Dynamic control and performance evaluation / optimization of secondary battery cell finish machining (formation / aging / sorting / grading) using simultaneous online electrochemical methods and closed loop process control

Abstract

Control, evaluation and optimization techniques for the manufacture of secondary electrochemical devices to improve the quality, yield and safety of the produced cells and facilitate the finish machining (formation / aging / sorting / grading) process. A system for dynamically controlling and optimizing a secondary battery finishing process includes a closed-loop process control module configured to process real-time online manufacturing data derived from at least one of electrochemical impedance spectroscopy (EIS), self-discharge analysis (SDA), ampere or potential battery measurements. The formation time of the battery cell can be shortened from several days in the prior art to less than 24 hours, and the aging time can be shortened from 2-3 weeks to less than 1 hour. The control module provides real-time feedback to the pre-operation / material for confirmation, refinement, correction, and / or identification or isolation of better / poorer performance characteristics. The control module also provides feed-forward information that may indicate an identified aspect of a deviation of performance from the specification.

Description

Technical Field

[0001] The present invention relates generally to manufacturing electrochemical cells, and more particularly to control, evaluation and optimization techniques to improve the quality, yield and safety of secondary batteries, such as lithium-ion cells, during the finishing process. Background Art

[0002] Lithium-ion cells are a type of secondary battery and contain four main components: a positive electrode (cathode), a negative electrode (anode), a separator placed between the electrodes to prevent contact and short circuits, and an electrolyte. Examples of cathode active materials may include, but are not limited to, mixed metal oxides, metal phosphates, or related materials. Examples of anode materials may include, but are not limited to, graphite, silicon, or a composite thereof. The electrolyte provides the transport of ions and may be a liquid, solid, or liquefied gas. Battery manufacturing begins with the manufacture of large sheets of double-sided coated anode copper substrates and double-sided coated cathode aluminum substrates. Electrodes are manufactured in a continuous winding process, in which premixed anode or cathode materials are coated onto a metal substrate sheet used as a current collector. The electrode sheet is cut into double-sided coated metal substrates of appropriate size.

[0003] There are two main methods of building a single cell. One is to wind the electrodes and separator into a "roll core", and the other is to combine discrete electrode sheets with separators in a z-folded or stacked manner between each electrode. Cylindrical and some prismatic cells are wound on a rotating machine, and the anode and cathode electrode rolls and two separator rolls are fed into the rotating machine. Pouch cells and some prismatic cells use a robotic arm to alternate the stack while the separator is unrolled from the top to allow the anode and cathode stacks to be interleaved by the rotation of the separator.

[0004] Lithium-ion cells are assembled in their uncharged state. The first charge or formation of the cell is critical to the expected cycle life and energy capacity. This involves multiple stages, where the rate and duration of each step and the current / voltage limits are designed to form a metastable passivation layer on the anode, which is called the solid electrolyte interface (SEI) layer. The formation of the SEI layer consumes some of the lithium available in the cell and is a product of electrolyte decomposition. Similarly, a cathode electrolyte interface (CEI) is also formed, which provides uniform passivation to the positive electrode. The CEI layer provides a path for maintaining ion transport while inhibiting undesirable side reactions between the positive electrode particles and the electrolyte. However, for the anode SEI, the formation of a too thin SEI layer and / or an uneven layer can allow electrolyte ions to flow to the anode material, thereby increasing the risk of lithium plating and / or lithium dendrite growth and reducing the life cycle of the cell. Producing a suitable SEI layer thickness is one of the key process parameters in the cell production process, more specifically the cell finishing area. Cell finishing operations also include degassing (which is a result of the formation process) and cell aging (which screens cells with unacceptable self-discharge levels).

[0005] The formation and finishing processes are isolated from the rest of the production process because of the potential for fire when a faulty cell is charged for the first time, which can lead to rapid cell failure, also known as "thermal runaway." Due to the long duration required to perform the formation and aging processes, which are often three weeks or more, the process typically occupies the largest area in the factory, represents a large amount of work-in-process inventory, and consumes approximately 40% of the capital expenditure required for major factory projects. Currently, the formation and aging of lithium-ion cells follow a static approach that is not adjusted based on real-time observations during either process.

[0006] Specifically, finishing includes formation functions for charge / discharge to "form" the solid electrode / electrolyte interface SEI of the anode and CEI cathode. This is a very long and critical process that greatly affects the length of the battery cell life. This can take at least 24 to 48 hours and requires a lot of space in racking, power electronics, energy and work-in-progress inventory. The process of aging the battery cells is even more time-consuming, taking 2 to 3 weeks. This also requires a considerable footprint to place and store the cells. Determining ΔOCV or voltage drop is a common test to determine the quality of the cell and the final grading of the cell. The main drawback of this approach is that delays may result in the production of a large number of unqualified batteries without timely quality feedback to correct, resulting in the accumulation of waste and / or suboptimal products with reduced value. Obviously, this conventional approach hinders the yield of the cell and hinders the optimization of lithium-ion cell performance under working conditions. Summary of the invention

[0007] The present invention is based in part on the development of a method for dynamic performance evaluation and control of secondary battery cell finishing, which includes formation, aging, sorting and grading steps in battery production. The method utilizes simultaneous online multi-frequency rapid response electrochemical impedance spectroscopy (EIS) and closed-loop process control, together with real-time data analysis, for battery cell finishing processes. The method reduces time, capital expenditure, operating expenses, and increases the output and quality of battery cells. In addition, the present invention allows rapid performance feedback on early operations for confirmation, refinement and / or correction. The present invention is applicable to any secondary battery type that undergoes a formation / aging process. Although the present invention will be illustrated in the production of lithium-ion battery cells, it should be understood that the present invention is also applicable to, for example, sodium-ion batteries and solid-state batteries.

[0008] The present invention solves the high-yield, high-quality needs of large-scale batch production facilities. The use of electrochemical techniques such as EIS during formation and / or aging provides new capabilities in the lithium-ion battery production industry. This ability determines the battery cell ohms, surface film (SEI / CEI), and charge transfer resistance to ensure the highest quality "beginning of life" level. Dynamic closed-loop control enables rapid identification of quality defects for upstream adjustments and corrections, thereby minimizing downtime and waste waste. For example, "bad cells" can be identified early in the formation process to avoid aging. Advanced charge-discharge algorithms are used to optimize batteries and intelligently charge / discharge batteries during the formation process, and to ensure the safety of factories and personnel.

[0009] Compared with conventional systems, the present invention reduces the area requirement for formation / aging and equipment and funds and operating costs. Specifically, the present invention can be used to significantly reduce the formation time. For example, formation can be shortened to less than 24 hours from a few days of prior art, and aging can be shortened to less than 1 hour from 2 to 3 weeks of prior art.

[0010] In one aspect, the present invention relates to a system for dynamically controlling and optimizing a secondary battery cell finishing process, the system comprising a closed-loop process control module configured to manage or process real-time online manufacturing data and determine the charging and discharging protocol of the lithium-ion battery during formation, and determine the cell performance classification of the lithium-ion battery during aging. Online data is derived from electrochemical impedance spectroscopy (EIS), self-discharge analysis (SDA), amperometric and / or potentiometric measurements. Process parameters monitored by the module include, for example, ohmic resistance R Ω , Charge transfer resistance R ct , leakage current I leak , open circuit voltage (OCV) and / or voltage drop (ΔV).

[0011] In one embodiment, the closed-loop functionality of the control module enables online real-time process parameters to be compared with a set of preselected values ​​and / or computerized supervisory control systems. Based on the deviation of the online value from the set value, the control module instructs the EIS measurement system and / or the SDA measurement system to execute a set of preconfigured charge / discharge protocols to make the measured value closer to the selected target value. Based on the deviation derived from the feedback data, the control module can execute, terminate or implement an alternating charge / discharge program. This feature of closed-loop feedback control enables optimization of the time spent in the formation and / or aging process, which is impossible in traditional offline formation and aging stations.

[0012] In another aspect, the present invention relates to a system for feedback warning and / or control of a secondary battery cell finishing process, the system comprising a closed-loop process control module configured to manage or process real-time online manufacturing data from a charge / discharge function, an EIS measurement, an SDA measurement, an amperometric measurement system, and / or a potentiometric measurement system to identify and quantify performance deviations from specifications, and to identify deviations from previous operations to determine their potential impact. Representative examples of monitored process parameters include, for example, current (I), voltage (V), ohmic resistance R Ω , Charge transfer resistance R ct , leakage current I leak , open circuit voltage (OCV) and voltage drop (ΔV), etc.

[0013] In another aspect, the present invention relates to a system for feedforward warning and / or control of a secondary battery cell finishing process, the system comprising a closed-loop process control module configured to manage or process real-time online manufacturing data from charge / discharge functions, EIS measurements, SDA measurements, amperometric and / or potentiometric measurement systems to identify and quantify performance deviations from a standard or specification, and to identify post-operation battery materials for similar properties to the standard or specification to determine potential impacts for laboratory analysis or isolation.

[0014] Performance deviations that can be characterized as better or worse than normal or standard acceptable performance for a battery can be evaluated through various techniques such as: (i) statistical analysis of process parameters, (ii) comparison of rates of change, (iii) application of parameter limits, (iv) data extraction (dQ / dV), (v) machine learning, and (vi) artificial intelligence. Historical data on material components used in the battery and process parameters used in manufacturing the battery are evaluated to determine their impact on performance deviations. Operating parameters in the battery production line, specifically in the formation, aging, sorting and grading steps, are continuously upgraded.

[0015] The closed-loop process control module can be configured to automatically adjust materials and process parameters to establish normal battery performance, and identify materials and process parameters that are harmful and subsequently subject to quality and / or safety checks. The control module can also be configured to identify beneficial materials and process parameters that improve battery performance. Finally, the control module can be configured to automatically trigger warnings and / or isolate materials for additional evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A system including a production line and a controller for producing lithium-ion batteries is shown;

[0017] Figure 2 It is a flow chart of the formation process;

[0018] Figure 3 is a flow chart of the aging process; and

[0019] Figure 4 A block diagram of a system for optimizing lithium-ion battery finishing is shown. DETAILED DESCRIPTION

[0020] Figure 1 A system 2 for manufacturing electrochemical cells and batteries is shown, which includes a production line 4 and a controller 6. The production line 4 is configured to perform operations in a manufacturing process. In a mixing station 8, separate anode and cathode slurries are usually prepared in batches. Anode slurries are prepared by mixing various anode components including, for example, graphite, a binder, and a conductive agent in a solvent. The source, batch, amount of each component, and the mixing parameters adopted, such as temperature and tank stirring speed, of each batch are stored in the memory of the controller 6. Similarly, cathode slurries are prepared by mixing various cathode components including, for example, lithium oxide, a binder, and a conductive agent in a solvent. Lithium oxides include, for example, lithium nickel manganese cobalt (NMC), lithium iron phosphate (LFP), lithium cobalt oxide (LCO), and lithium nickel cobalt alumina (NCA). The source, batch, amount of components, and mixing parameters of each batch are stored in the memory of the controller 6. In the case of using a solid electrolyte, an electrolyte slurry can be prepared by a mixing process. The material starting history, pedigree, amount of components, and mixing parameters of each batch are stored in the memory of the controller 6.

[0021] In the coating and drying station 10, the anode slurry and cathode slurry prepared in the mixing station are coated on the metal substrate to form an electrode. The anode slurry or cathode slurry is coated on both sides of the current collector continuously in a channel or intermittently in a sheet using a slot die coating head or other coating method. The wet coated foil is directly fed into a long drying oven to evaporate the solvent. The thickness and coating weight applied to the electrode coating are measured by optical, X-ray and / or beta-ray absorption metrology, and this feedback can be used to control the coating machine. The drying stage is one of the most energy-intensive steps in the battery cell production process. The drying process itself also imparts several key quality aspects to the electrode, such as uniform distribution of pores (porosity) due to the emptying of the solvent, avoiding hard surfaces and blistering, and using only the right amount of energy to achieve the desired drying effect. After coating, the coated foil undergoes a calendering process, in which they are compressed by a pair of rotating rollers in step 12. This process helps to adjust the final physical properties of the electrode (thickness, bonding, conductivity, density and porosity).

[0022] The operating parameters, conditions, quality aspects of the electrode coating and calendering process are monitored by various online sensors, and the data is stored in the controller 6. To ensure high quality lithium-ion batteries, it is critical to uniformly mix the active materials in the anode slurry and the cathode slurry. In addition, (i) there should be the same coating weight on both sides of the electrode, (ii) the top and bottom coatings are aligned, and (iii) the same thickness and density on both sides of the electrode, which affects the porosity and subsequent "wettability" during electrolyte filling. The electrode should be free of contamination or defects (such as holes and missing coatings), and the required load (mAh / cm 2 ) to meet the energy storage requirements of the battery cell. Specific materials, process parameters, deviations, etc. are stored in the controller 6.

[0023] After calendering, the finished electrode is cleaned and fed into a slitter to be cut into narrow strips and wound into "sub-rolls" at the slitting station 12. Vision systems can be used to ensure correct operation and / or detect non-standard inspections, and specific materials, process parameters, deviations, etc. are stored in the controller 6.

[0024] The web is then sent to a drying station 14 where a vacuum oven removes residual moisture and solvent.

[0025] In the separation station 16, the cell separator material is prepared for winding, or die-cut for cell stacking, or prepared for a z-folding method, depending on the cell format process. The separator material can also be calendered on a continuous moving sheet process to form a separator, or slurry cast, such as cast onto a substrate and cured as a separator. The specific material and process parameters are stored in the controller 6.

[0026] The battery is constructed in the stacking / winding station 18. Stacking is used to form pouch cells, and winding is used to form cylindrical and prismatic cells. Specific materials and process parameters are stored in the controller 6.

[0027] In the packaging station 20, the cells are enclosed in a protective container or housing. Specific materials and process parameters are stored in the controller 6.

[0028] In the filling station 22, liquid electrolyte is added to the battery. The electrolyte comprises a lithium solution containing solvents, additives and salts. The amount, volume and / or weight of the lithium salt solution added and the specific ratio of the components, supplier, date, batch are recorded in the controller 6.

[0029] In the formation station 24, the battery is subjected to a series of charge and discharge cycles to build solid electrolyte interface (SEI) and cathode electrolyte interface (CEI) protective layers on the anode and cathode, respectively. For the present invention, EIS is used to determine the electrochemical conditions of SEI and / or CEI characteristics. This is directly related to the in-situ performance of the battery cell, thereby providing dynamic online closed-loop process control. In addition to or instead of EIS measurements, amperometric measurements, potentiometric measurements and / or self-discharge analysis (SDA) measurements can be used for parameter analysis of dynamic responses. Representative process parameters monitored include, for example, ohmic resistance R Ω , Charge transfer resistance R ct , leakage current I leak , open circuit voltage (OCV) and voltage drop (ΔV). These methods are used to optimize the yield, life, quality and safety of battery cells.

[0030] Data collected from electrochemical measurements are interpreted through Nyquist plots, Bode plots, or other conventional techniques. Data interpretation provides closed-loop optimization of the formation process to obtain the fastest yield. In addition, trends can be determined to identify poor performing, substandard cells, or even higher performing cells. This can also determine grading / sorting. The interpretation provides traceability of previous processes such as mixing, electrode production (drying, calendering, etc.), cell formation (winding, stacking, welding, electrolyte filling), which will be identified as possible sources of defects in a feedback manner.

[0031] Additionally, performance deviations from specifications are identified and post-operational materials are identified for similar properties to determine potential impacts, which can be used for feed-forward warnings and / or control of the material.

[0032] The rapid response of the measurement to feedback / feedforward allows the identification of quality defects for upstream adjustments / corrections, thereby reducing downtime and scrap, thereby reducing the formation / aging footprint and equipment. The overall result is an integrated total manufacturing solution.

[0033] In the degassing and sealing station 26, the formation reaction produces various mixtures of hydrogen, carbon monoxide, carbon dioxide, hydrocarbons (methane, propane, etc.) and hydrofluorocarbons (HFCs), which are removed from the cell and then sealed.

[0034] In the aging station 28, the sealed cells are subjected to a regulated heating regime. For the present invention, self-discharge analysis is employed to measure the "leakage current", preferably in micro-amperes, for on-line process control. Specific process parameters are stored in the controller 6.

[0035] In the sorting station 30, the batteries are classified. The specific classification of batteries, materials, properties and parameters is stored in the controller 6.

[0036] In order to facilitate the transfer of batteries and cells between the formation station 24, the degassing and sealing station 26, the aging station 28 and the sorting station 30, the production line 4 ( Figure 1 ) may include automated storage and retrieval systems (AS / RS) and / or autonomous mobile robots (AMRs) or other methods of automating material movement. In this way, the production line can produce large quantities of batteries with minimal personnel.

[0037] Figure 2 An exemplary formation process is shown, wherein electrodes are produced in step 100 and electrochemical cells are assembled into batteries in step 102. The formation process is controlled by an algorithm 118. A plurality of batteries are positioned in a formation station, and the batteries are connected to a charging circuit configured to be connected to a plurality of batteries, where they are subjected to a DC resistance measurement 104. Batteries that fail are removed for quality investigation 106. And the batteries that pass undergo formation 108, wherein the batteries are charged 110 according to the protocol of the algorithm 118, are allowed to rest 112, and are tested by EIS 114. (Note that the rest step 112 is optional, as EIS can be performed in situ with the charging function.) EIS and cycle data analysis 116 are applied; batteries that fail will be discarded, while batteries that pass will continue the formation process according to the formation and optimization algorithm program 118. If the batteries are not charged, they proceed to step 110, where they are charged.

[0038] The cells that have passed the analysis step 116 and have been charged are then discharged in step 120 according to the protocol of the algorithm 118 and rest for a length of time n in step 122 before an EIS pulse 124 is applied. (Note that the rest step 122 is optional, as EIS can be performed in situ with the discharge function.) Another analysis protocol 126 removes defective cells that have not passed. Those cells that have passed the first time at this stage are returned to step 118 for additional formation. If necessary in step 128, some of the cells that have passed the second time can be subjected to additional charge / discharge cycles. If the cells are in acceptable conditions, they proceed to step 130, where they are charged to 100% state of charge for the last time to complete the formation 132 and are transferred to the cell aging 134 step.

[0039] Figure 3The aging process of a battery that has completed formation 200 is shown. An initial cell measurement is performed on the charged battery, where the battery undergoes one or more tests, such as, for example, EIS, SDA, amperometric and potentiometric analysis. The quality defects 204 of the batteries that failed are checked. The batteries that passed continue to the formation step 206, where they are stored for a specified length of time at a defined temperature in step 210. Thereafter, the battery undergoes a second cell measurement 212, and data analysis 216 identifies (i) defective batteries under investigation 204, (ii) batteries that meet specific quality specifications but require additional aging (conditionally passed), and (iii) batteries that pass, which proceed to classification 218. After classification, the refined batteries 220 are transported to inventory 222. The conditionally passed batteries undergo a formation / optimization algorithm 214, where they are tested to determine 208 whether they will continue another aging step 210 or will start again (reform).

[0040] Figure 4 A control module 300 is shown, which regulates the production line 4 ( Figure 1 ) functions. As used herein, the term "module" refers to any device used to facilitate communication and / or interaction between elements of a production line and to perform additional processes, tasks, and / or functions to support the operation of the production line, as described herein. In various embodiments, the control module 300 can be any hardware, software, firmware, electronic control component, processing logic, and / or processor device, either alone or in any combination. According to the embodiment, the control module 300 can be implemented or realized with the following items: a general-purpose processor (shared, dedicated, or group) controller, a microprocessor or microcontroller, and a memory that executes one or more software or firmware programs; a content addressable memory; a digital signal processor; an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA); any suitable programmable logic device; a combinational logic circuit, including discrete gates or transistor logic; discrete hardware components and memory devices; and / or any combination thereof designed to perform the functions described herein.

[0041] The control module may include a computer system including a processing unit 302, a memory 304, a removable storage device 312, and a non-removable storage device 314. Although the exemplary computing device is shown and described as a computer system, the computing device may take different forms in different embodiments. For example, the computing device may alternatively be a smart phone, a tablet computer, a smart watch, or other computing device. Devices such as smart phones, tablet computers, and smart watches are generally referred to as mobile devices. In addition, although various data storage elements are shown as part of the control module 300, the storage device may also or alternatively include a cloud-based storage device accessible via a network such as the Internet.

[0042] Memory 304 may include volatile memory 308 and non-volatile memory 310. The computer system may include, or have access to, a computing environment that includes, various computer-readable media, such as volatile memory 308 and non-volatile memory 310, removable storage 312, and non-removable storage 3144. Computer storage includes random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) and electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD ROM), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage, or other magnetic storage devices capable of storing computer-readable instructions for execution to perform the functions described herein.

[0043] The computer system may include or have access to a computing environment including an input 318, an output 320, and a communication interface 316. The output 320 may include a display device, such as a touch screen, which may also be used as an input device. The input 318 may include one or more of the following items: a touch screen, a touch pad, a mouse, a keyboard, a camera, one or more device-specific buttons, one or more sensors integrated in the control module 300 or connected to the control module via a wired or wireless data connection, and other input devices 318. The computer system may operate in a networked environment using a communication connection for connecting to one or more remote computers, such as a database server, including cloud-based servers and storage devices. The remote computer may include a personal computer (PC), a server, a router, a network PC, a peer device, or other common network nodes, etc. The communication connection may include a local area network (LAN), a wide area network (WAN), a cellular, WiFi, Bluetooth, or other network.

[0044] Computer readable instructions stored on a computer readable storage device may be executed by processing unit 302. A hard drive, a CD-ROM, and a RAM are some examples of articles of manufacture that include a non-transitory computer readable medium such as a storage device. The terms computer readable medium and storage device do not include carrier waves. For example, computer program 306 may be used to cause processing unit 302 to perform one or more methods of the present invention.

[0045] Although a single control module can control the entire production line 4 ( Figure 1), but it should be understood that each station of the production line can be equipped with a control module to specifically monitor and adjust the equipment associated with a specific station. For example, the data analysis module 322 is used to receive and process online data for analysis and visualization. The communication module 324 is used to transmit performance evaluation metrics and adjustment process parameters to a manufacturing execution system (MES) 326 or a distributed control system (DCS) 328 that can be located in a remote server. The MES or DCS can then guide the automated storage and retrieval system and / or autonomous mobile robots to manipulate batteries in the formation station, aging station, and sorting station. The MES or DCS can be incorporated into a computer system such as a "centralized operating console" or "integrated operating center" or equivalent, where data can be displayed in a human-machine interface (HMI). The communication module 324 can send online process information obtained from the formation and aging stations to a safety control system 330, which is an early battery fault detection mechanism. For example, it can provide early smoke or battery exhaust and / or heat detection, thermal imaging, electrolyte vapor detection, and related safety measures to prevent thermal runaway.

[0046] The foregoing describes the principles, preferred embodiments and modes of operation of the present invention. However, the present invention should not be construed as being limited to the specific embodiments discussed. On the contrary, the above embodiments should be considered as exemplary rather than restrictive, and it should be understood that variations may be made in these embodiments by those skilled in the art without departing from the scope of the present invention as defined by the following claims.

Claims

1. A system for dynamically controlling and optimizing a secondary battery cell finishing process, the system comprising a closed-loop process control module configured to process real-time online manufacturing data derived from at least one of electrochemical impedance spectroscopy (EIS), self-discharge analysis (SDA), amperometric or potentiometric battery measurements.

2. The system of claim 1, wherein the battery measurement comprises a process parameter selected from the group consisting of: ohmic resistance R Ω , Charge transfer resistance R ct , leakage current I leak , open circuit voltage (OCV), voltage drop (ΔV), and their combination.

3. A system according to claim 1, wherein the system includes an EIS measurement device operatively connected to a secondary battery and / or an SDA measurement device operatively connected to the secondary battery, wherein the closed-loop process control module is configured to compare real-time online process parameters with a set of selected process parameter values, and to direct the EIS measurement device and / or the SDA measurement device to perform a set of preconfigured charge / discharge protocols to bring the battery measurements closer to desired target values.

4. The system of claim 1 , wherein the system includes a battery charging and discharging device, and the closed-loop process control module is configured to: Receive and analyze feedback data, Determine the deviation from the desired target value, and Based on the deviation from the feedback, the battery charging and discharging device is instructed to execute, terminate or implement an alternating charging / discharging procedure.

5. The system of claim 1, wherein the closed-loop control module is operatively connected to a data analysis module configured to receive and process online manufacturing data for analysis and presentation in a visual format.

6. A system according to claim 5, wherein the system includes an EIS measurement device operatively connected to a secondary battery and / or an SDA measurement device operatively connected to a secondary battery, and wherein the data analysis module includes a processor configured to (i) receive measurement data from the EIS measurement device and / or the SDA measurement device, (ii) perform data processing and analysis using an algorithm and extract performance evaluation metrics, and present the metrics to a user interface.

7. The system of claim 1, wherein the system includes a communication module configured to transmit performance evaluation metrics and adjusted process parameters to a remote server, a manufacturing execution system (MES) and / or a distributed control system (DCS) for monitoring and analysis.

8. A system according to claim 7, wherein based on the performance evaluation metrics and adjusted process parameter inputs received from the communication module, the MES and / or DCS directs an automated storage and retrieval system (AS / RS) and / or an autonomous mobile robot (AMR) to transport individual battery cells between formation stations, aging stations and / or sorting stations.

9. A system for providing feedback warning and / or controlling a secondary battery cell finishing process, the system comprising a closed-loop process control module, the closed-loop process control module being configured to: (i) processing real-time online manufacturing data from charge / discharge functions, electrochemical impedance spectroscopy (EIS) measurements, self-discharge analysis measurements (SDA), amperometry measurements and / or potentiometry measurements, (ii) identify deviations in battery performance from specifications, and (iii) Identify battery manufacturing history operating conditions that potentially caused the battery performance to deviate from the specification.

10. A system for feedforward warning and / or control of a lithium-ion battery cell finishing process, the system comprising a closed-loop process control module, the closed-loop process control module being configured to: (i) processing real-time online manufacturing data from charge / discharge functions, electrochemical impedance spectroscopy (EIS) measurements, self-discharge analysis measurements (SDA), amperometry measurements and / or potentiometry measurements, and (ii) identify deviations in battery performance from specifications, and (iii) Identify post-operation materials with similar properties to those specified to determine potential impacts for laboratory analysis and / or quarantine.

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