices 406, and / or one or more ports 408-412. In addition, those skilled in the art will recognize that other elements may be included in computing system 400, but are not shown in FIG. Figure 4 The various elements of computer system 400 may be connected to one or more communication buses, point-to-point communication paths, or Figure 4 Other communication components not explicitly depicted in the system communicate with each other. Similarly, in various embodiments, various elements disclosed in the system may or may not be included in any given embodiment.

[0035] Processor 402 may include, for example, a central processing unit (CPU), a microprocessor, a microcontroller, a digital signal processor (DSP), and / or one or more internal levels of cache. There may be one or more processors 402, such that processor 402 includes a single central processing unit, or multiple processing units capable of executing instructions and performing operations in parallel with each other, which is generally referred to as a parallel processing environment.

[0036] The presently described techniques, in various possible combinations, may be implemented at least in part in software stored on the data storage device 404, stored on the memory device 406, and / or transmitted via one or more of the ports 408-412, thereby Figure 4 The computer system 400 in FIG. 4 is transformed into a special-purpose machine for performing the operations described herein.

[0037] The one or more data storage devices 404 may include any non-volatile data storage device capable of storing data generated or employed within the computing system 400, such as computer executable instructions for executing computer processes, which may include instructions for both application programs and an operating system (OS) that manages the various components of the computing system 400. The data storage device 404 may include, but is not limited to, a magnetic disk drive, an optical disk drive, a solid state drive (SSD), a flash drive, and the like. The data storage device 404 may include removable data storage media, non-removable data storage media, and / or an external storage device available via a wired or wireless network architecture with such computer program products, including one or more database management products, network server products, application server products, and / or other additional software components. Examples of removable data storage media include compact disk read-only memory (CD-ROM), digital versatile disk read-only memory (DVD-ROM), magneto-optical disk, flash drive, and the like. Examples of non-removable data storage media include internal magnetic hard disks, SSDs, and the like. One or more memory devices 406 may include volatile memory (eg, dynamic random access memory (DRAM), static random access memory (SRAM), etc.) and / or nonvolatile memory (eg, read only memory (ROM), flash memory, etc.).

[0038] A computer program product containing mechanisms for implementing systems and methods according to the presently described technology may reside in data storage device 404 and / or memory device 406, which may be referred to as a machine-readable medium. It should be appreciated that a machine-readable medium may include any tangible, non-transitory medium capable of storing or encoding instructions to perform any one or more operations of the present disclosure for execution by a machine, or any tangible, non-transitory medium capable of storing or encoding data structures and / or modules utilized by or associated with such instructions. A machine-readable medium may include a single medium or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) storing one or more executable instructions or data structures.

[0039] In some embodiments, the computer system 400 includes one or more ports for communicating with other computing, network, or vehicle devices, such as input / output (I / O) ports 408, communication ports 410, and subsystem ports 412. It should be appreciated that ports 408-412 may be combined or separated, and that more or fewer ports may be included in the computer system 400. The I / O port 408 may be connected to an I / O device or other device through which information is input to or output from the computing system 400. Such I / O devices may include, but are not limited to, one or more input devices, output devices, and / or environmental transducer devices.

[0040] In one embodiment, the input device converts human-generated signals such as human voice, body movement, physical touch, or pressure into electrical signals as input data that is input to the computing system 400 via the I / O port 408. In some examples, such input may be different from the various systems and methods discussed with respect to the previous figures. Similarly, the output device may convert electrical signals received from the computing system 400 via the I / O port 408 into signals that can be sensed or used by the various methods and systems discussed herein. The input device may be an alphanumeric input device that includes alphanumeric keys and other keys for transmitting information and / or command selections to the processor 402 via the I / O port 408.

[0041] The environmental transducer device converts one form of energy or signal into another form of energy or signal for input into or output from the computing system 400 via the I / O port 408. For example, an electrical signal generated within the computing system 400 may be converted into another type of signal, and / or vice versa. In one embodiment, the environmental transducer device senses a characteristic or aspect of the environment local to or remote from the computing device 400, such as battery voltage, open circuit battery voltage, charging current, battery temperature, light, sound, temperature, pressure, magnetic field, electric field, chemical property, etc.

[0042] In one embodiment, the communication port 410 can be connected to a network by means of which the computer system 400 can receive network data useful for executing the methods and systems described herein and transmitting information and network configuration changes determined thereby. For example, charging protocols can be updated, battery measurements or calculations can be shared with external systems, and so on. The communication port 410 connects the computer system 400 to one or more communication interface devices that are configured to transmit and / or receive information between the computer system 400 and other devices by means of one or more wired or wireless communication networks or connections. Examples of such networks or connections include, but are not limited to, Universal Serial Bus (USB), Ethernet, Wi-Fi, Near Field Communication (NFC), Long Term Evolution (LTE), etc. One or more such communication interface devices may be utilized via communication port 410 to communicate with one or more other machines directly through a point-to-point communication path, through a wide area network (WAN) (e.g., the Internet), through a local area network (LAN), through a cellular (e.g., third generation (3G), fourth generation (4G), fifth generation (5G)) network, or through another communication means.

[0043] The computer system 400 may include a subsystem port 412 for communicating with one or more systems related to charging a device to control the operation of the device and / or exchanging information between the computer system 400 and one or more subsystems of the device according to the methods and systems described herein. Examples of such subsystems of a vehicle include, but are not limited to, motor controllers and systems, battery management systems, and the like.

[0044] Figure 4 The system described in is only one possible example of a computer system that can be employed or configured according to various aspects of the present disclosure. It should be understood that other non-transitory tangible computer-readable storage media that store computer-executable instructions for implementing the techniques of the present disclosure on a computing system can be utilized.

[0045] Embodiments of the present disclosure include various steps described in this specification. The steps may be performed by hardware components or may be embodied in machine executable instructions, which may be used to cause a general or special purpose processor programmed with the instructions to perform the steps. Alternatively, the steps may be performed by a combination of hardware, software, and / or firmware.

[0046] Various modifications and additions may be made to the discussed exemplary embodiments without departing from the scope of the present invention. For example, although the embodiments described above, also referred to as implementations or examples, refer to specific features, the scope of the present invention also includes embodiments having different combinations of features and embodiments that do not include all of the described features. Therefore, the scope of the present invention is intended to cover all such alternatives, modifications and variations and all equivalents thereof.

[0047] Although specific embodiments are discussed, it should be understood that this is done for illustrative purposes only. Those skilled in the relevant art will recognize that other components and configurations may be used without departing from the spirit and scope of the present disclosure. Therefore, the following description and drawings are illustrative and should not be construed as limiting. Many specific details are described to provide a thorough understanding of the present disclosure. However, in some cases, well-known or conventional details are not described to avoid ambiguous descriptions. A reference to one or an embodiment in the present disclosure may be a reference to the same embodiment or any embodiment; and such references refer to at least one of the embodiments.

[0048] Reference to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. The appearances of the phrase "in one embodiment" or similarly "in one instance" or "in one case" in various places in this specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. In addition, various features are described that may be exhibited by some embodiments but not by others.

[0049] The terms used in this specification sheet usually have their general meaning in the art in the context of the present disclosure and in the specific context of using each term. For any one or more of the terms discussed herein, alternative language and synonyms can be used, and no matter whether the terms are described in detail or discussed herein, special meanings should not be added. In some cases, synonyms of some terms are provided. The detailed description of one or more synonyms does not exclude the use of other synonyms. The examples used anywhere in this specification sheet (including the examples of any terms discussed herein) are only illustrative, and are not intended to further limit the scope and meaning of the present disclosure or any example terms. Similarly, the present disclosure is not limited to the various embodiments provided in this specification sheet.

[0050] In the case of not intending to limit the scope of the present disclosure, the examples of instruments, equipment, methods and related results thereof according to the embodiments of the present disclosure are given below. It should be noted that for the convenience of the reader, titles or subtitles can be used in the examples, which should never limit the scope of the present disclosure. Unless otherwise defined, the technical terms and scientific terms used herein all have the same meaning as the meanings commonly understood by those of ordinary skill in the art to which the present disclosure belongs. In the case of conflict, this document (including definitions) shall prevail.

[0051] Additional features and advantages of the present disclosure will be set forth in the subsequent description, and to some extent will become apparent from the description or can be learned by practicing the principles disclosed herein. The features and advantages of the present disclosure can be realized and obtained by means of the instruments and combinations specifically pointed out in the appended claims. These and other features of the present disclosure will become more apparent from the following description and the appended claims, or can be learned by practicing the principles set forth herein.

Claims

1. A method comprising: accessing a noise signal from a battery, the noise signal comprising uncorrelated noise and correlated signal data; filtering the noise signal to isolate the relevant signal data; as well as The correlated signal data is processed to identify at least one of an electrochemical process or an electrokinetic process within the battery. The method of claim 1 , wherein the noise signal is a voltage measurement. The method of claim 1 , wherein the noise signal is a current measurement. 4 . The method of claim 1 , wherein the noise signal is a measurement generated from at least one of a current measurement and a voltage measurement. The method of claim 4 , wherein the noise signal is a generated impedance measurement. The method according to claim 1 , wherein the noise signal is obtained in a balanced state of the battery.

7. The method of claim 6, wherein the equilibrium state of the battery is during a charge or discharge sequence of the battery. The method of claim 6 , wherein the equilibrium state of the battery is during a period of zero net change of the battery.

9. The method according to claim 1, wherein the noise signal is obtained in a transient state of the battery.

10. The method of claim 9, wherein the transient is associated with a charging signal or a discharging signal. The method of claim 1 , wherein filtering comprises domain transformation, and identifying the correlated signal data.

12. The method of claim 1, wherein the correlated signal data is associated with plating.

13. The method of claim 1, wherein the correlated signal data is associated with dendrite formation and growth.

14. The method of claim 1, wherein the correlated signal data is associated with electrokinetic behavior in the battery.

15. The method of claim 1, wherein the associated signal data is indicative of a specific battery or a specific type of battery.

16. The method of claim 1, wherein the correlated signal data is associated with a balancing process within the battery.

17. The method of claim 1, wherein the uncorrelated signal data is thermal.

18. The method of claim 11, wherein the domain transform is one of a partial domain transform or a fractional domain transform.

19. The method of claim 1, wherein processing the correlated signal data involves identifying bifurcations that indicate the onset of additional electrochemical or electrokinetic processes.

20. The method of claim 1, further comprising: A charging parameter is varied based on the identification of the electrochemical process or the electrokinetic process within the battery.

21. The method of claim 1, further comprising: A discharge parameter is varied based on the identification of the electrochemical process or the electrokinetic process within the battery.

22. A method comprising: Based on a signal of an electrochemical device comprising irrelevant data and comprising relevant data regarding an electrochemical process or an electrokinetic process of the electrochemical device, filtering the signal to identify the relevant data comprising information regarding the electrochemical process or the electrokinetic process; as well as A charging parameter is changed based at least in part on the identification of a bifurcation in the filtered signal.

23. The method of claim 22, wherein the electrochemical device is a battery.

24. The method of claim 22, wherein the signal is measured during charging or discharging.

25. The method of claim 22, wherein the charging parameter comprises at least one of a charging rate, a charging voltage, or a duty cycle.

26. The method of claim 22, wherein changing the charging parameter comprises reducing at least one of a charging current or a charging voltage.

27. The method of claim 22, wherein the charging parameter comprises a harmonic component of a charging signal.

28. The method of claim 22, wherein the correlated data is at least partially about plating of the anode, and changing the charging parameters reduces plating.

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