Unit and rack performance monitoring system and method

Abstract

A battery cell performance monitoring system includes an energy storage system including at least one inverter and a battery node. Each battery node includes a battery rack, and each battery rack includes a battery cell. The battery performance monitoring system also includes a processor, a memory, and a program in the memory. The program causes the battery cell performance monitoring system to determine an extreme rack cell voltage value for each battery rack. An average extreme rack unit voltage value is then determined from the extreme rack unit voltage value for each battery rack. Further, the extreme rack unit voltage value for each battery rack is compared to an average extreme rack unit voltage value. Further, one or more anomalous battery racks are identified based on a comparison of the extreme rack unit voltage value for each battery rack to the average extreme rack unit voltage value.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. patent application No. 17 / 810,983, filed on July 6, 2022, and entitled “SYSTEM AND METHOD FOR UNIT AND RACK PERFORMANCE MONITORING,” the entire contents of which are incorporated by reference into this application. Technical Field

[0003] The present invention relates to an example of effectively detecting an inefficiently charged or discharged battery cell in an energy storage system composed of a plurality of battery cells divided into battery racks. Background Art

[0004] Energy storage systems typically include many individual battery cells to provide power. Specifically, these battery cells work together to provide direct current (DC) power to a power inverter, which then provides the DC power as alternating current (AC) to the end-use electrical devices.

[0005] When the battery cells are networked and wired in such a way that they function as a single DC power supply, in most cases the battery cells are charged and discharged as a group of batteries or a single function battery. Therefore, the collection of battery cells can all be charged from an external power source and can all be discharged to an external power source target. To avoid damaging the battery cells, the collection of battery cells stops charging once the individual battery cells in the collection are fully charged, and the collection stops discharging once the individual battery cells in the collection are fully discharged.

[0006] Therefore, the charging and discharging capabilities of the entire collection of cells are limited by the worst performing charging cell and the worst performing discharging cell (which may be different cells). Therefore, identifying poorly performing cells is critical: one cell operating at 50% of its charged capacity may limit tens of thousands of other cells to operating at the same 50% capacity. In some systems, low-performing cells are only investigated when the system is set up, or during periodic inspections, or when a user reports a degradation in performance. However, there is a strong interest in identifying low-performing cells before performance degradation is noticeable, and potentially isolating, repairing, or replacing the cells without affecting the equipment that supplies power to or consumes power from the energy storage system.

[0007] Auditing the performance of individual cells each time a collection of cells is charged or discharged provides better quality performance information than a one-time, periodic, or passive audit of cell performance. However, evaluating the performance of every cell in an energy storage system can be computationally expensive. Furthermore, if the collective failure rate of the cells is extremely low (e.g., only one cell fails in a thousand charging cycles, a failure rate of 1%), then the value of any single group calculations will be wasted (a 1% failure rate in a thousand cycles may result in an average of only one failure being identified every 100,000 cycles). However, once a failure occurs, it will persist until corrected - so timely identification of failures is critical to maintaining optimal performance of the entire energy storage system. Summary of the invention

[0008] Therefore, there is room for further improvement in the method of identifying low-performing battery cells in an energy storage system and the energy storage system using this method. The performance monitoring technology disclosed in this article is capable of identifying low-performing battery cells in an energy storage system during a single charge or discharge period of a charging cycle, and further identifying the classification of the type of failure experienced by the low-performing battery within a single charging cycle. Using this performance monitoring technology, a preliminary assessment of battery cell performance data can be performed at the battery node, battery rack, battery module, battery submodule or other battery element level, thereby potentially reducing the computational overhead of battery cell audits by 99% or more.

[0009] In a first example, a battery cell performance monitoring system includes: an energy storage system including at least one inverter and a plurality of battery nodes. Each battery node includes a plurality of battery racks, and each battery rack includes a respective plurality of battery cells. The battery cell performance monitoring system also includes a processor and a memory coupled to the processor. The memory includes a performance monitoring program, which, when executed, can configure the battery cell performance monitoring system to implement the following functions. First, determine the extreme rack unit voltage value of each battery rack. Second, determine the average extreme rack unit voltage value based on the extreme rack unit voltage value of each battery rack. Third, compare the extreme rack unit voltage value of each battery rack with the average extreme rack unit voltage value. Fourth, identify one or more outlier battery racks based on the comparison of the extreme rack unit voltage value of each battery rack with the average extreme rack unit voltage value.

[0010] In a second example, a method includes: first, determining an extreme element cell performance value for each battery element in a plurality of battery elements. Second, determining an average extreme element cell performance value based on the extreme element cell performance value for each battery element. Third, comparing the extreme element cell performance value for each battery element with the average extreme element cell performance value. Fourth, identifying one or more outlier battery elements based on the comparison of the extreme element cell performance value for each battery element with the average extreme element cell performance value.

[0011] In a third example, a battery cell performance monitoring system includes: an energy storage system including at least one inverter and a plurality of battery nodes. Each battery node includes a plurality of battery elements, and each battery element includes a respective plurality of battery cells. The battery cell performance monitoring system also includes a processor and a memory coupled to the processor. The memory includes a performance monitoring program, which, when executed, can configure the battery cell performance monitoring system to implement the following functions. First, determine the extreme element cell performance value of each battery rack. Second, determine the average extreme element cell performance value based on the extreme element cell performance value of each battery element. Third, compare the extreme element cell performance value of each battery element with the average extreme element cell performance value. Fourth, identify one or more abnormal value battery elements based on the comparison of the extreme element cell performance value of each battery element with the average extreme element cell performance value.

[0012] Other purposes, advantages and novel features of the examples will be described in part in the following description, and in part will become apparent to those skilled in the art after studying the following contents and drawings, or in part can be learned through the production or operation of the examples. The objects and advantages of the present invention can be realized and obtained by the methods, means and combinations particularly pointed out in the appended claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings describe one or more embodiments of the inventive concept, only by way of example and not limitation. In the drawings, the same reference numerals refer to the same or similar elements.

[0014] Figure 1 is an isometric view of an energy storage system including multiple battery nodes.

[0015] Figure 2 is an isometric view of a battery node including a plurality of battery racks or elements of a plurality of battery cells.

[0016] Figure 3 is a diagram of a performance monitoring subsystem of a battery cell performance monitoring system.

[0017] Figure 4 is a diagram of a plurality of battery cells in a battery rack or cell with subsets of the cells being in various classifications of outlier conditions.

[0018] Figure 5 This is a graph showing the change in cell voltage over time of abnormal value cells classified as high resistance cells compared to non-abnormal value cells.

[0019] Figure 6 It is a graph showing the change in cell voltage over time of an outlier battery cell classified as a low-capacity cell compared to a non-outlier battery cell.

[0020] Figure 7 is a graph showing changes in cell voltage over time for two outlier cells classified as a high-imbalance cell and a low-imbalance cell compared to non-outlier cells.

[0021] Figure 8 is a flow chart describing the unit and component performance monitoring protocol.

[0022] Reference numerals:

[0023] DETAILED DESCRIPTION

[0024] In the following detailed description, a large number of specific details are set forth by way of example in order to provide a comprehensive understanding of the relevant teachings. However, it is apparent to those skilled in the art that the present teachings can be practiced without these details. In other instances, relatively high-level descriptions of well-known methods, procedures, components and / or circuits are provided without detailed descriptions to avoid unnecessarily obscuring various aspects of the present teachings.

[0025] The term "coupled" as used herein refers to any logical, physical, electrical or optical connection, link, etc., by which a signal or light generated or provided by one system element is transmitted to another coupled element. Unless otherwise specified, coupled elements or devices are not necessarily directly connected to each other and may be separated by intermediate components, elements or communication media (which may modify, manipulate or transmit light or signals).

[0026] Unless otherwise stated, any and all measurements, values, ratings, positions, magnitudes, dimensions, and other specifications described in this specification (including the claims that follow) are approximate and not exact. These quantities are intended to have a reasonable range that is consistent with the functions to which these quantities are related and the customary practices in the art. For example, unless otherwise expressly stated, parameter values, etc. may vary from the stated quantity by as much as ±10%. The terms "approximately" and "substantially" mean that parameter values, etc. vary from the stated quantity by up to ±10%.

[0027] The orientation of a battery node, rack, module or unit, related components and / or any complete device (e.g., an energy storage system including a battery node, rack, module or unit shown in any of the accompanying drawings) is given by way of example only for the purpose of illustration and discussion. In operation for a specific energy storage application, the battery node, rack, module or unit may be oriented in any other direction suitable for the specific application of the energy storage system, such as upright, lateral or any other direction. In addition, within the scope of use herein, any directional terms, such as left, right, front, rear, back, end, up, down, upper, lower, top, bottom, and side, are used only as examples and do not limit the direction or orientation of any energy storage system or battery node, rack, module or unit, or the direction or orientation of the components of the energy storage system or battery node or rack. The examples shown in the accompanying drawings are discussed below.

[0028] Figure 1 1 is an isometric view of a battery cell performance monitoring system 1, which mainly includes an energy storage system 100 and a performance monitoring subsystem 112. The energy storage system 100 includes a plurality of battery nodes 110A-N. The battery nodes 110A-N include batteries of any existing or future reusable battery technology, including lithium-ion batteries or flow batteries. The battery nodes 110A-N (collectively and individually) can both provide direct current to an external load (thereby discharging) and receive direct current from an external power source (thereby charging).

[0029] To facilitate providing and receiving DC power, the battery nodes 110A-N are connected to one or more power inverters 104. The power inverters 104 are configured to normalize the power input and output to and from the battery nodes 110A-N. When the battery nodes 110A-N provide DC power, the power inverters 104 either convert the DC power to AC power for use by the connected loads 106, or normalize the DC power from the battery nodes 110A-N to the connected loads 106, or simply pass the DC power from the battery nodes 110A-N to the connected loads. In addition, when the battery nodes require DC power, the power inverters either convert the AC power from the energy source 102 to DC power, or normalize the DC power from the energy source 102 to the battery nodes 110A-N, or simply pass the DC power from the energy source 102 to the battery nodes 110A-N.

[0030] The depicted power inverter has separate lines to the energy source 102 and the connected loads 106: In the case where the energy source 102 is not uniform, such as wind or solar energy 102, separate lines may be advantageous. In this case, power from the energy source 102 is pushed to the battery nodes 110A-N through a unidirectional power inverter 104, and then the battery nodes 110A-N are charged or discharged; and power from the energy source 102 is provided to the connected loads 106 through another unidirectional power inverter 104 to provide continuous power. However, the connected loads 106 and the energy source 102 can be connected to the power inverter 104 on the same line through a bidirectional power inverter 104: In the case where the energy source 102 is complex and connected to the connected loads 106, such as a grid with consumer equipment, a single connection to the energy storage system either absorbs energy produced by the energy source 102 in excess of the connected loads 106 needs, or provides energy to the connected loads 106 in excess of the energy source 102 capacity.

[0031] To provide a consistent output and protect the battery nodes 110A-N, the energy source 102, or the connected load 106 from damage, the power inverter 104 may also include a power converter to facilitate normalizing the input or output wattage or voltage.

[0032] Energy source 102 may be any suitable system for producing electrical energy, such as a turbine or photovoltaic cells. Connected loads 106 may include the electrical grid or smaller local loads, such as backup power systems for facilities such as hospitals, manufacturing sites, residences, or other suitable facilities.

[0033] The battery unit performance monitoring system 1 includes a performance monitoring subsystem 112 connected to the energy storage system 100, which monitors the abnormal value charging and discharging cycles of the battery nodes 110A-N. Generally speaking, the battery nodes 110A-N of the energy storage system 100 connected to the inverter 104 or a group of inverters 104 work together: either provide power to the connected load 106 and discharge, or receive power from the energy source 102 and charge. Therefore, defects in a single battery node 110A-N can reduce the efficiency of the entire energy storage system 100. The performance monitoring subsystem 112 is configured to receive power system data from the battery nodes 110A-N connected to the power inverter 104. As discussed in the following figures, this data is used to identify poorly performing battery nodes 110A-N so that measures can be taken to restore the performance of the energy storage system 100 despite the poorly performing battery node 110A.

[0034] Figure 2is an isometric view of a battery node 110A including a plurality of battery racks 210A-F including a plurality of battery cells 212A-N. The battery node 110A stores a plurality of battery racks 210A-F. The battery node 110A is both a physical collection of battery racks 210A-F and a logical and electrical collection of battery racks 210A-F: the battery node 110A physically houses the battery racks 210A-F, and the electrical performance of the battery racks 210A-F within the battery node 110A is attributable to the battery node 110A itself. For example, if one battery rack 210A is capable of storing 102 kWh of energy, and the battery node 110A includes six battery racks 210A-F, then the battery node 110A may be understood and described as storing 612 kWh of energy. The battery node 110A may include more or fewer battery racks 210A than depicted in the figure.

[0035] A given battery rack 210A includes a plurality of battery cells 212A-N. Similar to the relationship between a battery node 110A and the battery racks 210A-F it contains, a battery rack 210A is both a physical collection of battery cells 212A-N and a logical and electrical collection of battery cells 212A-N. For example, if a battery cell 212A is capable of storing six kilowatt-hours of energy, and a battery rack 210A includes seventeen battery cells 212A-N, then the battery node 210A may be understood and described as storing 102 kilowatt-hours of energy. A battery rack 210A may include more or fewer battery cells 212A than depicted in the figure.

[0036] Because the battery rack 210A is a logical and electrical collection of battery cells 212A-N, the collection is not defined by the physical structure or ordering of the battery cells 212A-N. Therefore, the battery rack 210A may be alternatively described as a battery module, a battery submodule, or a battery array: Each of these terms (rack, module, submodule, array) is a category of battery element 210A: The battery element 210A is a logical and electrical collection of battery cells 212A-N without explicitly considering the physical structure or ordering of the battery cells 212A-N. In some embodiments, there is an interstitial level of encapsulation between the battery cells 212A and the battery rack 210A or battery element 210A, which can be identified as a battery module within the battery element 210A, containing prismatic, pouch, or cylindrical battery cells 212A-C: In this case, this distinction is largely irrelevant because the primary structural organization focuses on the logical and electrical, rather than the physical structure or ordering.

[0037] The battery node 110A represents a single physical fixture, the maximum size of which may be limited by the mass or volume that can be transported as a singular, atomic unit by a person, forklift, or vehicle. The battery rack 210A or battery element 210A within the battery node 110A represents an organizational structure for organizing and stacking the battery cells 212A-N within the battery node 110A. The battery cell 212A is generally the largest manufacturing unit that a battery manufacturer can produce that is capable of charging and discharging at a chemical level. In some examples, the battery cells 212A-C may be combined into battery modules in the battery element 210A-F, which will represent the smallest unit that a particular operator will remove or replace in the energy storage system 100: in these examples, the individual battery cells 212A are too small or too sensitive to undergo site-specific maintenance, and the entire battery module composed of the battery cells 212A-C is repaired or replaced collectively. As described later, the performance monitoring subsystem 112 may be able to detect an outlier at the battery cell 212A level: however, in an energy storage system 100 that includes battery modules within battery elements 210A-F, an operator may need to replace the entire battery module that includes the outlier cell 212A, even if the performance of the remaining battery cells 212B-C within the battery module is not abnormal.

[0038] Figure 3 is a diagram of a performance monitoring subsystem 112. The performance monitoring subsystem 112 collects performance data about all battery cells 212A-R in the energy storage system 100, as well as performance data for each battery rack or element 210A. In other embodiments, performance data may be collected at the battery node 110A-B level, as well as performance data for the entire energy storage system 100. In this example, the performance monitoring subsystem 112 is connected to the battery rack or element 210A-B and the battery cells 212A-D, OR via a wired connection; however, the performance monitoring subsystem 112 may also be connected to the battery rack or element 210A-B and the battery cells 212A-D, OR via a wireless connection.

[0039] The performance monitoring subsystem 112 includes a processor 330. The processor 330 is used to perform various operations, for example, according to instructions or programs executable by the processor 330. For example, such operations may include operations related to communicating with various energy storage system 100 elements (e.g., battery nodes 110A-N, power inverters 104, energy sources 102) or across distributed performance monitoring subsystems 112 to implement the performance monitoring protocol 800. Although the processor 330 can be configured using hard-wired logic, a typical processor is a general-purpose processing circuit configured by executing a program. The processor 330 includes such elements, which are structured and arranged to perform one or more processing functions (usually various data processing functions). Although discrete logic elements can be used, components that constitute a programmable CPU are used in the example. For example, the processor 330 includes one or more integrated circuit (IC) chips that incorporate electronic components to perform CPU functions. For example, the processor 330 can be based on any known or available microprocessor architecture, such as Reduced Instruction Set Computing (RISC) using the ARM architecture, which is currently commonly used in mobile devices and other portable electronic devices. Of course, other processor circuits may be used to form the CPU or processor hardware. Although the illustrated example of processor 330 includes only one microprocessor, for convenience, a multi-processor architecture may also be used. A digital signal processor (DSP) or a field-programmable gate array (FPGA) may be a suitable alternative to processor 330, but may consume more power due to the increased complexity.

[0040] Memory 335 is coupled to processor 330. Memory 335 is used to store data and programs. In this example, memory 335 may include flash memory (non-volatile or persistent storage) and / or random-access memory (RAM) (volatile storage). RAM can be used as short-term storage for processor 330 to process instructions and data, such as working data processing memory. Flash memory generally provides long-term storage.

[0041] Of course, other storage devices or configurations may be added to or replace those in this example. These other storage devices may be implemented using any type of storage media in which computer or processor readable instructions or programs are stored, for example, any or all tangible memories of a computer, processor, etc., or related modules.

[0042] The performance monitoring subsystem 112 may also include a network interface 332 coupled to the processor 330. The network interface 332 is configured to report performance data from the battery racks 210A-B and the battery cells 212A-D, OR to a networked server. In addition, if the battery racks 210A-B are equipped with a network interface, the network interface 332 may collect performance data from the battery racks or cells 210A-B; if the battery cells 212A-D, OR are equipped with a network interface, the network interface 332 may collect performance data from the battery cells 212A-D, OR.

[0043] The performance monitoring subsystem 112 can be implemented in a distributed manner: the processor 330 can be divided into two or more processors, and two or more storage devices 335. The processors 330 can work in parallel or be specialized to perform specific tasks. The storage 335 device can store a complete copy of all performance data, or store specific data related to a specific processor 330. In the example, the performance monitoring subsystem 112 is divided into a local group and a remote group. The local processor 330, the local memory 335, and the local network interface 332 can collect performance data from the battery rack or element 210A-B and the battery unit 212A-D, OR; while the remote processor 330, the remote memory 335, and the remote network interface 332 can receive the collected data and perform analysis and decision making.

[0044] Analyzing the battery racks or components 210A-B and the cells 212A-D, OR to detect low-performing or outlier cells 212A can be computationally intensive: a full check is performed at the end of the charge cycle and discharge cycle of each charging cycle. In particular, if it is unlikely that any of the cells 212A-D, OR is an outlier in any given charging cycle, then the actionable value of the calculation result if the calculation result does not identify the outlier cell 212A is often low. Therefore, the analysis process searches for outlier cells 212A in at least two stages: first, at the battery rack or component 210A level (does the battery rack 210A contain an outlier cell 212A?); second, at the cell 212A-D level within the battery rack or component 210A in the first stage (which cell 212A among the cells 212A-D is the outlier cell in that battery rack 210A?)

[0045] To facilitate this process, memory 335 includes several objects. In particular, performance monitoring program 337 is a program that implements performance monitoring protocol 800.

[0046] The extreme rack cell voltage value 339A is the most extreme voltage value for any battery cell 212A-D within a given battery rack 210A. An "extreme" voltage value can be either a high voltage value or a low voltage value. Generally speaking, an extreme voltage value is a high voltage value at the end of charge (EOC) and a low voltage value at the end of discharge (EOD). Each functional battery rack 210A-G in the energy storage system 100 should have an extreme rack cell voltage value 339A-G. The extreme rack cell voltage value 339A can be more broadly identified as an extreme element cell performance value 339A: The extreme element cell performance value 339A can encompass performance values ​​other than voltage, such as amperage or temperature, that describe or affect the performance of any battery cell 212A-D in a given battery element 210A. For example, an "extreme" performance value can be a high temperature value or a low amperage value.

[0047] The average extreme rack unit voltage value 341 is the average of each extreme rack unit voltage value 339A-G. Each extreme rack unit voltage value 339A-G used in the average extreme rack unit voltage value 341 is collected from the same EOC or EOD to allow for a one-to-one performance comparison. The average extreme rack unit voltage value 341 may be more broadly identified as an average extreme component unit performance value 341: the average extreme component unit performance value is the average of each extreme component unit performance value 339A-G.

[0048] Once the average extreme rack unit voltage value 341 is calculated, each extreme rack unit voltage value 339A-G is compared to the average extreme rack unit voltage value 341. If the extreme rack unit voltage value 339A is substantially deviated and the voltage is too high or too low, the battery rack 210A associated with the extreme rack unit voltage value 339A will be identified as an outlier battery rack and an outlier battery rack identifier 343. "Substantially deviated", "too high voltage" or "too low voltage" can be a deviation from the average, as low as one percent. Alternatively, each extreme component unit performance value 339A-G is individually compared to the average extreme component unit performance value 341, and the extreme component unit performance value 339A that has a larger deviation from the average extreme component unit performance value 341 is identified as an outlier battery component with an outlier battery component identifier 343.

[0049] Once the outlier battery rack identifier 343 identifies the outlier battery rack 210A or the outlier battery element identifier 343 identifies the outlier battery element 210A, the performance monitoring subsystem 112 finds the battery cell 212A that caused the battery rack or element 210A to be identified as an outlier. The cell voltage value 345A-D of each battery cell 212A-D in the outlier battery rack or element 210A is recorded in the memory 335, or the cell performance value 345A-D of each battery cell 212A-D in the outlier battery rack or element 210A is recorded in the memory. Based on the cell voltage values ​​345A-D, an average rack cell voltage value 347A is calculated, which is the average of the cell voltage values ​​345A-D. Alternatively, based on the cell performance values ​​345A-D, an average element cell performance value 347A is calculated, which is the average of the cell performance values ​​345A-D.

[0050] Once the cell voltage values ​​345A-D or cell performance values ​​345A-D are collected from the EOD or EOC of a given charging cycle and the average rack cell voltage value 347A or average component cell performance value 347A is calculated, any battery cell 212 with a substantial deviation is identified as an outlier battery cell 212A and an outlier battery cell identifier 349A is stored in the memory 335. A charging cycle may begin at any point in the charging cycle: the charging cycle may begin by discharging the energy storage system 100 or a subassembly, reaching EOD, charging the energy storage system 100, reaching EOC. Alternatively, the charging cycle may begin by charging the energy storage system 100, reaching EOC, discharging the energy storage system 100, reaching EOD. In particular, when initializing the energy storage system 100, the state of charge of any battery cell 212 may be unknown: in some cases, the battery cell 212 is partially charged. The operator may choose to move the energy storage system 100 toward the EOD or EOC direction in order to synchronize all battery cells 212 at the same EOC point and EOD point.

[0051] Multiple outlier battery cells 212A-B can be identified and multiple outlier battery cell identifiers 349A-B can be stored. Similarly, when checking an outlier battery rack 210A, multiple outlier battery racks 210A-B can be identified at the same time. Generally speaking, if there is no external interference (such as physical damage to the energy storage system 100), only one battery cell 212A in a battery rack 210A is an outlier at a time: once an outlier battery cell 212A is identified, the operator will usually take immediate action to repair or replace the outlier battery cell 212A. In some embodiments, the outlier battery cell 212A or outlier battery rack or element 210A can also be deactivated or disconnected from the remaining battery racks or elements 210A, battery node 110A, or disconnected from the remaining set of battery nodes 110B-N. Doing so may enable the energy storage system 100 to fully charge and discharge in exchange for lost capacity of the offline battery cells 212A, battery racks or elements 210A, or battery nodes 110A.

[0052] After identifying the outlier cell 212A, the operator may be interested in the specific type of abnormal behavior exhibited by the cell 212A. Four types of abnormal behavior may include high resistance, low capacity, unbalanced on the high end, and unbalanced on the low end. High resistance or low capacity cells are typically replaced, while unbalanced (high or low) cells may be repaired or rebalanced. In order to characterize an outlier cell 212A in one of these categories, several data points should be collected.

[0053] In a given charging cycle, the voltage of the battery cell 212A at EOC is stored as the EOC cell voltage 351, and the voltage of all the battery cells in the entire battery rack 210A at EOC is stored as the EOC average rack voltage value 361. The voltage of the battery cell 212A at EOD is stored as the EOD cell voltage 355, and the voltage of the entire battery rack 210A at EOD is stored as the EOD average rack voltage value 365. The voltage of the battery cell 212A at mid-discharge (MOD) is stored as the MOD cell voltage 353, and the voltage of the entire battery rack 210A at MOD is stored as the EOD average rack voltage value 363.

[0054] Although identifying high resistance, low capacity, unbalanced at the high end, and unbalanced at the low end battery cells 212 may be most effectively performed using voltages (i.e., EOC cell voltages 351, MOD cell voltages 353, EOD cell voltages 355, EOC average rack voltage values ​​361, MOD average rack voltage values ​​363, EOD average rack voltage values ​​365), other similar performance values, such as amperage or temperature, may also be used. Thus, the performance monitoring system may store the EOC cell performance values ​​351, MOD cell performance values ​​353, EOD cell performance values ​​355, EOC average element performance values ​​361, MOD average element performance values ​​363, and EOD average element performance values ​​365 within a given charging cycle.

[0055] Although the figure depicts a single copy of the stored cell voltage or performance values ​​351, 353, 355 and rack voltage or component performance values ​​361, 363, 365, in some embodiments, each battery cell 212A-R and each battery rack or component 210A-G has a copy of these cell voltage or performance values ​​351, 353, 355 and rack voltage or component performance values ​​361, 363, 365 stored in the memory 335. If each value is stored, then a single charge cycle can be used to identify the characteristics of an outlier battery rack 210A, an outlier battery 212A, and an outlier battery 212A.

[0056] Figure 4 2 is a diagram of a plurality of battery cells 212A-L, wherein subsets of battery cells 212A, D, G, J are in various classifications of outlier states. Each battery cell 212A-L is configured to generally target three voltages: 3.6 volts at EOC, 3.2 volts at MOD, and 2.8 volts at EOD.

[0057] To characterize the problem type of outlier battery cells 212A, D, G, J, it is necessary to compare the cell voltage differences at different times during the cycling process. The voltage differences are calculated at EOC, EOD, and mid-discharge (MOD). The voltage differences are calculated by comparing the EOC cell voltage 351 to the average EOC cell voltage 361 of all cells in rack 361, comparing the MOD cell voltage 353 to the average MOD cell voltage of all cells in rack 363, and comparing the EOD cell voltage 355 to the average EOD cell voltage of all cells in rack 365. The outlier batteries 212A, D, G, J are classified into four types: high resistance, low capacity, high imbalance, or low imbalance.

[0058] The high resistance cell 212A has a greater resistance to the flow of electrons or ions. According to Ohm's law (V=IR), a greater resistance means a greater voltage drop or voltage rise (depending on whether the cell 212A is discharging or charging). Due to the voltage curve offset, the high resistance cell 212A will reach the cutoff voltage earlier, thereby limiting the full use of the capacity of the cell 212A and preventing the other cells 212B-L from fully cycling. Whenever a load is applied to the high resistance cell 212A, the voltage will deviate from the average cell voltage to a large extent, that is, the voltage difference will be large at EOC, EOD and MOD.

[0059] It can be seen that battery cell 212A experiences high resistance: the EOC value of battery cell 212A is greater than the other two EOC values ​​in battery rack 210H, the MOD value of battery cell 212A is lower than the other two MOD values ​​in battery rack 210H, and the EOD value of battery cell 212A is lower than the other two EOD values ​​in battery rack 210H.

[0060] The low capacity battery 212D has fewer ions available to participate in charge transfer. Low capacity can be caused by a variety of damage mechanisms, including active material loss, SEI formation, lithium plating, or production defects. The low capacity battery cell 212D itself has a lower capacity than the other battery cells 212E-F in the battery rack 210I. This battery cell 212D reaches the voltage cutoff limit earlier than the other battery cells 212E-F, which then limits the full cycle of the other battery cells 212E-F. The low capacity battery cell 212D is detected by the large voltage difference at EOC and EOD and the small voltage difference at MOD.

[0061] It can be seen that battery cell 212D experiences low capacity: the EOC value of battery cell 212D is greater than the other two EOC values ​​in battery rack 210I, the MOD value of battery cell 212D is close to the other two MOD values ​​in battery rack 210I, and the EOD value of battery cell 212D is lower than the other two EOD values ​​in battery rack 210I.

[0062] An unbalanced cell 212G, J refers to a cell 212G, J that is charged or discharged more than the other cells 212H-I, 212K-L in the battery rack 210J-K. It can be observed that the voltage of the high-unbalanced cell 212G is higher than the other cells 212H-I in the battery rack 210J throughout the cycle (even during the rest phase). It can also be observed that the voltage of the low-unbalanced cell 212J is lower than the other cells 212K-L in the battery rack 210K throughout the cycle (even during the rest phase).

[0063] The high-unbalanced battery cell 212G is charged more and has a higher voltage than other battery cells 212H-I, and reaches the upper voltage limit of the battery cell 212G earlier than other battery cells 212H-I, thereby limiting the total charging capacity of the battery rack 210J. Conversely, the unbalanced battery cell 212J is discharged more and has a lower voltage, and reaches the lower voltage limit earlier, thereby limiting the total discharge capacity of the battery rack 210K.

[0064] It can be seen that cell 212G experiences high imbalance: the EOC value of cell 212G is greater than the other two EOC values ​​in battery rack 210J, and the EOD value of cell 212G is close to the other two EOD values ​​in battery rack 210J. Note that the MOD value is generally not used to determine the high imbalance cell 212G.

[0065] It can be seen that cell 212J experiences low imbalance: the EOC value of cell 212G is close to the other two EOC values ​​in battery rack 210K, and the EOD value of cell 212G is lower than the other two EOD values ​​in battery rack 210K. Note that the MOD value is generally not used to determine the low imbalance cell 212J.

[0066] Figure 5 2 is a graph showing the cell voltage of the abnormal value battery cell 212A classified as a high resistance cell over time compared to the non-abnormal value battery cells 212B-C. Figure 4 As described above, it can be seen that as time goes by, the voltage peak value of the abnormal value battery cell 212A at EOC is higher, the voltage of the abnormal value battery cell 212A at MOD is lower, and the voltage valley value of the abnormal value battery cell 212A at EOD is lower.

[0067] Figure 6 2 is a graph showing the cell voltage of the abnormal value battery cell 212D classified as a low capacity cell over time compared to the non-abnormal value battery cells 212E-F. Figure 4 As described above, it can be seen that as time goes by, the voltage peak value of the abnormal value battery cell 212D at EOC is higher, the voltage of the abnormal value battery cell 212D at MOD is consistent with the average value, and the voltage valley value of the abnormal value battery cell 212D at EOD is lower.

[0068] Figure 7 2 is a graph showing the cell voltage changes over time of two abnormal value battery cells 212G and 212J, which are classified as a high imbalance cell 212G and a low imbalance cell 212J, compared to the non-abnormal value battery cells 212H-I and KL. Figure 4As described above, it can be seen that as time goes by, the voltage peak value of the abnormal value battery cell 212G at EOC is higher, and the voltage valley value of the abnormal value battery cell 212G at EOD is consistent with the average value. In addition, the voltage peak value of the abnormal value battery cell 212J at EOC is consistent with the average value, and the voltage valley value of the abnormal value battery cell 212J at EOD is lower.

[0069] therefore, Figures 1 to 7 A battery cell performance monitoring system 1 is described, comprising: an energy storage system 100, which includes at least one inverter 104 and a plurality of battery nodes 110A-N. Each battery node 110A includes a plurality of battery racks 210A-F. Each battery rack 210A includes a respective plurality of battery cells 212A-N. The battery cell performance monitoring system 1 also includes a processor 330 and a memory 335 coupled to the processor 330. The memory includes a performance monitoring program 337, which, when executed, can configure the battery cell performance monitoring system 1 to implement the following functions. First, determine the extreme rack unit voltage value 339A-G of each battery rack 210A-G. Second, determine an average extreme rack unit voltage value 341 based on the extreme rack unit voltage value 339A-G of each battery rack 210A-G. Third, compare the extreme rack unit voltage value 339A-G of each battery rack 210A-G with the average extreme rack unit voltage value 341. Fourth, based on a comparison of the extreme rack unit voltage values ​​339A-G of each battery rack 210A-G with the average extreme rack unit voltage value 341 , one or more outlier battery racks 210A are identified.

[0070] The determination of the extreme rack unit voltage value 339A may be based on the charging portion or the discharging portion of the cycle or a combination of both. The cycle includes charging the battery cell 212A from the energy source 102 and discharging the battery cell 212A to power the connected load 106. The extreme rack unit voltage value 399A may be determined at the end of the charging portion of the cycle, or at the end of the discharging portion of the cycle.

[0071] The extreme rack unit voltage value 339A may describe a voltage that is too high compared to other battery racks 210B-G in the energy storage system 100, wherein the voltage that is too high may be a voltage that is at least one percent higher than the voltage of other battery racks 210B-G in the energy storage system 100. The extreme rack unit voltage value 339A may describe a voltage that is too low compared to other battery racks 210B-G in the energy storage system 100, wherein the voltage that is too low may be a voltage that is at least one percent lower than the voltage of other battery racks 210B-G in the energy storage system 100.

[0072] The execution of the performance monitoring program 337 may further configure the battery cell performance monitoring system 1 to implement the following functions. First, determine the average rack cell voltage value 347A of each battery rack 210A. Second, compare the cell voltage value 345A-D of each battery cell 212A-D of the plurality of battery cells 212A-D of each battery rack 210A with the average rack cell voltage value 347A. Third, identify one or more outlier battery cells 212A based on the comparison of the cell voltage value 345A-D of each battery cell 212A-D with the average rack cell voltage value 347A.

[0073] When calculating the average extreme rack unit voltage value 341 or the average rack unit voltage value 347A, any averaging method can be used: calculating the mean, the median, the mode, and calculating the mean by performing a "drop one" averaging method (for example, when calculating the average to be compared with battery cell 212A, use battery cell 212B-D; when calculating the average to be compared with battery cell 212B, use battery cell 212A, CD, etc.). It can also be further decided to exclude or weight different values ​​in the averaging. The average value can also be an expected performance value based on the manufacturer's specifications for the 212A-D battery. The expected performance value can be modified by a degradation function, for example, the battery cell 212A-D is expected to lose 10% functionality per year during use, or 1% functionality per thousand charging cycles.

[0074] The execution of the performance monitoring program 337 may further configure the battery cell performance monitoring system 1 to implement the following functions. First, determine an end-of-charge (EOC) cell voltage 351, an end-of-discharge (EOD) cell voltage 355, and a mid-discharge (MOD) cell voltage 353 of a first abnormal value battery cell 212A among one or more abnormal value battery cells 212A. Second, determine an EOC average rack cell voltage value 361, an EOD average rack cell voltage value 365, and a MOD average rack cell voltage value 363 of each battery rack. Third, in response to the EOC cell voltage 351 substantially deviating from the EOC average rack voltage value 361, the EOD cell voltage 355 substantially deviating from the EOD average rack voltage value 365, and the MOD cell voltage 353 substantially deviating from the MOD average rack voltage value 363, characterize the first abnormal value battery 212A as a high resistance cell.

[0075] Fourth, in response to the EOC cell voltage 351 substantially deviating from the EOC average rack unit voltage value 361 , the EOD cell voltage 355 substantially deviating from the EOD average rack unit voltage value 365 , and the MOD cell voltage 253 being substantially similar to the MOD average rack unit voltage value 363 , the first outlier cell 212D is characterized as a low capacity cell.

[0076] Fifth, in response to the EOC cell voltage 351 being substantially deviated from the EOC average rack unit voltage value 361 , and the EOD cell voltage 355 being substantially similar to the EOD average rack unit voltage value 365 , the first outlier cell 212G is characterized as an unbalanced cell.

[0077] Figure 1-7 A battery cell performance monitoring system 1 is also described, including: an energy storage system 100, which includes at least one inverter 104 and a plurality of battery nodes 110A-N. Each battery node 110A includes a plurality of battery elements 210A-F. Each battery element 210A includes a respective plurality of battery cells 212A-N. The battery cell performance monitoring system 1 also includes a processor 330 and a memory 335 coupled to the processor 330. The memory includes a performance monitoring program 337, which, when executed, can configure the battery cell performance monitoring system 1 to implement the following functions. First, determine the extreme element cell performance value 339A-G of each battery element 210A-G. Second, determine an average extreme element cell performance value 341 based on the extreme element cell performance value 339A-G of each battery element 210A-G. Third, compare the extreme element cell performance value 339A-G of each battery element 210A-G with the average extreme element cell performance value 341. Fourth, based on a comparison of the extreme cell performance value 339A-G of each cell 210A-G with the average extreme cell performance value 341, one or more outlier cell elements 210A are identified.

[0078] The determination of the extreme element cell performance value 339A may be based on the charge portion or the discharge portion of the cycle or a combination of both. The cycle includes charging the battery cell 212A from the energy source 102 and discharging the battery cell 212A to power the connected load 106. The extreme element cell performance value 399A may be determined at the end of the charge portion of the cycle, or the extreme element cell performance value may be determined at the end of the discharge portion of the cycle.

[0079] The extreme element cell performance value 339A may describe a voltage, amperage, temperature, or other characteristic that is too high compared to other battery elements 210B-G in the energy storage system 100, wherein the voltage that is too high may be a voltage that is at least one percent higher than the voltage of other battery elements 210B-G in the energy storage system 100. The extreme element cell voltage value 339A may describe a voltage, amperage, temperature, or other characteristic that is too low compared to other battery elements 210B-G in the energy storage system 100, wherein the voltage that is too low may be a voltage that is at least one percent lower than the voltage of other battery elements 210B-G in the energy storage system 100.

[0080] Executing the performance monitoring program 337 may further configure the battery cell performance monitoring system 1 to implement the following functions. First, determine an average component cell performance value 347A for each battery component 210A. Second, compare the cell performance value 345A-D of each battery cell 212A-D in the plurality of battery cells 212A-D of each battery component 210A with the average component cell performance value 347A. Third, identify one or more outlier battery cells 212A based on the comparison of the cell performance value 345A-D of each battery cell 212A-D with the average component cell performance value 347A.

[0081] When calculating the average extreme cell performance value 341 or the average cell performance value 347A, any averaging method can be used: calculating the mean, the median, the mode, and calculating the mean by performing a "drop one" averaging method (for example, when calculating the average to be compared with cell 212A, use cell 212B-D; when calculating the average to be compared with cell 212B, use cell 212A, CD, etc.). It can also be further decided to exclude or weight different values ​​in the averaging. The average value can also be an expected performance value based on the manufacturer's specifications for the 212A-D batteries. The expected performance value can be modified by a degradation function, for example, the expected battery cell 212A-D functionality loss is 10% per year during use, or 1% functionality loss per thousand charging cycles.

[0082] Executing the performance monitoring program 337 may further configure the battery cell performance monitoring system 1 to implement the following functions. First, determine an end-of-charge (EOC) cell performance value 351, an end-of-discharge (EOD) cell performance value 355, and a mid-discharge (MOD) cell performance value 353 of a first abnormal value battery cell 212A among one or more abnormal value battery cells 212A. Second, determine an EOC average element cell performance value 361, an EOD average element cell performance value 365, and a MOD average element cell performance value 363 of each battery element. Third, in response to the EOC cell performance value 351 substantially deviating from the EOC average element cell performance value 361, the EOD cell performance value 355 substantially deviating from the EOD average element cell performance value 365, and the MOD cell performance value 353 substantially deviating from the MOD average element cell performance value 363, characterize the first abnormal value battery 212A as a high resistance cell.

[0083] Fourth, in response to EOC cell performance value 351 substantially deviating from EOC average cell performance value 361 , EOD cell performance value 355 substantially deviating from EOD average cell performance value 365 , and MOD cell performance value 253 being substantially similar to MOD average cell performance value 363 , first outlier cell 212D is characterized as a low capacity cell.

[0084] Fifth, in response to the EOC cell performance value 351 being substantially deviated from the EOC average cell performance value 361 , and the EOD cell performance value 355 being substantially similar to the EOD average cell performance value 365 , the first outlier cell 212G is characterized as an unbalanced cell.

[0085] Figure 8 is a flow chart describing a cell and component performance monitoring protocol 800. The battery cell performance monitoring system 1 executes the performance monitoring protocol 800 to determine battery components or battery racks 210 and battery cells 212 having outlier performance.

[0086] The energy storage system 100 first runs a complete charge and discharge cycle. Test data is stored in the performance monitoring subsystem 112. In some examples, the test data is uploaded to a central data acquisition system (DAS) via Ethernet, which performs some functions of the performance monitoring subsystem 112 and the performance monitoring protocol 800. The analysis script extracts the data for analysis and performs two analysis processes: capacity and energy calculation and outlier unit identification.

[0087] The capacity in ampere-hours is calculated by integrating the current with respect to time. The energy in watt-hours is calculated by integrating the power (voltage multiplied by current) with respect to time. In this analysis method, the performance monitoring protocol 800 distinguishes between charging and discharging steps to calculate the charging and discharging capacity and energy respectively. The capacity and energy of the battery node 110A and the battery element or rack 210A are calculated by this method. However, the battery element capacity is calculated only for the battery node 110A that is identified as having a calculated low capacity. In order to perform the analysis, the battery node / element data must first be extracted into the analysis script of the performance monitoring subsystem 112. The charging and discharging start and stop times are identified, and then the current is integrated to obtain the capacity and the power is integrated to obtain the energy. The analysis is run in parallel to analyze multiple battery nodes / elements at the same time and reduce calculation time.

[0088] The capacity data of the battery nodes 110A-N and battery elements 210A-N are then used to identify outlier battery cells 212A. The outlier battery cells 212A limit the capacity of the entire battery node 110A and battery element 210A because charging or discharging is terminated once one battery cell 212A reaches the upper or lower voltage limit of the battery node 110A, battery element 210A, or energy storage system 100. However, since a single battery node 110A and multiple nodes in the energy storage system 100 may have hundreds of battery cells 212A-N, analyzing all of the battery cell data is computationally expensive. Instead, the outlier cells contained in the battery element or battery rack 210A are first identified, and then the battery cell data is deeply examined only for these problem battery elements 210A.

[0089] The cell element maximum and minimum cell voltage data (also referred to as extreme cell element cell performance values ​​339A) can be used to identify cells 210A that contain outlier cells. The cell maximum / minimum cell voltage data points (or extreme cell element cell performance values ​​339A) record the voltage of the cell 212A with the highest or lowest voltage among all the cells 212A-N in the cell element 210A. In a cell element 210C that contains non-outlier cells, the highest and lowest voltage cells will fluctuate among many cells because all cells in the cell element 210C have nearly the same voltage. In a cell element 210A that contains outlier cells, a single cell 212A may consistently have the highest and / or lowest voltage, indicating that the performance of that cell 212A is different from the other cells 212B-N.

[0090] Outlier cells 212A are most noticeable at the end of charge (EOC) and / or end of discharge (EOD) because low capacity, high resistance, or unbalanced cells will reach the cutoff voltage before other healthy cells 212B-N. EOC can be defined as the first ten minutes of charging and the last ten minutes of charging, and EOD can be defined as the first ten minutes of discharging and the last ten minutes of discharging. Check the maximum and minimum cell voltages (or extreme rack cell voltage values ​​339A) for each battery rack 210A-N at EOC and EOD. Due to the nature of the voltage curve, outliers are also more noticeable at EOC / EOD. Some batteries often have a long plateau in the middle of the discharge, with little voltage change even though the battery capacity changes a lot.

[0091] The maximum / minimum cell voltage of each battery rack 210A-N is compared to the average maximum / minimum cell voltage of all battery racks in the node to determine if the cell voltage of one battery rack 210A is "substantially different" from the cell voltages of the other battery racks 210B-N. The difference between the maximum cell voltage of each battery rack 210A-F at EOC and the average rack maximum cell voltage at EOC is calculated, as is the difference between the minimum cell voltage of each battery rack 210A-F at EOD and the average rack minimum cell voltage at EOD. The difference at EOC may be greater than 80 millivolts (mV), or the difference at EOD may be greater than 50 mV: if so, the battery rack 210A is marked as containing an outlier cell 212A. Note that these values ​​are subjective. Lower or higher thresholds may be used depending on the user's definition of "substantially different" cell voltages.

[0092] Using only the maximum / minimum cell voltages results in identifying at most one or two outlier cells 212A in a single battery rack (depending on whether the same or different cells are outliers at EOC and EOD). Using the individual cell voltage data allows all outlier cells 212A in a battery rack 210A to be identified. In this process, the voltage of each battery cell 212A-N is compared to the average cell voltage 347A for the entire battery rack 210A. The difference between the cell voltage and the average cell voltage is calculated at EOC and EOD, when the difference is most significant. The difference may be greater than 80mV at EOC or greater than 50mV at EOD: if so, the battery cell 212A is marked as an outlier.

[0093] To characterize the problem type of the outlier cell 212A, the cell voltage difference at different points during the cycle is compared. The voltage difference is calculated at EOC, EOD, and mid-discharge (MOD). The outlier cell 212A can be classified into four types: high resistance, low capacity, high imbalance, or low imbalance.

[0094] Although the previous description discloses an analysis based on performance values ​​related to voltage, similar analysis may also be performed based on performance values ​​of other characteristics, such as amperage or temperature.

[0095] Therefore, to identify an outlier battery rack 210A, in step 805, the performance monitoring protocol 800 determines the extreme element cell performance value 339A for each battery element 210A in the plurality of battery elements 210A-N. In step 810, the performance monitoring protocol 800 determines the average extreme element cell performance value 341 based on the extreme element cell performance value 339A-G of each battery element 210A-G. In step 815, the performance monitoring protocol 800 compares the extreme element cell performance value 339A-G of each battery element 210A-G with the average extreme element cell performance value 341. In step 820, based on the comparison of the extreme element cell performance value 339A-G of each battery element 210A-G with the average extreme element cell performance value 341, the performance monitoring protocol 800 identifies one or more outlier battery racks 210A.

[0096] Next, to identify outlier battery cells 212A, the performance monitoring protocol 800 determines the average component cell performance value 347A for each battery rack 210A in step 825. In step 830, the performance monitoring protocol 800 compares the cell performance value 345A of each battery cell 212A in the plurality of battery cells 212A-D of each battery component 210A with the average component cell performance value 347A. In step 835, the performance monitoring protocol 800 identifies one or more outlier battery cells 212A based on the comparison of the cell performance value 345A-D of each battery cell 212A-D with the average component cell performance value 347A.

[0097] To characterize the outlier cell 212A, at step 840, the performance monitoring protocol 800 determines an end-of-charge (EOC) cell performance value or voltage 351, an end-of-discharge (EOD) cell performance value or voltage 355, and a mid-discharge (MOD) cell performance value or voltage 353 of a first outlier cell 212A among the one or more outlier cells 212A. At step 845, the performance monitoring protocol 800 determines an EOC average cell performance value 361, an EOD average cell performance value 365, and a MOD average cell performance value 363 for each battery element 210A. Finally, to characterize the outlier cell 212A, the performance monitoring protocol 800 continues to execute steps 850, 855, and 860, and attempts to characterize the first outlier cell 212A as a high resistance cell, a low capacity cell, or an unbalanced cell.

[0098] Alternatively, prior to step 805, steps similar to steps 805, 810, 815, and 820 may be performed: however, in these alternative steps, outlier battery nodes are identified based on extreme node unit performance values. Specifically, these steps include: first, determining an extreme node component performance value for each of a plurality of battery nodes. Second, determining an average extreme node component performance value based on the extreme node component performance value for each battery node. Third, comparing the extreme node component performance value for each battery node with the average extreme node component performance value. Fourth, identifying one or more outlier battery nodes. Once one or more outlier battery nodes are identified, step 805 is continued, but step 805 is performed only in the battery components of the outlier battery nodes.

[0099] The scope of protection is limited only by the following claims. When interpreted in light of this specification and the subsequent prosecution history, the scope is intended and should be interpreted to be broad consistent with the ordinary meaning of the language used in the claims and encompassing all structural and functional equivalents. Notwithstanding the foregoing, no claims are intended to include subject matter that does not comply with the requirements of Sections 101, 102, or 103 of the Patent Act, nor should they be interpreted in such a manner. Any unintended inclusion of such subject matter is not claimed herein.

[0100] Except as stated immediately above, nothing stated or shown is intended or should be construed as contributing to the public any component, step, feature, object, benefit, advantage, or equivalent, whether or not recited in the claims.

[0101] It should be understood that the terms and expressions used herein have the ordinary meaning of the terms and expressions associated with the corresponding areas of investigation and study, unless a specific meaning is otherwise specified herein. Relational terms, such as first and second, etc., are used only to distinguish one entity or action from another entity or action, and do not necessarily require or imply any actual relationship or order between these entities or actions. The terms "comprises", "comprising", "includes", "including" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes or includes a series of elements or steps does not include only these elements or steps, but may also include other elements or steps that are not explicitly listed or inherent to the process, method, article or apparatus. An element preceded by "a" or "an" does not, without further limitation, exclude the presence of other identical elements in the process, method, article or apparatus that includes the element.

[0102] Furthermore, as can be seen from the foregoing detailed description, various features are grouped together in different examples in order to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that the claimed examples require more features than are expressly recited in each claim. Rather, as the following claims reflect, the subject matter to be protected is less than all features of any single disclosed example. Therefore, the following claims are hereby incorporated into the detailed description, with each claim standing on its own as a separate claimed subject matter.

[0103] Although the foregoing describes what is considered to be the best mode and / or other examples, it should be understood that various modifications may be made therein, and the subject matter disclosed herein may be implemented in various forms and examples and may be applied to numerous applications, only some of which are described herein. The following claims are intended to claim any and all modifications and variations that fall within the true scope of the inventive concept.

Claims

1. A battery cell performance monitoring system, comprising: An energy storage system comprising at least one inverter and a plurality of battery nodes, wherein each battery node comprises a plurality of battery racks, and each battery rack comprises a respective plurality of battery cells; processor; as well as A memory coupled to the processor, wherein the memory includes a performance monitoring program, and when the performance monitoring program is executed, the battery cell performance monitoring system is configured to implement functions, including the following functions: Determine the extreme rack unit voltage value for each battery rack, determining an average extreme rack unit voltage value according to the extreme rack unit voltage value of each battery rack, comparing the extreme rack unit voltage value of each battery rack with the average extreme rack unit voltage value, and One or more outlier battery racks are identified based on a comparison of the extreme rack unit voltage value of each battery rack with the average extreme rack unit voltage value.

2. The battery cell performance monitoring system according to claim 1, wherein: The determination of the extreme rack unit voltage value is based on the charging portion or the discharging portion of the cycle or a combination of both.

3. The battery cell performance monitoring system according to claim 2, wherein: The determination of the extreme rack unit voltage value is performed at the end of the charging portion.

4. The battery cell performance monitoring system according to claim 3, wherein: The extreme rack unit voltage value describes a voltage that is too high compared to other battery racks in the energy storage system.

5. The battery cell performance monitoring system according to claim 2, wherein: The determination of the extreme rack unit voltage value is performed at the end of the discharge portion.

6. The battery cell performance monitoring system according to claim 5, wherein: The extreme rack unit voltage value describes a voltage that is too low compared to other battery racks in the energy storage system.

7. The battery cell performance monitoring system according to claim 1, wherein: Executing the performance monitoring program further configures the battery cell performance monitoring system to implement functions, including the following functions: determining an average rack unit voltage value for each battery rack; comparing a cell voltage value of each battery cell of a plurality of battery cells of each battery rack with the average rack cell voltage value; One or more outlier battery cells are identified based on the comparison of the cell voltage value of each battery cell with the average rack cell voltage value.

8. The battery cell performance monitoring system according to claim 7, wherein: Executing the performance monitoring program further configures the battery cell performance monitoring system to implement functions, including the following functions: determining an end-of-charge (EOC) cell voltage, an end-of-discharge (EOD) cell voltage, and a mid-discharge (MOD) cell voltage of a first outlier cell among the one or more outlier battery cells; Determine the EOC average rack unit voltage value, the EOD average rack unit voltage value, and the MOD average rack unit voltage value of each battery rack; The first outlier cell is characterized as a high resistance cell in response to: i) the EOC unit voltage substantially deviates from the EOC average rack unit voltage value, ii) the EOD unit voltage deviates substantially from the EOD average rack unit voltage value, and iii) the MOD unit voltage substantially deviates from the MOD average rack unit voltage value.

9. The battery cell performance monitoring system according to claim 7, wherein: Executing the performance monitoring program further configures the battery cell performance monitoring system to implement functions, including the following functions: determining an end-of-charge (EOC) cell voltage, an end-of-discharge (EOD) cell voltage, and a mid-discharge (MOD) cell voltage of a first outlier cell among the one or more outlier battery cells; Determine the EOC average rack unit voltage value, the EOD average rack unit voltage value, and the MOD average rack unit voltage value of each battery rack; The first outlier cell is characterized as a low capacity cell in response to: i) the EOC unit voltage substantially deviates from the EOC average rack unit voltage value, ii) the EOD unit voltage deviates substantially from the EOD average rack unit voltage value, and iii) the MOD unit voltage is substantially similar to the MOD average rack unit voltage value.

10. The battery cell performance monitoring system according to claim 7, wherein: Executing the performance monitoring program further configures the battery cell performance monitoring system to implement functions, including the following functions: determining an end-of-charge (EOC) cell voltage and an end-of-discharge (EOD) cell voltage of a first outlier cell among the one or more outlier battery cells; Determine the EOC rack voltage and EOD rack voltage of each battery rack; The first outlier unit is characterized as an unbalanced unit in response to: i) the EOC unit voltage is substantially different from the EOC frame voltage and the EOD unit voltage is substantially similar to the EOD frame voltage, or The EOC cell voltage is substantially similar to the EOC frame voltage and the EOD cell voltage is offset from the EOD frame voltage.

11. A method comprising: determining an extreme element unit performance value for each battery element in the plurality of battery elements; Determining an average extreme element unit performance value based on the extreme element unit performance value of each battery element; comparing the extreme element unit performance value of each battery element with the average extreme element unit performance value; as well as One or more outlier battery elements are identified based on a comparison of the extreme element cell performance value of each battery element with the average extreme element cell performance value.

12. The method according to claim 11, wherein: The determination of the extreme element unit performance value is based on the charging portion or the discharging portion of the cycle or a combination of both.

13. The method according to claim 12, wherein: The determination of the extreme element unit performance value is performed at the end of the charging portion.

14. The method according to claim 13, wherein: The extreme element cell performance value describes a voltage that is too high compared to other battery racks in the energy storage system.

15. The method according to claim 12, wherein: The determination of the extreme element unit performance value is performed at the end of the discharge portion.

16. The method according to claim 11, further comprising: determining an average element unit performance value for each battery element; comparing a cell performance value of each battery cell of a plurality of battery cells of each battery element with the average element cell performance value; One or more outlier battery cells are identified based on the comparison of the cell performance value of each battery cell with the average component cell performance value.

17. The method according to claim 16, further comprising: determining an end-of-charge (EOC) cell performance value, an end-of-discharge (EOD) cell performance value, and a mid-discharge (MOD) cell performance value of a first outlier cell among the one or more outlier battery cells; Determining an EOC average component unit performance value, an EOD average component unit performance value, and an MOD average component unit performance value for each battery component; The first outlier cell is characterized as a high resistance cell in response to: iv) said EOC cell performance value substantially deviates from said EOC average component cell performance value, v) the EOD unit performance value substantially deviates from the EOD average element unit performance value, and vi) the MOD unit performance value substantially deviates from the MOD average element unit performance value.

18. The method according to claim 16, further comprising: determining an end-of-charge (EOC) cell performance value, an end-of-discharge (EOD) cell performance value, and a mid-discharge (MOD) cell performance value of a first outlier cell among the one or more outlier battery cells; Determining an EOC average component unit performance value, an EOD average component unit performance value, and an MOD average component unit performance value for each battery component; The first outlier cell is characterized as a low capacity cell in response to: iv) said EOC cell performance value substantially deviates from said EOC average component cell performance value, v) the EOD unit performance value substantially deviates from the EOD average element unit performance value, and vi) the MOD unit performance value is substantially similar to the MOD average element unit performance value.

19. The method according to claim 17, further comprising: determining an end of charge (EOC) cell performance value and an end of discharge (EOD) cell performance value of a first outlier cell among the one or more outlier battery cells; Determining an EOC component performance value and an EOD component performance value of each battery component; The first outlier unit is characterized as an unbalanced unit in response to: ii) the EOC unit performance value is substantially different from the EOC component performance value, and the EOD unit performance value is substantially similar to the EOD component performance value, or iii) the EOC unit performance value is substantially similar to the EOC component performance value, and the EOD unit performance value is substantially different from the EOD component performance value.

20. A battery cell performance monitoring system, comprising: An energy storage system comprising at least one inverter and a plurality of battery nodes, wherein each battery node comprises a plurality of battery elements, and each battery element comprises a respective plurality of battery cells; processor; as well as A memory coupled to the processor, wherein the memory includes a performance monitoring program, and when the performance monitoring program is executed, the battery cell performance monitoring system is configured to implement functions, including the following functions: Determine the extreme cell voltage value of each battery cell, Determine an average extreme cell voltage value according to the extreme cell voltage value of each battery element, comparing the extreme cell element voltage value of each battery element with the average extreme cell element voltage value, and One or more outlier battery elements are identified based on a comparison of the extreme element cell voltage value of each battery element with the average extreme element cell voltage value.

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