Dynamic control and performance evaluation / optimization of secondary battery cell finishing (formation / aging / sorting / grading) using simultaneous in-line electrochemical methods and closed-loop process control.
Patent Information
- Application Number
- JP2026092157
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-07-06
- Filing Date
- 2026-06-01
- Publication Date
- 2026-09-08
Smart Images
Figure 2026143546000001_ABST
Abstract
Description
[Technical Field]
[0001] The present invention relates, in general, to the manufacture of electrochemical batteries, and more particularly to control, evaluation, and optimization techniques for improving the quality, throughput, and safety of secondary batteries such as lithium-ion cells in the finishing process. [Background technology]
[0002] A lithium-ion cell is a type of secondary battery that comprises 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 include, but are not limited to, mixed metal oxides, metal phosphates, or related materials. Examples of anode materials include, but are not limited to, graphite, silicon, or composites thereof. The electrolyte provides ion transport and may be liquid, solid, or liquefied gas. Battery manufacturing begins with the production of large sheets of double-sided coated anode copper substrates and double-sided coated cathode aluminum substrates. Electrodes are manufactured in a continuous roll-to-roll process in which pre-mixed anode or cathode material is coated onto sheets of metal substrates that function as current collectors. The electrode sheets are then cut into double-sided coated metal substrates of appropriate size.
[0003] There are two main methods for constructing individual cells. One is winding the cells onto a "jelly roll" of electrodes and separators, and the other is combining separate electrode sheets and separator films in a z-fold or lamination between each electrode. Cylindrical cells and some prism cells are wound onto a rotating machine supplied with two rolls: rolls of anode and cathode electrodes and separator film. Pouch cells and some prism cells are constructed using a robotic arm, alternating the anode and cathode laminations so that the separator film unfolds from above and intersects the stacks, which is completed by rotating the separator film.
[0004] Lithium-ion cells are assembled in an uncharged state. The initial charging or formation of the cell is critical to its expected cycle life and energy capacity. This involves multiple steps in which the rate and duration and current / voltage limits of each step are designed to form a metastable passivation layer called a solid electrolyte interface (SEI) layer on the anode. The formation of the SEI layer consumes some of the lithium from the available lithium in the cell and is a product of electrolyte decomposition. Similarly, a cathode electrolyte interface (CEI) develops, resulting in uniform passivation of the positive electrode. This CEI layer allows for the maintenance of ion transport pathways while suppressing undesirable side reactions between the positive electrode particles and the electrolyte. However, for the anode SEI, forming an SEI layer that is too thin and / or non-uniform allows electrolyte ions to flow into the anode material, increasing the risk of lithium plating and / or lithium dendritic growth, and reducing the cell's cycle life. Generating an appropriate SEI layer thickness is one of the critical process parameters in the cell production process, more specifically in the cell finishing area. Cell finishing also includes degassing, which is a result of the forming process, and cell aging, which involves sorting out cells that have unacceptable levels of self-discharge.
[0005] The forming and finishing processes are isolated from the rest of the production process because a fire could occur when a faulty cell is first charged, potentially resulting in rapid failure known as "thermal runaway." Because the forming and aging processes require a long period (often more than three weeks), these processes typically occupy the largest area in the plant, represent significant work in inventory, and consume approximately 40% of the capital expenditure required for major plant projects. Currently, lithium-ion cell forming and aging are carried out according to static recipes that are not adjusted during either process based on real-time observations.
[0006] Specifically, the finishing process includes the function of forming for charge / discharge to "form" the solid electrode / electrolyte interface SEI for the anode and CEI cathode. This is a long and critical process that significantly impacts the length of the cell life. It can take at least 24–48 hours and requires considerable space in racking, power electronics, energy, and in-process inventory. The process of aging the battery cells takes even longer, taking 2–3 weeks. This also requires considerable floor space to stage and store the cells. Determining ΔOCV, or voltage drop, is a common test for determining cell quality and final cell grading. The main drawback of this approach is that the delay means there is no timely quality feedback to correct, and a significant number of substandard batteries may be produced, resulting in an accumulation of scrap and / or suboptimal products with reduced value. As is obvious, this conventional methodology hinders cell throughput and impractically prevents the optimization of Li-ion cell performance. [Overview of the project]
[0007] This invention is partly based on the development of a method for dynamic performance evaluation and control of secondary battery cell finishing, encompassing the formation, aging, sorting, and grading steps in battery production. The method utilizes simultaneous, in-line, multi-frequency fast-response electrochemical impedance spectroscopy (EIS) and closed-loop process control, along with real-time data analysis, for the battery cell finishing process. This method reduces time, capital expenditure, and operational costs, and improves battery cell throughput and quality. In addition, the invention enables fast performance feedback to prior actions for verification, improvement, and / or correction. The invention is applicable to any secondary battery type undergoing a formation / aging process. While the invention is described in the context of lithium-ion battery cell production, it is understood that the invention is also applicable to, for example, sodium-ion batteries and solid-state batteries.
[0008] This invention addresses the high throughput and superior quality requirements of large-scale mass production facilities. The use of electrochemical technologies such as EIS in the formation and / or aging process provides a novel capability in the Li-ion battery production industry. This capability verifies the ohmic resistance, surface film (SEI / CEI), and charge transfer resistance of battery cells to ensure the highest quality "life start" level. Dynamic closed-loop control enables rapid recognition of quality defects for upstream adjustment and correction, minimizing downtime and scrap waste. For example, "defective cells" can be identified early during the formation process to prevent aging. Advanced charge / discharge algorithms are used to optimize the battery during the formation process, intelligently charging / discharging and ensuring plant and personnel safety.
[0009] This invention reduces the formation / aging floor space requirements, as well as equipment, capital, and operating costs, compared to conventional systems. Specifically, the invention dramatically reduces formation time. For example, formation, which currently takes several days with current technology, can be reduced to less than 24 hours, and aging, which currently takes 2-3 weeks with current technology, can be reduced to less than 1 hour.
[0010] In one embodiment, the present invention relates to a system for the dynamic control and optimization of a secondary battery cell finishing process, including a closed-loop process control module configured to manage or process real-time in-line manufacturing data, determine the charging and discharging protocols of lithium-ion batteries during formation, and determine the cell performance classification of lithium-ion batteries during aging. The in-line data is derived from electrochemical impedance spectroscopy (EIS), self-discharge analysis (SDA), current measurement, and / or potentiometric measurement. Process parameters monitored by the module include, for example, ohm resistance R Ω , charge transfer resistance R ct , leakage current I leakThese include open-circuit voltage (OCV) and / or voltage drop (ΔV).
[0011] In one embodiment, the closed-loop function of the control module allows for the comparison of inline real-time process parameters with a pre-selected set of values and / or a computerized monitoring and control system. Based on the deviation of the inline values from the setpoint, the control module instructs the EIS measurement system and / or SDA measurement system to execute a pre-configured set of charge / discharge protocols to bring the measured values closer to a selected target value. Based on the deviation derived from the feedback data, the control module can execute, terminate, or perform alternating charge / discharge procedures. This feature of closed-loop feedback control enables optimization of the time spent on the formation and / or aging process, which was not possible with conventional offline formation and aging stations.
[0012] In another aspect, the present invention relates to a system for feedback alerts and / or control of a secondary battery cell finishing process, including a closed-loop process control module configured to manage or process real-time in-line manufacturing data from charge / discharge functions, EIS measurements, SDA measurements, current measurement systems, and / or potentiometric measurement systems to identify and quantify performance deviations from a standard and to identify previous operational deviations to their potential contributions from that standard. Typical examples of process parameters to be monitored include, for example, current (I), voltage (V), and ohm resistance R. Ω、 Charge transfer resistance R ct , leakage current I leak Examples include open-circuit voltage (OCV) and voltage drop (ΔV).
[0013] In yet another aspect, the present invention relates to a system for feedforward alerting and / or control of a secondary battery cell finishing process, which includes a closed-loop process control module configured to manage or process real-time in-line manufacturing data from charge / discharge functions, EIS measurements, SDA measurements, current measurement systems, and / or potentiometric measurement systems to identify and quantify performance deviations from standards or benchmarks, and to identify post-operation battery materials with similar attributes for potential contributions from those standards or benchmarks for laboratory analysis or isolation.
[0014] Performance deviations, which can be characterized as being better or worse than normal or standard battery tolerances, can be evaluated by 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 of material components used in batteries and process parameters used in battery manufacturing are evaluated to determine their contribution to performance deviations. Operating parameters in battery manufacturing lines are constantly being upgraded, particularly in the forming, aging, sorting, and grading steps.
[0015] The closed-loop process control module may be configured to automatically adjust material and process parameters to establish normal battery performance and to identify material and process parameters that are hazardous and subsequently subject to quality and / or safety review. The control module may also be configured to identify beneficial material and process parameters that improve battery performance. Finally, the control module may be configured to automatically trigger alarms and / or isolate materials for further evaluation. [Brief explanation of the drawing]
[0016] [Figure 1] This shows a system including a manufacturing line and controller for producing lithium-ion batteries. [Figure 2] This is a flowchart of the formation process. [Figure 3] This is a flowchart of the aging process. [Figure 4] A block diagram of the system for optimizing lithium-ion battery finishing is shown. [Modes for carrying out the invention]
[0017] Figure 1 shows System 2, including a manufacturing line 4 and a controller 6, for fabricating electrochemical cells and batteries. Manufacturing line 4 is configured to perform operations in the fabrication process. At the mixing station 8, individual anode slurries and cathode slurries are typically prepared in batches. Anode slurries are prepared by mixing various anode components, such as graphite, binders, and conductors, in a solvent. The source, lot, amount of each component, and mixing parameters used for each batch, such as temperature and tank stirring speed, are stored in the memory of the controller 6. Similarly, cathode slurries are prepared by mixing various cathode components, such as lithium oxide, binders, and conductors, in a solvent. Examples of lithium oxides include lithium nickel manganese cobalt (NMC), lithium iron phosphate (LFP), lithium cobalt oxide (LCO), and lithium nickel cobalt alumina (NCA). The source, lot, component amounts, and mixing parameters for each batch are stored in the memory of the controller 6. When a solid electrolyte is used, the electrolyte slurry may be prepared by the mixing process. The material start history, system, component amounts, and mixing parameters for each batch are stored in the memory of the controller 6.
[0018] In the coating and drying station 10, the anode slurry and cathode slurry prepared in the mixing station are coated onto a metal substrate to form electrodes. The anode slurry or cathode slurry is coated on both sides of the current collector in a lane-like continuous or patch-like intermittent manner using a slot die coating head or other coating method. The wet coated foil is fed directly 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 spectroscopy, and this feedback can be used to control the coating machine. The drying stage is one of the most energy-intensive steps in the cell production process. The drying process itself also imparts several important quality aspects to the electrodes, such as a uniform distribution of pores (porosity) due to solvent removal, avoidance of hard surfaces and blistering, and the use of just the right amount of energy to achieve the desired drying. After coating, the coated foil undergoes a calendering process in step 12, where it is compressed by a pair of rotating rollers. This process helps to adjust the final physical properties of the electrodes (thickness, bonding, conductivity, density, and porosity).
[0019] The operating parameters, conditions, and quality characteristics of the electrode coating and calendering processes are monitored by various in-line sensors, and the data is stored in controller 6. To ensure high-quality Li-ion batteries, it is important that the active materials in the anode slurry and cathode slurry are uniformly mixed. In addition, (i) the same coating weight should be present on both sides of the electrode, (ii) the top and bottom coatings should be aligned, and (iii) the same thickness and density should be present on both sides of the electrode, which affects porosity and "wetness" during subsequent electrolyte filling. The electrodes must be free from contamination or defects (such as holes and missing coatings) and have the required load (mAh / cm³) to meet the cell energy storage requirements. 2 ) should be present. Specific materials, process parameters, deviations, etc., are stored in controller 6.
[0020] After calendering, the finished electrode is washed, fed into a slitting machine to be cut into narrow strips, and wound onto "daughter rolls" at slitting station 12. A vision system is used to ensure proper operation and / or detect non-standard detections, and relevant specific materials, process parameters, deviations, etc. are stored in controller 6.
[0021] The coil is then sent to drying station 14, where a vacuum oven removes residual moisture and solvent.
[0022] At separation station 16, cell separator material is prepared for winding, die-cut for cell stacking, or prepared for a Z-folding method depending on the cell formatting process. The separator material may also be calendered to form a separator film in a continuous moving sheet process, or may for example be slurry cast onto a substrate and cured as discrete units. Specific materials and process parameters are stored in controller 6.
[0023] At stacking / winding station 18, the battery is constructed. Stacking is used to form pouch cells, while winding is used to form cylindrical cells and prismatic cells. Specific materials and process parameters are stored in controller 6.
[0024] At packaging station 20, the battery is placed into a protective container or shell. Specific materials and process parameters are stored in controller 6.
[0025] At 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 added lithium salt solution, as well as the specific proportions of components, supplier, date, and batch are recorded in controller 6.
[0026] In the formation station 24, the battery undergoes a series of charge and discharge cycles to build a solid electrolyte interphase (SEI) and a cathode electrolyte interphase (CEI) protective layer on the anode and cathode, respectively. In the present invention, EIS is used to confirm the electrochemical state of SEI and / or CEI characteristics. This is directly related to the in-situ performance of the battery cell and provides dynamic in-line closed-loop process control. In addition to or instead of EIS measurement, amperometric measurement, potentiometric measurement, and / or self-discharge analysis (SDA) measurement can be used for parameter analysis of dynamic responses. Typical process parameters to be monitored include, for example, ohmic resistance R Ω、 charge transfer resistance R ct , leakage current I leak , open circuit voltage (OCV), voltage drop (ΔV), etc. These methods are used to optimize the throughput, service life, quality and safety of battery cells.
[0027] Data collected from electrochemical measurements are interpreted by Nyquist plots, Bode plots, or other conventional techniques. Data interpretation provides closed-loop optimization of the formation process for maximum throughput. Additionally, trends can be established to identify poorly performing cells and out-of-specification cells, or higher-performing cells. This can also establish grading / sorting. The interpretation provides traceability from preceding processes such as mixing, electrode production (drying, calendering, etc.), cell fabrication (winding, lamination, welding, electrolyte filling), and is identified in a feedback manner as the root cause of potential defects.
[0028] In addition, after identifying performance deviations from a reference, post-operation materials with similar attributes are identified for potential contributions that can be used in feedforward for material alerts and / or control.
[0029] The fast response from measurement to feedback / feedforward enables the recognition of quality defects for upstream adjustment / correction, reducing downtime and scrap, and thereby reducing the floor space and equipment required for forming / aging. The overall result is an integrated, comprehensive manufacturing solution.
[0030] In the degassing and sealing station 26, the formation reaction generates various mixtures of hydrogen, carbon monoxide, carbon dioxide, hydrocarbons (such as methane and propane), and hydrofluorocarbons (HFCs), which are removed from the cell and then sealed.
[0031] In the aging station 28, the sealed batteries undergo controlled heating. In this invention, self-discharge analysis is used to measure the "leakage current," preferably in microamperes, for inline process control. Specific process parameters are stored in the controller 6.
[0032] At sorting station 30, the batteries are graded. The grading, materials, performance, and parameters of a particular battery are stored in controller 6.
[0033] To facilitate the movement of batteries and cells between the forming 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 an automated storage and retrieval system (AS / RS) and / or an autonomous mobile robot (AMR) or other automated material handling method. In this way, the production line can accommodate a large number of batteries with minimal personnel.
[0034] Figure 2 shows an exemplary formation process in which electrodes are produced in step 100 and electrochemical cells are assembled into batteries in step 102. The formation process is controlled by algorithm 118. Multiple batteries are positioned at the formation station, connected to a charging circuit configured to connect to multiple batteries, and multiple batteries undergo DC resistance measurement 104. Failed batteries are removed for quality inspection 106. Passed batteries undergo formation (108), where the batteries are charged (110), paused (112), and tested by EIS (114) according to protocols from algorithm 118. (Note that the pause step 112 is optional, as EIS can be performed in situ using the charging function.) EIS and cycle data analysis 116 are applied. Failed batteries are rejected, and passed batteries continue the formation process according to the formation and optimization algorithm procedure 118. If a battery is not charged, the process proceeds to step 110, where the battery is charged.
[0035] Batteries that pass analysis step 116 and are charged are then discharged in step 120 according to the protocol from algorithm 118 and paused for a length of time n in step 122 before the EIS pulse 124 is applied. (Note that the pause step 122 is optional, as EIS can be performed in situ using the discharge function.) Another analysis protocol 126 removes any unsuccessful defective batteries. Batteries that initially pass at this stage are returned to step 118 for additional formation. Some batteries that pass a second time may receive additional charge / discharge cycles in step 128 as needed. If the batteries are in an acceptable state, they proceed to step 130, where they are finally charged to 100% to complete formation 132 and proceed to step cell aging 134.
[0036] Figure 3 shows the aging process of a battery that has completed formation 200. The charged battery undergoes an initial cell measurement in which the battery undergoes one or more tests, such as EIS, SDA, current measurement, and potentiometric measurement analysis. Failed batteries are inspected for quality defects 204. Those that pass proceed to the formation step 206 and, in step 210, are stored at a specified temperature for a specified length of time. The battery then undergoes a second cell measurement 212, and analysis of the data 216 identifies (i) defective batteries to be investigated 204, (ii) batteries that meet certain quality specifications but require additional aging (conditionally accepted), and (iii) accepted batteries, and accepted batteries proceed to grading 218. After grading, the completed batteries 220 are transported to inventory 222. Conditionally accepted batteries undergo the formation / optimization algorithm 214, where they are tested to determine whether to continue to another aging step 210 or start again (reformation) (208).
[0037] Figure 4 shows a control module 300 that adjusts the functionality of manufacturing line 4 (Figure 1). As used herein, the term “module” means any means for performing additional processes, tasks, and / or functions to facilitate communication and / or interaction between elements of a manufacturing line and to support the operation of the manufacturing line, as described herein. In various embodiments, the control module 300 may be any hardware, software, firmware, electronic control components, processing logic, and / or processor devices, individually or in any combination thereof. Depending on the embodiment, the control module 300 may be implemented or realized using a general-purpose processor (shared, dedicated, or group) controller, microprocessor, or microcontroller, and memory; associative memory; digital signal processor; application-specific integrated circuit (ASIC), field programmable gate array (FPGA); any suitable programmable logic device; combinational logic circuits including discrete gate or transistor logic; separate hardware components and memory devices; and / or any combination thereof, designed to perform the functions described herein.
[0038] The control module may comprise a computer system including a processing unit 302, memory 304, removable storage 312, and non-removable storage 314. Although an exemplary computing device is illustrated and described as a computer system, the computing device may take different forms in different embodiments. For example, the computing device may instead be a smartphone, tablet, smartwatch, or other computing device. Devices such as smartphones, tablets, and smartwatches are generally collectively referred to as mobile devices. Furthermore, although various data storage elements are illustrated as part of the control module 300, the storage may also, or alternatively, include cloud-based storage accessible via a network such as the Internet.
[0039] Memory 304 may include volatile memory 308 and non-volatile memory 310. A 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disk (DVD) or other optical disc storage, magnetic cassettes, magnetic tapes, magnetic disk storage, or other magnetic storage devices capable of storing computer-readable instructions for performing the functions described herein.
[0040] The computer system includes, or can access, 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 touchscreen, which can also function as an input device. The input 318 may include one or more of the following: a touchscreen, a touchpad, a mouse, a keyboard, a camera, one or more device-specific buttons, one or more sensors integrated within a control module 300 or coupled via a wired or wireless data connection, and other input devices 318. The computer system can operate in a networked environment using a communication connection to connect to one or more remote computers, such as a database server including cloud-based servers and storage. The remote computers may include personal computers (PCs), servers, routers, network PCs, peer devices, or other common network nodes. The communication connection may include a local area network (LAN), a wide area network (WAN), cellular, WiFi, Bluetooth®, or other networks.
[0041] Computer-readable instructions stored in a computer-readable storage device are executable by the processing unit 302. A hard drive, CD-ROM, and RAM are some examples of articles containing non-temporary computer-readable media such as storage devices. The terms computer-readable media and storage device do not include carrier waves. For example, a computer program 306 can be used to cause the processing unit 302 to perform one or more of the methods described herein.
[0042] While a single control module can control the entire manufacturing line 4 (Figure 1), it is understood that individual stations on the manufacturing line may have control modules to specifically monitor and adjust devices associated with that particular station. For example, a data analysis module 322 is used to receive and process inline data for analysis and visualization. A communication module 324 is used to send performance evaluation metrics to a manufacturing execution system (MES) 326 or distributed control system (DCS) 328, which may be located in a remote server, and to adjust process parameters. The MES or DCS can then instruct automated storage and retrieval systems and / or autonomous mobile robots to operate batteries within the forming station, aging station, and sorting station. The MES or DCS may be integrated into a computer system such as a "centralized operation console" or "integrated operation center," or equivalent, and the data may be displayed on a human-machine interface (HMI). The communication module 324 can transmit inline process information acquired from the forming station and aging station to the safety control system 330, which is an early battery failure detection mechanism. For example, it can provide early detection of smoke or gas and / or heat from the battery, thermal imaging, electrolyte vapor detection, and related safety measures to prevent thermal runaway.
[0043] The above has described the principles, preferred embodiments, and operating modes of the present invention. However, the present invention should not be construed as being limited to the specific embodiments considered. Rather, the embodiments described above should be considered illustrative rather than restrictive, and it should be understood that modifications of those embodiments can be made 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 dynamic control and optimization of a secondary battery cell finishing process, comprising a closed-loop process control module configured to process real-time in-line manufacturing data derived from at least one of the following battery measurements: electrochemical impedance spectroscopy (EIS), self-discharge analysis (SDA), current measurement, or potentiometric measurement.
2. The aforementioned battery measurement is performed by ohm resistance R Ω , charge transfer resistance R ｃｔ , leakage current I ｌｅａｋ The system according to claim 1, comprising process parameters selected from the group consisting of open-circuit voltage (OCV), voltage drop (ΔV), and combinations thereof.
3. A system for feedback alerts and / or control of a secondary battery cell finishing process, comprising a closed-loop process control module, the closed-loop process control module is (i) Process real-time in-line manufacturing data from charge / discharge function, electrochemical impedance spectroscopy (EIS) measurement, self-discharge analysis (SDA) measurement, current measurement, and / or potentiometric measurement. (ii) Identify the deviation from the standard for battery performance, (iii) A system configured to identify past battery manufacturing operating conditions that potentially contribute to deviations in battery performance from that standard.
4. A system for feedforward alerting and / or control of a lithium-ion battery cell finishing process, comprising a closed-loop process control module, the closed-loop process control module is (i) Process real-time in-line manufacturing data from charge / discharge function, electrochemical impedance spectroscopy (EIS) measurement, self-discharge analysis (SDA) measurement, current measurement, and / or potentiometric measurement. (ii) Identify the deviation from the standard for battery performance, (iii) A system configured to identify post-operation material of similar attributes for potential contribution from its criteria for laboratory analysis and / or isolation.