Electrochemical Process Manifold for Monitoring Battery Cells

Abstract

A system, method, and apparatus for constructing an electrochemical process manifold (EPM) for a battery cell during a formation process. A current through the cell is controllably adjusted to charge or discharge the cell. Temperature and / or pressure may be controllably adjusted along with the current. At each of a plurality of time steps during which the current is controllably adjusted, a voltage across the cell is measured and integrated over time to obtain a voltage-time value for each time step. For each time step, data points are stored in a memory, including the measured voltage, the voltage-time value, and the current through the cell for each time step. The data points for each time step are mapped to an EPM, and the EPM is stored in a non-transitory computer-readable memory medium.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Patent Application No. 63 / 380,040, filed October 18, 2022, entitled "Electrochemical Process Manifolds for Battery Cell Monitoring," which is hereby incorporated by reference in its entirety as if fully and in detail set forth herein.

[0002] The present invention relates to the field of battery cell manufacturing and formation. [Background technology]

[0003] The typical workflow for battery cell construction involves cell fabrication, formation, and aging. Yields in battery cell manufacturing processes are typically below 80% due to variability in the electrochemical processes involved, and improving this yield rate is challenging. Furthermore, formation and aging are time-consuming processes, taking days to complete. Aging involves repeated cell measurements to detect anomalies, which can be difficult to detect and pose significant risks to product performance and safety. Current implementations for addressing these issues are prohibitively expensive at scale. Battery cell factories use equipment and infrastructure to cycle and age large numbers of cells, potentially numbering in the millions at peak operation. Therefore, improvements in this area are desirable, particularly in efficient and effective mass-production battery cell formation, aging, and manufacturing. Summary of the Invention

[0004] Presented herein are various embodiments of systems, methods, and apparatus for constructing an electrochemical process manifold (EPM) for a battery cell during the formation process.

[0005] In some embodiments, the current through (or voltage across) the cell is controllably adjusted to charge or discharge the cell, hi some embodiments, the temperature and / or pressure may be controllably adjusted along with the current.

[0006] In some embodiments, at each of a number of time steps during which the current is controllably adjusted, the voltage across the cell is measured and integrated over time to obtain a voltage-time value for each time step. For each time step, data points may be stored in memory including the measured voltage, the voltage-time value, and the current through the cell at each time step.

[0007] In some embodiments, rather than controllably adjusting the current through the cell and periodically measuring the voltage, the voltage across the cell may be controllably adjusted and the current may be periodically measured.

[0008] In some embodiments, the data points for each time step are mapped to an electrochemical process manifold (EPM).

[0009] In some embodiments, the EPM is stored on a non-transitory computer-readable memory medium.

[0010] This summary is intended to provide a brief overview of some of the subject matter described herein. Accordingly, it should be understood that the features described above are merely examples and should not be construed in any way as narrowing the scope or spirit of the subject matter described herein. Other features, aspects, and advantages of the subject matter described herein will become apparent from the following detailed description, drawings, and claims. [Brief explanation of the drawings]

[0011] The present invention can be better understood when the detailed description of the preferred embodiment is considered in conjunction with the following drawings.

[0012] [Figure 1]FIG. 1 illustrates a battery cell manufacturing workflow, according to some embodiments.

[0013] [Figure 2] FIG. 2 illustrates a computer system coupled to a controller, according to some embodiments.

[0014] [Figure 3] FIG. 3 is a block diagram of a basic computer system according to some embodiments.

[0015] [Figure 4] FIG. 4 is a flow diagram illustrating a method for constructing an electrochemical process manifold (EPM) by controllably adjusting the current through cells, according to some embodiments.

[0016] [Figure 5] FIG. 5 is a flow diagram illustrating a method for constructing an electrochemical process manifold (EPM) by controllably adjusting the voltage across cells, according to some embodiments.

[0017] [Figure 6] FIG. 6 shows a schematic diagram of a cell formation setup, according to some embodiments.

[0018] [Figure 7] FIG. 7 shows exemplary waveforms for controllably adjusting the current through a cell, according to some embodiments.

[0019] [Figure 8] FIG. 8 shows an expanded portion of the waveform shown in FIG. 7, according to some embodiments.

[0020] [Figure 9] FIG. 9 shows Vcross voltage measurements for different charge values ​​according to some embodiments.

[0021] [Figure 10] FIG. 10 shows an example of a displayed EPM, according to some embodiments.

[0022] [Figure 11] FIG. 11 shows two different examples of EPMs, according to some embodiments.

[0023] While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and are herein described in detail. It should be understood, however, that the drawings and detailed description are not intended to limit the invention to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims. DETAILED DESCRIPTION OF THE INVENTION

[0024] Abbreviation Below is a list of abbreviations used in this application:

[0025] EPM: Electrochemical Process Manifold

[0026] DUT: Device under test

[0027] SUT: System Under Test

[0028] AC: Alternating current

[0029] IGBT: Insulated gate bipolar transistor

[0030] ADC: Analog-to-Digital Converter

[0031] PLD: Programmable Logic Device

[0032] FPGA: Field Programmable Gate Array

[0033] TX / RX: Transmit / Receive

[0034] CLK: Clock

[0035] LED: Light-emitting diode

[0036] BCI: Battery Cell Interface

[0037] BCF: Battery cell fixture

[0038] PDU: Power Distribution Unit

[0039] term Below is a glossary of terms used in this application.

[0040] Memory medium—Any of various types of non-transitory computer-accessible memory or storage device. The term “memory medium” is intended to include installation media such as CD-ROMs, floppy disks 104, or tape drives; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM; magnetic media such as flash, hard drives, or non-volatile memory such as optical storage devices; registers and other similar types of memory elements. Memory media may also include other types of non-transitory memory, or combinations thereof. Furthermore, the memory medium may be located on a first computer on which a program is executed, or on a second, separate computer connected to the first computer via a network such as the Internet. In the latter case, the second computer may provide the first computer with program instructions for execution. The term “memory medium” may include two or more memory media that may reside in different locations, such as separate computers connected via a network.

[0041] Carrier Medium - includes the memory media mentioned above as well as physical transmission media such as a bus, network, and / or other physical transmission medium that carries signals such as electrical, electromagnetic, or digital signals.

[0042] Programmable Hardware Element - includes a variety of hardware devices containing multiple programmable function blocks connected via programmable interconnects. Examples include FPGAs (Field Programmable Gate Arrays), PLDs (Programmable Logic Devices), FPOAs (Field Programmable Object Arrays), and CPLDs (Complex PLDs). Programmable function blocks can range from fine-grained (combinational logic or lookup tables) to coarse-grained (arithmetic logic units or processor cores). Programmable hardware elements are sometimes also referred to as "reconfigurable logic."

[0043] Processing Element—Refers to various elements or combinations of elements capable of performing functions in a device such as user equipment or cellular network equipment. A processing element may include, for example, a processor and associated memory, portions or circuitry of an individual processor core, an entire processor core, a processor array, circuitry such as an ASIC (Application Specific Integrated Circuit), a programmable hardware element such as a Field Programmable Gate Array (FPGA), and any various combinations of the above.

[0044] Software Program—The term “software program” is intended to have the full scope of its ordinary meaning and includes any type of program instructions, code, scripts, and / or data, or combinations thereof, that can be stored on a memory medium and executed by a processor. Exemplary software programs include programs written in text-based programming languages ​​such as C, C++, PASCAL, FORTRAN, COBOL, JAVA, assembly language, graphical programs (programs written in graphical programming languages), assembly language programs, programs compiled into machine language, scripts, and other types of executable software. A software program may include two or more software programs that interoperate in some manner. It should be noted that the various embodiments described herein may be implemented by a computer or software program. A software program may be stored as program instructions on a memory medium.

[0045] Hardware Configuration Program - A program, such as a netlist or bitfile, that can be used to program or configure programmable hardware elements.

[0046] Program - The term "program" is intended to have the full scope of its ordinary meaning. The term "program" includes 1) a software program storable in a memory and executable by a processor, or 2) a hardware configuration program usable to configure a programmable hardware element.

[0047] Computer System - Any of various types of computing or processing systems, including personal computer systems (PCs), mainframe computer systems, workstations, network appliances, Internet appliances, personal digital assistants (PDAs), television systems, grid computing systems, and other devices or combinations of devices. In general, the term "computer system" can be broadly defined to include any device (or combination of devices) having at least one processor that executes instructions from a memory medium.

[0048] Measurement devices—include instruments, data acquisition devices, smart sensors, and any of a variety of other types of devices configured to acquire and / or store data. Measurement devices may optionally be further configured to analyze or process the acquired or stored data. Measurement devices may optionally be further configured as signal generators that generate signals to be supplied to the device under test. Examples of measurement devices include traditional stand-alone “box” instruments, computer-based instruments (card-based instruments), or external instruments, data acquisition cards, devices external to a computer that operate similarly to data acquisition cards, smart sensors, one or more DAQ or measurement cards or modules within a chassis, image acquisition devices such as image acquisition (or machine vision) cards (also called video capture boards) or smart cameras, motion control devices, robots with machine vision, signal generators, and other similar types of devices. Exemplary “stand-alone” instruments include oscilloscopes, multimeters, signal analyzers, arbitrary waveform generators, spectroscopes, and similar measurement, inspection, or automation equipment.

[0049] The measurement device may be further configured to perform control functions, for example, in response to analysis of the acquired or stored data. For example, the measurement device may send control signals to an external system, such as a motion control system, or to a sensor in response to particular data. The measurement device may be further configured to perform automated functions, i.e., receive and analyze data and issue automated control signals in response.

[0050] Functional Unit (or Processing Element) - refers to various elements or combinations of elements. Processing elements include, for example, circuits such as ASICs (Application Specific Integrated Circuits), portions or circuits of individual processor cores, entire processor cores, individual processors, programmable hardware devices such as Field Programmable Gate Arrays (FPGAs), and / or larger portions of systems containing multiple processors, and any combination thereof.

[0051] Radio - A communication, monitoring, or control system in which electromagnetic or sound waves send signals through space rather than along wires.

[0052] Approximately—refers to a value that is within a certain tolerance or acceptable error or uncertainty of a target value, where the particular tolerance or error is generally application dependent. Thus, for example, in various applications or embodiments, the term approximately may mean within 0.1% of the target value, within 0.2% of the target value, within 0.5% of the target value, within 1%, 2%, 5%, or 10% of the target value, etc., depending on the needs of the particular application of the technology.

[0053] SUT Interface - One or more antenna probes and potential supporting components that modify the collective characteristics that the antenna probes and components exhibit to electromagnetic radiation associated with radio signals, provide structural integrity to the assembly, and may be used to measure radio signals generated by the SUT.

[0054] Figure 1- Battery cell manufacturing workflow 1 is a flow diagram illustrating a method for manufacturing a battery cell, according to some embodiments. At 104, after physically constructing the battery cell components, a case closure is provided to house the battery components. At 106, the cell is inspected for quality prior to the formation process. At 108, the cell formation process is performed, in which the cell is repeatedly charged and discharged to establish a stable voltage differential between the positive and negative electrodes. Embodiments herein construct an electrochemical process manifold (EPM) 110 for the cell during charge and / or discharge to aid in cell diagnostics and improve the cell formation process.

[0055] After an electrochemical cell is assembled, its chemical structure is modified to prepare it for use as an energy storage element. This can be done by forcing a current from one electrode to another, thereby generating an electrical potential between the electrodes. This process generally involves a net positive supply of energy to the cell ("charging"), but the process also generally includes a period during which the net supply of energy becomes negative ("discharging"). Fabrication is considered complete after a programmed sequence of currents, typically dependent on cell voltage, temperature, stored or dissipated energy, and / or time, is applied to the cell. Fabrication of each cell typically takes a different amount of time, primarily due to variations in the manufacturing process of the cell's components.

[0056] The quality of the cells can be determined by inspection after the formation process is complete in step 112. The defect rate after cell formation can reach 20%, with only 80% of the formed cells being of high enough quality to proceed to aging and deployment. This is likely because a significant number of cells exhibit deviations during manufacturing, for example, in their temperature, terminal voltage, or other physical characteristics. If the deviations exceed a specified quality threshold, the manufacturing has failed. Defective cells are preferably removed from the manufacturing process as soon as possible and replaced with another cell to begin production. Embodiments herein use EPM to implement dynamic monitoring and control during the cell formation process to improve battery yield.

[0057] At 114, cells that have completed the formation process and passed cell quality testing are transferred to an aging tower to stabilize the cell's chemical composition. At step 116, the same measurement and control circuitry used for the formation process may be diverted for periodic cell quality testing during the aging process so that defective cells can be identified and addressed, and the cell fixtures may be diverted for new cells. Finally, at 118, the aged cells undergo end-of-line (EOL) cell quality testing before being released to the market.

[0058] Figure 2 - Computer System and Controller FIG. 2 is a system diagram illustrating a computer system 82 coupled to a controller 202, according to some embodiments. The controller can be coupled to the forming towers and / or aging towers via a wired or wireless connection and can be configured to receive information from the forming and / or aging towers during the cell manufacturing process and provide instructions to modify parameters of the manufacturing process. For example, the controller can receive information from a measurement and control circuit monitoring a particular battery cell in a battery cell fixture during cell formation, and in response to this information, the controller can construct an EPM, display the EPM on a display, and / or provide instructions to modify the manufacturing process for the particular battery cell or another battery cell. Additionally or alternatively, the controller can perform an analysis on the EPM and display the analysis along with the EPM on a display device, allowing a user to decide whether to modify the manufacturing process based on the displayed information. In some embodiments, the controller can execute from the computer system 82 (i.e., the controller can be part of a computer system rather than a separate device).

[0059] Advantageously, the information provided by the EPM during the manufacturing process allows a user to dynamically intervene in manufacturing, increasing overall yield and efficiency. For example, defective cells can be identified early in the manufacturing process (e.g., during the formation process or the aging process), the defective cells can be removed from the manufacturing process for repair or disposal, and the battery cell fixture containing the defective cells may be repurposed to manufacture new battery cells.

[0060] Figure 3 - Computer system block diagram FIG. 3 shows a simplified block diagram of computer system 82. As shown, computer system 82 may include a processor 302 coupled to random access memory (RAM) 304 and non-volatile memory 306 for implementing embodiments described herein. For example, the processor may execute program instructions stored in the non-volatile memory to control and / or receive information from cell formation and / or aging towers. Computer system 82 may further include an input device 312 (e.g., keyboard, mouse, touchpad) for receiving user input and a display device 310 for presenting output on a display. Computer 82 may further include an input / output (I / O) interface 308 coupled to controller 202 or directly to the cell tower to provide output / instructions for controlling cell formation and to receive input and / or information regarding individual cells.

[0061] Electrochemical process manifold for battery cell formation Embodiments herein construct an electrochemical process manifold (EPM) for electrochemical processes and systems (such as battery cells) during the cell formation process. The EPM is a detailed construct that includes state-space mapping for multiple variables related to the cell, such as current, voltage, temperature, and / or pressure.

[0062] As used herein, a "manifold" refers to a mathematical structure in an n-dimensional phase space, where each of the n dimensions corresponds to a cell's state variable (e.g., current, voltage, temperature, etc.). The EPM then encodes relevant information about the cell's state history with respect to the associated variables. For example, the EPM describes a phase space whose points represent the recorded state history of the cell's variables. Advantageously, the mathematical properties of the manifold can be leveraged to facilitate analysis of the EPM and diagnose the health of the cell. For example, the EPM can be used diagnostically to identify defective cells early in the formation process and can also be used to dynamically modify cell formation to further improve yield. Various properties of the EPM (e.g., curvature, area, metric quantities) can be quantified to diagnose various aspects of the cell. For example, to diagnose the health of a cell, one or more deviations from the EPM properties of a reference healthy cell can be measured and quantified.

[0063] Figure 4 - Flow diagram for building an electrochemical process manifold with controlled current 4 is a flow diagram illustrating a method for constructing an electrochemical process manifold (EPM) while controllably adjusting current through a battery cell during a cell formation process, according to some embodiments. The method illustrated in FIG. 4 may be used in conjunction with any computer system, battery cell, memory medium, or device illustrated in the figures above, including other devices.

[0064] In some embodiments, the described methods may be performed during a cell formation process for a battery cell. The cell may be any of various types of battery cells and may be made of materials including, but not limited to, lithium, sodium ion, lithium sulfur, lithium air, lithium oxygen, lithium metal, metal fluorides, carbon nanotubes, carbon nanowires, nickel cadmium (NiCd), nickel metal hydride (NiMH), lead acid, lithium cobalt oxide (LiCoO), lithium iron phosphate (LiFePO), lithium nickel manganese cobalt oxide (LiNiMnCoO), lithium manganese oxide (LiMnO), lithium titanate (LiTiO), or organic compounds.

[0065] In some embodiments, a computer system may include a processor and memory, and the memory may store program instructions executable by the processor to perform elements of the method described with reference to FIG. 4. In various embodiments, the processor may be a parallel multiprocessor system, a field programmable gate array (FPGA), or an application specific integrated circuit (ASIC). In various embodiments, the steps of the described method may be directed by a combination of a controller processor (e.g., controller 202 of FIG. 2) and one or more processors (e.g., processor 302) of computer system 82. In various embodiments, some of the illustrated method elements may be performed simultaneously, in a different order than illustrated, or omitted. Additional method elements may be performed as desired. As illustrated, the method may operate as follows.

[0066] At 402, the current through the cell is controllably adjusted to charge or discharge the cell. The cell may be charged or discharged as part of the cell formation process. The current may sweep from a minimum current value to a maximum current value for the cell at each charge state, during which the cell transitions from a fully discharged state to a fully charged state, or vice versa. In some embodiments, the cell may be charged and discharged using a cell formation setup such as that shown in FIG. 6, which includes switching circuitry for adjusting the current through the cell.

[0067] In some embodiments, the temperature of the cell and / or the pressure applied to the cell are controllably adjusted simultaneously with the controllable adjustment of the current through the cell. In some embodiments, the controllable adjustment of the current, temperature, and pressure is performed in an oscillatory manner using a single common frequency. As used herein, the set of controllably adjusted variables (which may include one or more of current, voltage, temperature, and pressure) is referred to as "EPM stimulus variables."

[0068] In some embodiments, the current through the cell is controllably adjusted as an oscillatory function (e.g., a sinusoidal function). Adjusting the current as an oscillatory function allows the phase angle of the current to be tracked, which can be stored as a data point along with the measurement data. In these embodiments, the oscillatory function can have a bias toward charging or discharging the cell, resulting in cycles of alternating charge and discharge phases with an overall bias toward charging or discharging. In some embodiments, the frequency of the oscillatory function can be adjusted every half cycle to create a bias toward charging or discharging. For example, for discharging, the frequency of the current waveform can be lower when the current is negative and higher when the current is positive, creating a bias toward discharging. An example of a waveform for controllably adjusting the current is shown in FIG. 7. In FIG. 7, the cell is being discharged, so the frequency of the half-sine wave when the current is negative is lower than the half-sine wave when the current is positive. In the illustrated example, the discharge frequency is 0.1 Hz and the charge frequency is 1.0 Hz. Note that for the 10th cycle, the current is set to zero for one cycle.

[0069] The frequency of the oscillatory function may be selected based on the spacing of subsequent time steps used to construct the EPM to measure different currents at the time steps during subsequent oscillation periods of the oscillatory function. In other words, the frequency of the current oscillation may be selected such that, during subsequent oscillation periods, the time steps occur at different points along the oscillating current (so that different currents are measured during each subsequent period). In some embodiments, this may be achieved by selecting the current oscillation period to be misaligned with the period between subsequent time steps.

[0070] In some embodiments, the oscillatory function is modified to obtain a constant current through the cell for at least one period of the oscillatory function to determine a battery equivalent circuit model for the cell. For example, measurements of the battery's initial transition toward open-circuit voltage over a range of states of charge may be used to predict the open-circuit voltage, which can be used to identify a battery equivalent circuit model for each state of charge. To this end, a counter may record the number of complete sine wave cycles, sineCycle. Every N cycles, the current can be set to zero for one cycle, and the cell voltage response is recorded. Figure 8 shows the current waveform of Figure 7, zoomed in on the response during the zero-current time on the 10th cycle. Note the exponential curve as the voltage drops, followed by a slow, approximately linear increase. This waveform can be used to identify a battery equivalent circuit model for each state of charge once the information is collected.

[0071] At 404, as the current is controllably adjusted, various measurements and calculations are made for each of a number of time steps, as described in more detail below. The set of variables (which may include one or more of current, voltage, temperature, and / or pressure) that are measured periodically for each time step are referred to herein as "EPM response variables."

[0072] The time steps may be separated by regular intervals, or the spacing between subsequent time steps may be random or pseudo-random according to a predetermined probability distribution. In some embodiments, the pattern for adjusting the distance between subsequent time steps and the current through the cell is selected to obtain a predetermined average distance in current, voltage, and voltage-time, respectively, between adjacent data points in the EPM.

[0073] At 406, at a particular time step, the voltage across the cell is measured.

[0074] In some embodiments, the voltage may be measured when the current crosses zero, referred to as Vcross. Vcross can be used to determine when the maximum or minimum state of charge is reached. Figure 9 shows Vcross measurements for various states of charge. Note that after the discharge cycle, Vcross is slightly lower. After the charge cycle, Vcross is slightly higher.

[0075] At 408, the measured voltage may be integrated over time to obtain a voltage-time value for a particular time step. The voltage-time may represent the integrated measured voltage from the start of the formation process to a particular time step.

[0076] In some embodiments, for each time step, a differentiation of the current with respect to time is performed to obtain a value for the rate of change of the current, and / or for a particular time step, a differentiation of the voltage with respect to time is performed to obtain a value for the rate of change of the voltage.

[0077] At 410, data points including voltage-time values, measured voltages, and current through the cell at each time step are stored in memory. In some embodiments, the current over time is also integrated with time to obtain a current-time value for each time step, and the data point for each time step may further include a current-time value. In some embodiments, a value for the rate of change of current and a value for the rate of change of voltage may further be stored in the data point for each time step. Generally, the stored data points include the EPM stimulus variable and the EPM response variable for each time step.

[0078] In some embodiments, the temperature of the cell is measured at each time step and the temperature is integrated over time to obtain a temperature-time value. In these embodiments, the temperature and temperature-time values ​​may be further stored in a data point for each time step.

[0079] In some embodiments, for each time step, the pressure applied to the cell is measured and this pressure is further integrated over time to obtain a pressure-time value, in these embodiments, the pressure and pressure-time may be further stored in a data point for each time step.

[0080] In some embodiments, the measured voltage and current through the cell (as well as other quantities, such as temperature and pressure, in at least some embodiments) are stored in data points as complex values ​​containing respective amplitude and phase information for the voltage and current.

[0081] At 412, the data points are mapped to an electrochemical process manifold (EPM). An example of an EPM is shown in FIG. 10. The EPM may be a tensor quantity that includes, for each time step, multiple variables for that time step, including, among other possibilities, one or more of: current through the cell; voltage across the cell; integrated current-time and / or voltage-time; rate of change of current and / or voltage; temperature; pressure; temperature-time; and / or pressure-time. The EPM may map the data points to a common state-space matrix, with each address representing the same state location (i.e., current = 1 A + / - 0.01 A, charge = 1000 mAh + / - 10 mAh). Advantageously, because the EPM is constructed as a mathematical manifold, analysis may be performed on the EPM to characterize it. For example, properties of the EPM may be quantitatively analyzed to characterize and / or classify various aspects of the cell from which the EPM is constructed.

[0082] In some embodiments, a three-dimensional plot of the EPM is displayed on a display. Advantageously, visual observation of the EPM allows a skilled technician to effectively diagnose problems that may arise during a charge or discharge cycle.

[0083] In some embodiments, EPMs generated from preliminary cell formation data can be used to identify cell failure modes. The EPMs can enable early identification of good and bad cells during the formation process. Diagnostic and / or corrective instructions can be provided based on the EPMs to mitigate or eliminate failure modes. In some embodiments, EPMs can be determined individually for each of two bad / defective cells, which can then be compared to determine whether they have the same state-space dynamics and, therefore, whether they have one or more different failure modes. For example, variables described in EPMs can be mapped to a quantifiable structure of a manifold, so that the relationships and dynamics between variables can be quantified and compared between EPMs of different cells. As an example, how current varies as a joint function of voltage and temperature can be quantified, and specific feature dependencies can be identified as potential failure modes for a cell or as a healthy cell.

[0084] In some embodiments, patterns may be identified in the EPM to correspond to specific failure modes of the formation process. In some embodiments, the cell formation process may be dynamically altered based on the EPM to improve formation performance. Dynamic feedback may be implemented between developing the EPM for the cell during formation and providing feedback to alter the formation process to improve formation.

[0085] In some embodiments, the EPM is provided to a processor (or set of processors) that executes a machine learning algorithm. The machine learning algorithm may be pre-trained to analyze the EPM to provide various types of predictive, diagnostic, or other information regarding the cell formation process. For example, based at least in part on the EPM, the machine learning algorithm may determine, among other possibilities, information that assesses the quality of the cell, predicts the coulombic efficiency of the cell, and / or predicts one or more quality indicators of the cell after the cell formation process is complete.

[0086] In these embodiments, the machine learning algorithm may generate instructions based on the EPM to modify the cell's formation process to improve the cell's quality index.

[0087] In some embodiments, the EPM may be provided to a machine learning algorithm along with the partially formed data of the second cell. In these embodiments, the machine learning algorithm may determine a quality indicator of the second cell using the EPM and the partially formed data of the second cell.

[0088] At 414, the EPM is stored in a non-transitory computer-readable memory medium.

[0089] Figure 5 - Flow diagram for building an electrochemical process manifold with controlled voltage FIG. 5 is a flow diagram illustrating a method for constructing an electrochemical process manifold (EPM) while controllably adjusting the voltage across battery cells during a cell formation process, according to some embodiments. The method illustrated in FIG. 5 may be used in conjunction with any computer system, battery cell, memory medium, or device illustrated in the above figures, including other devices. The method illustrated in FIG. 5 is similar in some respects to the method illustrated in FIG. 4, in that in FIG. 5 the voltage is controllably adjusted and the current is periodically measured, whereas in FIG. 4 the current is controllably adjusted and the voltage is periodically measured. It should be noted that various aspects described in FIG. 4 may be equally applicable to the method illustrated in FIG. 5, as appropriate.

[0090] Additional technical explanation The following numbered paragraphs describe additional aspects of the described embodiments.

[0091] While embodiments herein are described in the context of charging and discharging battery cells to generate an electrochemical process manifold (EPM), it is within the scope of this disclosure to generate EPMs for any of a wider variety of electrochemical processes, and the described embodiments are not limited to battery cells. For example, any material or device undergoing an electrochemical process may be controllably exposed to one or more of current, voltage, temperature, or pressure changes, and one or more of the variables may be measured during this exposure, and these data points may be mapped to an EPM.

[0092] In various embodiments, either the current can be directly controlled (and the voltage periodically measured) or the voltage can be directly controlled (and the current periodically measured). In some embodiments, in a "current control mode," the temperature and pressure can be controlled in addition to controlling the current, so that the voltage is the dependent variable. Similarly, in some embodiments, in a "voltage control mode," the temperature and pressure can be controlled in addition to controlling the voltage and current, so that the current is the dependent variable. However, in some embodiments, a satisfactory but less informative EPM may be obtained with less effort if the temperature and pressure are not controlled and / or measured. In some embodiments, the temperature and pressure are controlled to oscillate at the same frequency as the current in a current control mode, or at the same frequency as the voltage in a voltage control mode. Advantageously, this allows for easier calculation of the phase relationship between the variables, yielding more information about the electrochemical process.

[0093] In some embodiments, the phase angle of the voltage is calculated relative to the phase angle of the controlled current and other variables. This is a coordinate transformation from the time domain to a rotating coordinate system aligned with other signals (e.g., current phasors). Each sampled value in the time domain (i.e., voltage, temperature, pressure) may be described by its amplitude and its phase angle relative to other variables. This phase angle relationship provides valuable information about the electrochemical process and thus helps build a more information-rich EPM. As an example, oscillatory fluctuations in temperature produce oscillatory voltage responses, and the nature of the voltage response contains information about the ongoing electrochemical process. To keep the phase angle calculation simple, the cell temperature may be varied at the same frequency as the electrical control variable (current in the case of current control or voltage in the case of voltage control). Various methods may be used to calculate the relative phase angle and control the temperature phase angle. To include phase information in concise mathematical expressions, each transformation variable can be represented by a vector, e.g., a complex or high-dimensional vector in the EPM subspace (i.e., for each location on the EPM mesh grid, calculate the component of voltage parallel to temperature, the component of voltage orthogonal to temperature, the component of voltage parallel to current, the component of voltage orthogonal to current, etc.). Mathematically, the time-domain data is mapped to an electrochemical process manifold because the manifold uniquely defines mathematical properties that facilitate interpretation and analysis.

[0094] In various embodiments, different processes are implemented to map time-series data points (i.e., a series of data points each including a timestamp, a current value, a voltage value, a current-time value, a voltage-time value, etc.) to the EPM. For example, in some embodiments, a conventional method is used to identify the nearest grid point on an N-dimensional EPM mesh grid for each time-domain sampled data set (where "set" refers to simultaneously sampled voltage, voltage_time, current, current_time, etc.) and perform data aggregation to update the mesh grid value at that location using the average value of all samples nearest to the mesh grid location in N-dimensional space. This is a coordinate transformation to a discrete manifold using averaging of time-domain data. Doing this is a form of data compression: the value for each location in the discrete manifold is the average of all time-domain samples in the range. Therefore, there is the option to discard the time-series data and store only the dense manifold values. An ideal EPM scanner algorithm would ensure that at least S samples are collected for each location in the EPM mesh grid, where S≧1.

[0095] In other embodiments, machine learning methods can be used to map time-series data points to EPMs. Based on prior knowledge of many EPM mesh grids for a complete electrochemical process, a mesh grid that is most likely to explain one or more sets of sampled data in the time domain can be identified, even given optionally incomplete time-series data. This has the desirable properties of traditional methods such as coordinate transformation and data compression, but adds important additional benefits, such as 1) the ability to perform intelligent nonlinear interpolation between unsampled data points in the EPM mesh grid when there is a priori knowledge of many EPMs, and 2) the ability to predict the EPM of an entire electrochemical process before the process is complete. In this case, the level of confidence in the EPM prediction increases over time, reaching 100 percent upon completion of the electrochemical process.

[0096] Additional Embodiments Additional embodiments are described in the following paragraphs.

[0097] In some embodiments, a method for performing monitored charging or discharging of a cell is described. The method may include controllably adjusting a voltage across a cell to charge or discharge the cell. Concurrently with the voltage being controllably adjusted, currents through the cell may be measured at each time step of a plurality of time steps, and the measured currents may be integrated over time to obtain current-time values ​​for each time step. Data points may be stored, including current-time values, measured currents, and voltages across the cell at each time step. The data points may be mapped to an electrochemical process manifold (EPM). The EPM may be stored in a non-transitory computer-readable memory medium.

[0098] In some embodiments, the method further comprises integrating the voltage over time at each time step of the plurality of time steps to obtain a respective voltage-time value; Each data point further includes a respective voltage-time value.

[0099] In some embodiments, the method further includes measuring a respective temperature of the cell at each time step of the plurality of time steps and integrating the temperature over time to obtain a respective temperature-time value. In these embodiments, each data point may further include a respective temperature and a respective temperature-time value.

[0100] In some embodiments, the method further includes measuring a respective pressure applied to the cell at each time step of the plurality of time steps and integrating the pressure over time to obtain a respective pressure-time value, In these embodiments, each data point may further include a respective pressure and a respective pressure-time value.

[0101] In some embodiments, the method further comprises displaying a three-dimensional plot of the EPM on a display.

[0102] In some embodiments, the method further includes providing the EPM to at least one processor that executes the machine learning algorithm, and receiving, from the at least one processor, a quality assessment of the cell, the quality assessment being determined at least in part based on the EPM.

[0103] In some embodiments, the method further includes providing the EPM to at least one processor that executes a machine learning algorithm, and receiving from the processor a prediction of the coulombic efficiency of the cell, the prediction being determined at least in part based on the EPM.

[0104] In some embodiments, the voltage across the cell is controllably adjusted as an oscillatory function, and the frequency of the sinusoidal oscillatory function is selected based at least in part on the spacing of multiple time steps to measure different voltages at time steps during subsequent oscillation periods of the oscillatory function.

[0105] In some embodiments, the oscillatory function has a bias towards charging or discharging the cell.

[0106] In some embodiments, the method further includes modifying the oscillatory function to obtain a constant voltage across the cell for at least one period of the oscillatory function to determine a battery equivalent circuit model of the cell.

[0107] In some embodiments, the method further includes providing the EPM to at least one processor running a machine learning algorithm, and upon completion of the formation process, receiving from the at least one processor instructions to modify the formation process to improve a quality index of the cell, the instructions being determined by the machine learning algorithm based at least in part on the EPM.

[0108] In some embodiments, the method further includes providing the EPM to at least one processor that executes a machine learning algorithm, and receiving information from the at least one processor that predicts one or more quality indicators of the cell after performing the formation process on the cell.

[0109] In some embodiments, the method further includes providing the EPM to at least one processor that executes a machine learning algorithm; providing partially formed data of the second cell to the at least one processor; and determining, by the at least one processor, a quality indicator of the second cell based, at least in part, on the EPM and the partially formed data of the second cell.

[0110] In some embodiments, the method further includes selecting a distance between subsequent time steps of the plurality of time steps and a pattern for adjusting the voltage across the cells to obtain a respective predetermined average distance in each of the current, voltage, and voltage-time between adjacent data points in the EPM.

[0111] In some embodiments, the cell is a battery cell made from one of lithium, sodium ion, lithium sulfur, lithium air, lithium oxygen, lithium metal, metal fluoride, carbon nanotubes, carbon nanowires, nickel cadmium (NiCd), nickel metal hydride (NiMH), lead acid, lithium cobalt oxide (LiCoO), lithium iron phosphate (LiFePO), lithium nickel manganese cobalt oxide (LiNiMnCoO), lithium manganese oxide (LiMnO), lithium titanate (LiTiO), or an organic compound.

[0112] In some embodiments, the voltage and current are stored in the data points as respective complex values ​​containing respective amplitude and phase information for the voltage and current.

[0113] In some embodiments, the method further includes, at each time step of the plurality of time steps, differentiating the current with respect to time to obtain a respective current rate of change value and differentiating the voltage with respect to time to obtain a respective voltage rate of change value, In these embodiments, each data point further includes each of the current rate of change value and the voltage rate of change value.

[0114] In some embodiments, the method further comprises the step of controllably adjusting the temperature of the cell and the pressure applied to the cell simultaneously with the step of controllably adjusting the voltage across the cell as described above.

[0115] In some embodiments, the controllable adjustment of voltage, temperature, and pressure is performed in an oscillatory manner using a single common frequency.

[0116] In some embodiments, the described methods may be performed by a standard computer processor coupled to a memory. Alternatively, in some embodiments, programmable hardware elements may be used to perform the described methods. Programmable hardware elements may include various hardware devices including multiple programmable function blocks connected via programmable interconnects. Examples include FPGAs (field programmable gate arrays), PLDs (programmable logic devices), FPOAs (field programmable object arrays), and CPLDs (complex PLDs). Programmable function blocks may range from fine-grained (combinational logic or lookup tables) to coarse-grained (arithmetic logic units, graphics processing units (GPUs), or processor cores). Programmable hardware elements may also be referred to as "reconfigurable logic." Alternatively, integrated circuits including dedicated hardware components, such as application-specific integrated circuits (ASICs), may be used to perform the described method steps.

[0117] Although the foregoing embodiments have been described in great detail, many variations and modifications will become apparent to those skilled in the art once the foregoing disclosure is fully understood, and it is intended that the following claims be interpreted to embrace all such variations and modifications.

Claims

1. 1. A method for supervised charging or discharging of a cell, comprising: controllably adjusting a current through the cell to charge or discharge the cell; At each time step of a plurality of time steps in which the current is controllably adjusted, measuring each voltage across the cells; integrating the measured voltage over time to obtain a respective voltage-time value for each of the time steps; storing each data point including each of the voltage-time values, each of the measured voltages, and the current through the cell at each of the time steps; mapping the plurality of data points to an electrochemical process manifold (EPM); and storing the EPM in a non-transitory computer-readable memory medium.

2. At each time step of the plurality of time steps, integrating the current over time to obtain a respective current-time value, wherein each of the data points further comprises the respective current-time value. The method of claim 1.

3. At each time step of the plurality of time steps, measuring the temperature of each of the cells; and integrating the temperature over time to obtain each temperature-time value; each said data point further comprising said respective temperature and said respective temperature-time value; The method of claim 1.

4. At each time step of the plurality of time steps, measuring each pressure applied to the cell; and integrating the pressure over time to obtain each pressure-time value; each said data point further comprising said respective pressure and said respective pressure-time value; The method of claim 1.

5. further comprising the step of displaying a three-dimensional plot of the EPM on a display. The method of claim 1.

6. providing the EPM to at least one processor that executes a machine learning algorithm; and receiving from the at least one processor a quality assessment of the cell determined based at least in part on the EPM. The method of claim 1.

7. providing the EPM to at least one processor that executes a machine learning algorithm; and receiving from the at least one processor a prediction of a coulombic efficiency of the cell determined at least in part based on the EPM. The method of claim 1.

8. the current through the cell is controllably adjusted as an oscillatory function; a frequency of the oscillatory function is selected based at least in part on the spacing of the plurality of time steps to measure different currents at the time steps during subsequent oscillation periods of the oscillatory function; The method of claim 1.

9. the oscillatory function includes a bias for charging or discharging the cell; The method of claim 8.

10. further comprising modifying the oscillatory function to obtain a constant current through the cell during at least one period of the oscillatory function to determine a battery equivalent circuit model of the cell. The method of claim 8.

11. providing the EPM to at least one processor that executes a machine learning algorithm; and upon completion of the formation process, receiving from the at least one processor instructions to modify the formation process to improve a quality metric of the cell, the instructions being determined by the machine learning algorithm based at least in part on the EPM. The method of claim 1.

12. providing the EPM to at least one processor that executes a machine learning algorithm; and receiving, after performing a formation process in the cell, information from the at least one processor predicting one or more quality indicators of the cell. The method of claim 1.

13. providing the EPM to at least one processor that executes a machine learning algorithm; providing the at least one processor with partially formed data for a second cell; and determining, by the at least one processor, a quality indicator for the second cell based, at least in part, on the EPM and the partially formed data for the second cell. The method of claim 1.

14. selecting a distance between subsequent time steps of the plurality of time steps and a pattern for adjusting the current through the cell to obtain a respective predetermined average distance in each of current, voltage, and voltage-time between adjacent data points in the EPM; The method of claim 1.

15. The cell lithium, sodium ions, lithium sulfur, Lithium Air, Lithium oxygen, lithium metal, metal fluorides, carbon nanotubes, carbon nanowires, Nickel cadmium, (NiCd), Nickel-metal hydride (NiMH), lead acid, Lithium cobalt oxide (LiCoO), lithium iron phosphate (LiFePO4), Lithium nickel manganese cobalt oxide (LiNiMnCoO2), Lithium manganese oxide (LiMn2O4), Lithium titanate (Li2TiO3), or organic compound 10. The method of claim 1, wherein the battery cell comprises one of:

16. the measured voltage and current through the cell are stored in the data points as respective complex values ​​containing respective amplitude and phase information for the voltage and current; The method of claim 1.

17. At each time step of the plurality of time steps, differentiating the current with respect to time to obtain respective current rate-of-change values; differentiating the voltage with respect to time to obtain respective voltage change rate values; each said data point further comprising said respective current rate of change value and voltage rate of change value; The method of claim 1.

18. and controllably adjusting a temperature of the cell and a pressure applied to the cell simultaneously with the step of controllably adjusting the current through the cell; wherein the steps of controllably adjusting the current, temperature, and pressure are performed in an oscillatory manner using a single common frequency; The method of claim 1.

19. When executed by one or more processors, a cell formation device controllably adjusting current through the cell to charge or discharge said cell; At each time step of a plurality of time steps in which the current is controllably adjusted, measuring each voltage across the cells; integrating the measured voltage over time to obtain a respective voltage-time value for each of the time steps; storing each data point including each of the voltage-time values, each of the measured voltages, and each of the currents through the cell at each of the time steps; mapping the plurality of data points to an electrochemical process manifold (EPM); storing the EPM in a non-transitory computer-readable memory medium; A non-transitory computer-readable memory medium that stores program instructions.

20. a non-transitory computer-readable memory medium; one or more processors coupled to the memory medium; and circuitry coupled to the one or more processors and configured to interact with cells, controllably adjusting the current through the cell to charge or discharge the cell; At each time step of a plurality of time steps in which the current is controllably adjusted, measuring each voltage across the cells; integrating the measured voltage over time to obtain a respective voltage-time value for each of the time steps; storing each data point including each of the voltage-time values, each of the measured voltages, and each of the currents through the cell at each of the time steps; mapping the plurality of data points to an electrochemical process manifold (EPM); An apparatus configured to store the EPM in a non-transitory computer-readable memory medium.

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