System and method for determining determination of battery

Abstract

Systems and methods for estimating battery degradation of a battery energy storage system (BESS) are disclosed. An iterative process is performed within a predefined period of time divided into a plurality of iterations. For each iteration, an average temperature of the BESS is determined by inputting a state of health (SOH) and a charge rate into an average temperature lookup table (LUT). The SOH for the next iteration is determined by inputting the determined average temperature into a set of cell degradation equations. A charge rate for the next iteration is derived from a usage profile defining charge and discharge cycles over a predefined time period and including power and SOC over the predefined time period. The SOH of the BESS within the predefined time period may then be displayed on the user interface.

Description

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to U.S. Provisional Application 63 / 601,603, filed November 21, 2023, the disclosure of which is incorporated herein by reference. Technical Field

[0003] This disclosure relates to the management of battery energy storage systems (BESS), and more specifically to the accurate determination of the state of health (SOH) of the BESS. Background Technology

[0004] Battery-Energy-Sustainable Storage (BESS) has become a key component of modern energy management systems. With the increasing integration of renewable power sources such as wind and solar (which are inherently intermittent), energy storage solutions are essential for ensuring grid stability and efficient power distribution. BESS technology allows for the storage of excess electricity during periods of low demand and the release of scarce electricity during periods of high demand, thereby optimizing energy use (by reducing cuts to solar and wind power) and decreasing reliance on fossil fuel-based power generation such as gas turbines. This capability is particularly valuable as the global transition to clean energy accelerates and as intermittent power sources take up an increasingly larger share of the electricity supply structure.

[0005] Because individual battery cells degrade over time (also known as "degradation"), accurately predicting the State of Health (SOH) at a specific point in the battery's lifespan is crucial. SOH represents the overall condition of a battery after charge and discharge cycles, compared to its condition when it is a new battery or at the beginning of its life (BOL). SOH is typically expressed as a percentage and takes into account factors such as battery capacity, internal resistance, and ability to retain charge. SOH helps determine the remaining lifespan of a battery and its efficiency in storing and delivering power. Summary of the Invention

[0006] Therefore, this disclosure describes a system and method for estimating the State of Energy (SOH) of a BESS over a time period. This system and method can provide insights into BESS capacity decay based on historical site usage and can offer users the opportunity to change (or not change) their usage profiles for BESS sites already in use. Furthermore, this system and method can provide advance insights into BESS capacity decay for future site usage profiles and can therefore be used as an opportunity predictor for BESS sites not yet in use.

[0007] According to one aspect, the present disclosure relates to a system for estimating battery degradation of a BESS, the system comprising: a controller comprising one or more processing modules and one or more non-transitory memory storage modules storing computing instructions configured to, when executed by the one or more processing modules: (a) perform an iterative process over a predefined time period, wherein the predefined time period is divided into a plurality of iterations, wherein each iteration of the plurality of iterations comprises: (1) determining an average temperature of the BESS for a current iteration of the plurality of iterations by inputting into an average temperature lookup table (LUT): a state of health (SOH) of the BESS for the current iteration and a charge rate of the BESS for the current iteration; and (2) inputting the determined average temperature into a set of cell degradation equations to determine the SOH of the BESS for a next iteration of the plurality of iterations.

[0008] In some cases, the average temperature LUT is generated by inputting different combinations of SOH and charge rate into a thermal model.

[0009] In some cases, the controller is configured to repeat steps (1) and (2) until a last iteration of the iterative process is performed.

[0010] In some cases, the controller is configured to instruct a user interface (UI) to display a time series, the time series showing the SOH determined for each iteration over the predefined time period, wherein a horizontal axis of the time series represents time and a vertical axis of the time series represents SOH.

[0011] In some cases, the SOH for the first iteration is an initial SOH of the BESS.

[0012] In some cases, the charge rate of the BESS for the current iteration is determined based on a usage profile of the BESS over the predefined time period and a rated energy capacity of the BESS.

[0013] In some cases, the usage profile of the BESS over the predefined time period is derived from historical usage data of the BESS.

[0014] In some cases, the usage profile of the BESS over the predefined time period is derived from future usage data of the BESS.

[0015] In some cases, wherein the average temperature LUT includes an average cycle temperature that accounts for charging and discharging cycles of the BESS and an average rest temperature based on time when the BESS is not undergoing charging and discharging cycles.

[0016] In some cases, the average temperature LUT for the current iteration is generated based on the cell type and module type of the BESS.

[0017] According to another aspect, the present disclosure relates to a method for estimating battery degradation of a BESS, the method comprising: (a) performing an iterative process over a predefined time period, wherein the predefined time period is divided into a plurality of iterations, wherein each iteration of the plurality of iterations comprises: (1) determining an average temperature of the BESS for a current iteration of the plurality of iterations by inputting into an average temperature lookup table (LUT): a state of health (SOH) of the BESS for the current iteration and a charge rate of the BESS for the current iteration; and (2) inputting the determined average temperature into a set of cell degradation equations to determine a SOH of the BESS for a next iteration of the plurality of iterations.

[0018] It should be noted that the technical effects obtainable by the present disclosure are not limited to the above-mentioned effects, and other effects not mentioned herein will be clearly understood by those skilled in the art from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0019] The accompanying drawings illustrate exemplary aspects of the present disclosure and together with the following detailed description, provide further understanding of the technical spirit of the present disclosure. However, the present disclosure should not be construed as being limited to the accompanying drawings.

[0020] Figure 1 is a perspective view schematically showing a configuration of a battery container according to an aspect of the present disclosure.

[0021] Figure 2 is a perspective view schematically showing a form in which some components of a battery container according to an aspect of the present disclosure are separated or moved.

[0022] Figure 3 is a view showing an internal configuration of a battery container viewed from above according to an aspect of the present disclosure.

[0023] Figure 4 is a flowchart illustrating an implementation of a system and / or method for estimating battery degradation of a BESS according to an aspect of the present disclosure.

[0024] Figure 5 is a flowchart illustrating generation of an average temperature lookup table according to an aspect of the present disclosure.

[0025] Figure 6 is a flowchart illustrating an implementation of a system and / or method for estimating battery degradation of a BESS according to an aspect of the present disclosure.

[0026] Figure 7is a flowchart illustrating an implementation of a mode classifier for classifying data points in a BESS usage profile as peak shifting, frequency regulation, or rest, according to one aspect of the present disclosure.

[0027] Figure 8 is a graph showing an estimation of SOH of a BESS over a period of time, according to one aspect of the present disclosure.

[0028] Figure 9 is a schematic diagram of a controller implementing a system and / or method for estimating battery degradation of a BESS, according to one aspect of the present disclosure. DETAILED DESCRIPTION

[0029] The present disclosure can be altered in various ways and have various aspects, and the specific aspects disclosed in detail herein are to facilitate the understanding of the present disclosure for those skilled in the art.

[0030] Therefore, it should be understood that the present disclosure is not intended to be limited to the particular aspects disclosed herein but is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure.

[0031] In the present application, it should be understood that terms such as "include" or "have" are intended to indicate that there are the features, numbers, steps, operations, components, parts or combinations thereof described in the specification, and they do not exclude the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0032] Figure 1 is a perspective view schematically showing a configuration of a battery container 1000 of a BESS, according to one aspect of the present disclosure. Figure 2 is a perspective view schematically showing a form in which some components of the battery container 1000 are separated or moved, according to one aspect of the present disclosure. Figure 3 is a view showing an internal configuration of the battery container 1000 viewed from above, according to one aspect of the present disclosure.

[0033] Referring to Figures 1 to 3 , the battery container 1000 according to the present disclosure includes a battery rack 100, a container housing 200, a main connector 300, and a main busbar 400.

[0034] The battery rack 100 can include a plurality of battery modules 110. Here, each battery module 110 can be configured in a form in which a plurality of battery cells (secondary batteries) are accommodated in a module case. Also, the battery modules 110 can be stacked in one direction, such as in the up-down direction, to form the battery rack 100. Specifically, the battery rack 100 can include a rack case to facilitate stacking of the battery modules 110. In this case, the plurality of battery modules 110 can be accommodated in respective storage spaces provided in the rack case to form a module stack. In some aspects, the battery modules 110 can be arranged in other configurations, such as side-by-side or in a matrix style. The rack case can include features like cooling channels or structural reinforcements to support the weight of the stacked modules. In some cases, the battery rack 100 can incorporate sensors to monitor temperature, voltage, or other parameters of the battery modules 110.

[0035] The battery modules 110 included in the battery rack 100 can also include a control unit, such as a battery management system (BMS) for each group or certain groups. For example, a separate group BMS can be provided for each battery module 110. In this case, each battery module 110 can be referred to as a battery pack. That is, the battery rack 100 can be considered to include a plurality of battery packs. In various descriptions below, the battery modules 110 can be replaced with battery packs. In some cases, the battery rack 100 can incorporate sensors to monitor parameters like temperature, voltage, or current of the battery modules 110. The BMS of each battery module or group can communicate with a higher-level rack BMS to coordinate battery rack performance and safety.

[0036] One or more battery racks 100 can be included in the battery container 1000. Specifically, a plurality of battery racks 100 can be included in the battery container 1000. Also, the plurality of battery racks 100 can be disposed in at least one direction, for example, in the horizontal direction. For example, eight battery racks 100 can be included in the battery container 1000, and the plurality of battery racks 100 can be arranged in the left-right direction (X-axis direction) inside the battery container 1000. When a plurality of battery racks 100 are included, a separate control unit, such as a rack BMS, can be provided for each battery rack 100. In this case, the rack BMS can be connected to a plurality of group BMSs to exchange data and control the plurality of group BMSs. Meanwhile, when the battery container 1000 includes at least one rack BMS, the rack BMS can be connected to a separate control device provided outside the battery container 1000, such as a control container. Also, the control container can be connected to the rack BMS or group BMS of the battery container 1000 to control or exchange data with them.

[0037] An empty space can be formed inside the container housing 200. Furthermore, the container housing 200 can accommodate the battery holder 100 within the internal space. More specifically, the container housing 200 can be formed as follows: Figure 1 The container housing 200 has an approximate cuboid shape as shown in the diagram. In this case, the container housing 200 may include an upper housing 201, a lower housing, a front housing 203, a rear housing, a left housing 205, and a right housing surrounding the internal space. Furthermore, the container housing 200 can accommodate the battery holder 100 within the internal space defined by these six unit housings.

[0038] The container shell 200 can be made of a material that ensures a certain level of rigidity and stably protects the internal components from external physical and chemical factors. For example, the container shell 200 can be made of, or contain, metallic materials such as steel, aluminum, or titanium. In some aspects, the container shell 200 can be constructed of composite materials such as carbon fiber reinforced polymers or glass fibers, which provide a high strength-to-weight ratio. In areas exposed to harsh environmental conditions, the shell can also incorporate corrosion-resistant alloys such as stainless steel or galvanized steel. In some cases, the container shell 200 can utilize combinations of materials, such as a steel frame combined with aluminum plates, to balance strength, weight, and cost considerations. Furthermore, the shell can include specialized coatings or treatments, such as powder coating or anodizing, to enhance its durability and weather resistance.

[0039] The size of the container shell can be the same as or similar to that of a shipping container. Furthermore, the container shell can conform to pre-defined shipping container standards such as ISO standards. For example, the container shell can be designed to have the same or similar dimensions as a 20-foot or 40-foot container. However, the size of the container shell can be appropriately designed depending on the circumstances. Specifically, the size or shape of the container shell can be set in various ways according to the construction scale, shape, form, etc., of the system in which the battery container is applied (such as an energy storage system). This disclosure is not limited to the size or shape of the container shell. In some aspects, for example, the container shell can have other shapes, such as cylindrical, spherical, or custom polygonal shapes. The shell can also be modular, allowing for expansion or contraction based on capacity requirements. In some cases, the container shell can incorporate features such as a sloping roof for drainage or reinforced walls for increased durability in harsh environments.

[0040] The main connector 300 can be configured to be electrically connected to the outside. That is, relative to the battery container 1000, the main connector 300 can be configured to be connected to another component outside the battery container 1000, such as another battery container 1000 or a control container equipped with a control unit (such as a battery system controller (BSC)).

[0041] The main connector 300 may be located on at least one side of the container housing 200. For example, the main connector 300 may be located on the left or right side of the container housing 200. Furthermore, multiple main connectors 300 may be included in the battery container 1000. For example, as... Figure 2 and Figure 3 As shown, the main connector 300 may include two main connectors 300, namely the first connector 301 and the second connector 302.

[0042] Multiple main connectors 300 can be located on different sides of the container housing 200. Furthermore, multiple main connectors 300 can be located on opposite sides of the container housing 200. For example, as... Figures 1 to 3 As shown, the first connector 301 and the second connector 302 can be disposed on the left and right sides of the container housing 200, respectively. In some aspects, the main connector 300 can be located on the top or bottom plate of the container housing 200. In some cases, the main connector 300 can be located at a corner or edge of the container housing 200. The main connector 300 can also be arranged in various configurations, such as staggered arrangement or vertical arrangement along the sides of the container housing 200. In some implementations, additional main connectors can be included on the front or back of the container housing 200 to provide additional connection options.

[0043] The main busbar 400 can be configured to transmit power. Specifically, the main busbar 400 can serve as a path for transmitting charging and discharging power to the battery rack 100 included in the corresponding battery container 1000. For this purpose, the main busbar 400 can be electrically connected to each terminal of the battery module 110 disposed in the battery rack 100. Furthermore, the main busbar 400 can also be connected to the main connector 300. Therefore, the main busbar 400 can serve as a path for transmitting charging power from the main connector 300 to the battery module 110. Additionally, the main busbar 400 can serve as a path for transmitting discharging power from the battery module 110 to the main connector 300.

[0044] Furthermore, the main busbar 400 can serve as a power transmission line between multiple main connectors 300. For this purpose, different ends of the main busbar 400 can be connected to different main connectors 300. For example, the main busbar 400 can be a power line extending in one direction (e.g., in a left-right direction). In this case, both ends of the main busbar 400 can be connected to different main connectors 300, such as the first connector 301 and the second connector 302. Additionally, the main busbar 400 can serve as a path for transmitting power between different main connectors 300 (e.g., between the first connector 301 and the second connector 302).

[0045] The main busbar 400 may include two unit busbars, namely a positive busbar 410 and a negative busbar 420, for use as power transmission paths. The positive busbar 410 may be connected to the positive terminal of the battery rack 100 or the positive terminal of the included battery module 110. Similarly, the negative busbar 420 may be connected to the negative terminal of the battery rack 100 or the negative terminal of the included battery module 110.

[0046] Furthermore, the main connector 300 can be respectively disposed at each end of the positive busbar 410 and the negative busbar 420. For example, the first connector 301 and the second connector 302 can be respectively disposed at the left and right ends of the positive busbar 410. The first connector 301 and the second connector 302 disposed at both ends of the positive busbar 410 can be positive connectors 310. Furthermore, the first connector 301 and the second connector 302 can be respectively disposed at the left and right ends of the negative busbar 420. The two connectors disposed at both ends of the negative busbar 420, namely the first connector 301 and the second connector 302, can both be negative connectors 320.

[0047] Furthermore, the battery container 1000 according to this disclosure may include a cable protection sleeve CC. The cable protection sleeve CC may be configured to surround cables connected to the battery container 1000. For example, multiple power cables may be connected to a terminal busbar TB to transmit power. In this case, the cable protection sleeve CC may be located at one end (e.g., the lower end) of the terminal protection sleeve CC to protect the multiple power cables connected to the terminal busbar TB. Alternatively, the battery container 1000 may be connected to data cables to exchange various data with other external components (such as a control container 2000). In this case, the cable protection sleeve CC may be configured to protect data cables connected to the battery container 1000 from external damage.

[0048] Specifically, the cable protection sleeve CC may include a cable tray CC1 and a tray cover CC2. The cable tray CC1 may include a main body portion attached to the outer wall of the container housing 200 and a side wall portion projecting outward from the edge of the main body portion. For example, the side wall portion may be formed to project to the left from the front and rear edges of the main body portion. The tray cover CC2 may be coupled to the end of the side wall portion projecting from the main body portion of the cable tray CC1 to form an empty space therein together with the main body portion and the side wall portion. Specifically, this empty space may be formed in a hollow shape. Therefore, cables can extend outward from the battery container 1000 through the empty space of the cable protection sleeve CC. Furthermore, the cables extending to the outside may be connected to other external components, such as the control container 2000 or another battery container 1000.

[0049] According to this aspect, by minimizing the exposure of cables extending from the battery container 1000 to the outside, the cables can be protected and prevented from damage or breakage. Furthermore, the cable protection sleeve CC is configured to have a cavity formed downwards on the side surface of the container housing, allowing the cables housed inside to be exposed downwards to the outside. In this configuration, it facilitates the installation, management, and underground burial of the cables.

[0050] Furthermore, the battery container 1000 according to this disclosure may also include, for example: Figure 1 and Figure 2 The air conditioning module 600 shown is configured to regulate the air inside the container housing 200. Specifically, the air conditioning module 600 can control the temperature of the internal air. Furthermore, the air conditioning module 600 can be configured to circulate the air inside the container housing 200 to control the temperature of various electronic devices (such as the battery rack 100 or the BMS rack) included in the battery container 1000 within a certain range. Specifically, the air conditioning module 600 can cool the air inside the container housing 200. For example, the air conditioning module 600 can be configured to absorb heat from the air inside the container housing 200 and discharge it to the outside. Additionally, the air conditioning module 600 can be configured to remove dust or foreign matter from the air inside the container housing 200.

[0051] Typically, the air conditioning module 600 may include at least one HVAC (heating, ventilation, and air conditioning) system. For example, the battery container 1000 according to this disclosure may include four HVAC systems. The HVAC system allows air to circulate within the container housing 200. In this case, the temperature of the battery rack 100 can be reduced, and the temperature difference between the battery racks 100 or between the battery modules 110 included in the container housing 200 can be reduced.

[0052] Specifically, the container shell 200 may include at least one door (such as one provided by a door). Figure 1 and Figure 2 (As indicated by E in the diagram) to facilitate the installation, maintenance, or repair of the battery rack 100. For example, the container housing 200 may have eight doors E on the front. In addition, two doors E may open and close in pairs as casement windows. Furthermore, such doors E may be additionally provided on another part of the container housing 200 (e.g., on the rear surface).

[0053] In this way, when a door E is provided for the container housing 200, the HVAC system can be installed in the door E of the container housing 200. For example, when two doors E are configured as a pair, the HVAC system can be installed on one of the two doors E. Furthermore, the HVAC system (i.e., the air conditioning module 600) can be configured to penetrate the container housing 200, specifically the door E. In this case, one surface of the air conditioning module 600 can be exposed to the outside of the container housing 200, while the other surface of the air conditioning module 600 can be exposed to the inside of the container housing 200. Therefore, the inner surface of the air conditioning module 600 can contact the internal air of the container housing 200 to absorb heat, while the outer surface of the air conditioning module 600 can contact the external air of the container housing 200 to dissipate heat.

[0054] The air conditioning module 600 can be configured to prevent direct contact between internal and external air. That is, the air conditioning module 600 can be configured to prevent internal air from being exhausted to the outside and to prevent external air from being introduced into the inside. Therefore, even if the temperature inside the container housing 200 rises, the air conditioning module 600 can only absorb heat from the internal air and discharge the heat to the outside, without directly venting the internal air to the outside. According to this aspect, even if a fire or toxic gas is generated inside the battery container 1000, it can prevent the fire or toxic gas from being emitted to the outside and causing damage to other equipment (such as other nearby battery containers 1000) or to personnel outside.

[0055] Furthermore, the battery container 1000 according to this disclosure may also include, for example: Figure 1 and Figure 2 The ventilation module 700 is shown. The ventilation module 700 can be configured to exhaust gas inside the container housing 200 to the outside. Furthermore, the ventilation module 700 can introduce outside air into the container housing 200. Therefore, the ventilation module 700 can be used as a ventilation device. That is, the ventilation module 700 can exchange gas between the inside and outside of the container housing 200 or circulate gas between the inside and outside of the container housing 200.

[0056] Specifically, the ventilation module 700 can be configured to operate under abnormal conditions, such as when ventilation gas or fire is generated in a specific battery module 110. Furthermore, when gas is generated inside the container housing 200 due to thermal runaway of the battery rack 100, the ventilation module 700 can be configured to vent the gas to the outside. Additionally, the ventilation module 700 can be configured to be in a closed state under normal conditions and switch to an open state under abnormal conditions such as thermal runaway. In this case, since the ventilation module 700 performs active ventilation, the ventilation module 700 can be referred to as an AVS (Active Ventilation System) or a system including such a system.

[0057] In this way, larger problems, such as an explosion due to increased internal pressure in the battery container 1000, can be prevented. Furthermore, by rapidly venting flammable gases inside the container housing 200 to the outside, the likelihood of a fire in the battery container 1000 can be reduced or the occurrence of a fire can be delayed, and the size of the fire may be minimized.

[0058] In one aspect where both the ventilation module 700 and the air conditioning module 600 are included, the ventilation module 700 may not operate under normal circumstances, but the air conditioning module 600 may operate. In this case, during cooling, the ventilation module 700 can prevent foreign objects or moisture from flowing into the container housing 200. According to this aspect, since the air conditioning module 600, ventilation module 700, etc., are included in the battery container 1000, the air conditioning module 600 or ventilation module 700 can be transported and installed together simply by transporting and installing the battery container 1000. Therefore, the on-site installation work for installing the energy storage system can be minimized, and the connection structure can be simplified.

[0059] In this respect, the air conditioning module 600 and / or the ventilation module 700 can operate under the control of the control container 2000. Alternatively, the air conditioning module 600 and / or the ventilation module 700 can be controlled by a control unit included in the battery container 1000, such as a rack BMS for controlling the charging / discharging operation of each battery rack 100 or another separate control unit.

[0060] Furthermore, the battery container 1000 according to this disclosure may include at least one sensor and provide sensing information to a rack-mounted BMS, another separate control unit, or a control container 2000 included in the battery container 1000. For example, a temperature sensor, a smoke sensor, an H2 sensor, and / or a CO sensor may be included in the battery container 1000. In this case, the operation of the air conditioning module 600 and / or the ventilation module 700 can be controlled based on the information sensed by these sensors. The battery container 1000 may also include a fire connector 810 connected to a fire suppression module (not shown).

[0061] Figure 4This is a flowchart 1100 illustrating an implementation of a system and / or method for estimating battery degradation (BESS) according to one aspect of this disclosure. Flowchart 1100 can be implemented as an iterative process within a predefined time period divided into multiple iterations (corresponding to time intervals). The predefined time period can be, for example, a day, a month, a year, five years, or twenty years, but this disclosure is not limited thereto and can be defined as any time unit. Each iteration in the multiple iterations can correspond to a time interval, such as one minute, one hour, one day, or one month, but this disclosure is not limited thereto and can be defined as any time unit. Typically, shorter iterations (time intervals) can produce more accurate SOH calculations, but require more computational resources.

[0062] BESS configuration 1102 may include rated (e.g., specified or nameplate) energy capacity (available in direct current [DC] form prior to any conversion to alternating current [AC]), cell type and module type, and initial state of equilibrium (SOH). The calculations described herein can vary based on parameters defined in BESS configuration 1102, such as cell degradation equation 1114 and thermal model 1206 (reference). Figure 5 (Further description).

[0063] The usage profile 1104 can define the charge and discharge cycles of the BESS within a predefined time period, such as the depth of discharge (DOD) (and therefore SOC) and charge rate (charge / discharge power) for each iteration of the BESS. In some cases, the usage pattern 1104 within the predefined time period is based on historical usage data of the BESS (e.g., data from BESS already in use, which can then be used to predict future battery degradation by assuming that trends from past usage profiles will continue in the future). In some cases, the usage profile 1104 within the predefined time period is derived from future usage data of the BESS (e.g., users can upload data from BESS not yet in use to predict future battery degradation). The usage profile 1104 can be categorized as implementing low usage patterns, medium usage patterns, and / or high usage patterns.

[0064] Low usage mode may involve a relatively low depth of discharge (DOD) such that the battery's state of charge (SOC) is discharged less than about 25% during a discharge cycle and charged less than about 25% during a charge cycle, and / or may involve a relatively low charging rate such that the output power during a discharge cycle is less than about 25% of the rated power and the input power during a charge cycle is less than about 25% of the rated power.

[0065] The usage mode may involve a relatively moderate depth of discharge (DOD) such that the battery's state of charge (SOC) is discharged greater than about 25% and less than about 75% during a discharge cycle and charged greater than about 25% and less than about 75% during a charge cycle, and / or may involve a relatively moderate charging rate such that the output power during a discharge cycle is greater than about 25% and less than about 75% of the rated power, and the input power during a charge cycle is greater than about 25% and less than about 75% of the rated power.

[0066] High usage modes may involve a relatively large depth of discharge (DOD) such that the battery's state of charge (SOC) is discharged greater than about 75% during a discharge cycle and charged greater than about 75% during a charge cycle, and / or may involve a relatively high charging rate such that the output power during a discharge cycle is greater than about 75% of the rated power and the input power during a charge cycle is greater than about 75% of the rated power.

[0067] It should be noted that the use of profile 1104 allows for the combination of low, medium, and high usage modes. For example, in some cases, the battery can be discharged significantly faster (e.g., more than 75% of its rated capacity) compared to when it is charged (e.g., less than about 25% of its rated capacity), which can help maintain the battery's state of harmonic equilibrium (SOH) by reducing temperature-based degradation.

[0068] Each iteration of the iterative process implemented in flowchart 1100 may include determining (i.e., retrieving or referencing) the average temperature of the BESS by inputting the SOH 1106 for the current iteration and the charge rate 1108 for the current iteration into the average temperature LUT 1112. The average temperature LUT 1112 may be generated (i.e., constructed) prior to the execution of the iterative process in flowchart 1100 and may be a file storing tabular data (e.g., CSV, XLS, XML, JSON, SQL, etc.). The generation of LUT 1112 will reference... Figure 5 Further details are provided. The charging rate 1108 for the current iteration can be determined based on the use of profile 1104. Except for the first iteration, the SOH 1106 for the current iteration can be determined based on the output of monomer degradation equation 1114.

[0069] For the first iteration, an initial SOH (e.g., 100% or greater than about 95%) can be used for SOH 1106. The initial SOH of BESS can be measured by comparing the measured energy capacity to the rated (i.e., specified or nameplate) energy capacity, or by comparing the measured charge capacity to the rated charge capacity. For example, if the measured energy capacity is 500 MWh and the rated energy capacity is 525 MWh, the initial SOH is about 95.2%.

[0070] Each iteration of the iterative process executed in flowchart 1100 may include inputting the average temperature determined according to LUT 1112 into a set of monomer degradation equations 1114 to determine the SOH 1116 for the next iteration of the multiple iterations. Except for the first iteration (where the initial SOH is used), the SOH 1116 determined in the previous iteration becomes the SOH 1106 for the current iteration.

[0071] For example, the set of degradation equations 1114 includes an Arrhenius-based equation that models several chemical degradation processes (such as electrolyte decomposition, solid electrolyte interface layer growth, lithium plating, and transition metal dissolution) as generalized equations:

[0072] in, For changes in health status, The current iteration time is given by E, k is the generalized rate constant, and E is the time length of the current iteration. a E is the generalized activation energy, R is the universal gas constant, and T is the average temperature of the BESS for the current iteration, as determined by LUT 1112. a and k can be fitting parameters based on experimental data and can reflect the average sensitivity of several temperature-related degradation processes. However, methods based on Arrhenius equations can lead to oversimplification, as a single equation may fail to capture the subtle behavior of individual degradation mechanisms. For example, some reactions may dominate at low temperatures (e.g., lithium plating), while others may dominate at high temperatures (e.g., electrolyte degradation). Other examples of degradation equations 1114 may include empirical degradation models that directly link temperature to SOH loss and / or consider both cycling and calendar aging.

[0073] The following steps can be repeated until the last iteration is performed: (1) input SOH 1106 and charge rate 1108 into LUT 1112 to determine the average temperature; and (2) input the determined average temperature into the set of monomer degradation equations 1114 to determine SOH 1116.

[0074] In some cases, based on pattern classifier 1110 (reference) Figure 7(Described in more detail) Adjusting the SOH determined by the monomer degradation equation 1114, this pattern classifier can classify each iteration (time interval or data point) using profile 1104 into a peak shift (PS) interval, a frequency regulation (FR) interval, or a rest interval. Peak shift involves charging the BESS during times of low grid demand (e.g., peak power supply from solar at midday) and discharging the BESS during times of high grid demand (e.g., peak demand at night). Frequency regulation involves adjusting the charging / discharging of the BESS to maintain the grid frequency at a stable level (typically 50 or 60 Hz), which prevents power outages. Because the BESS is charged and discharged frequently during FR intervals, the reduction in SOH may be more significant compared to PS intervals, and therefore, when the interval is FR, the SOH output by monomer degradation equation 1114 may be adjusted more significantly (e.g., a greater reduction in SOH) compared to PS or rest intervals.

[0075] Figure 5 This is a flowchart 1200 illustrating the generation (i.e., construction) of an average temperature LUT 1112 according to one aspect of this disclosure. Different combinations of input variables 1202 (such as charge rate, state of equilibrium (SOH), and usage mode (low / medium / high)) can be input (e.g., cyclically or iteratively) into a thermal model 1206 to generate an average temperature 1208 for each combination, which can then be used to populate the LUT 1112. Furthermore, constant parameters 1204 can be configured, such as the time interval between charge and discharge (e.g., 2 hours) and the depth of discharge (e.g., 100%). Generally, the average temperature 1208 increases as the SOH becomes lower, the charge rate becomes higher, and the usage mode becomes more advanced. The average temperature LUT 1112 may include an average cycle temperature considering the charge and discharge cycles of the BESS (e.g., when the charge rate is non-zero) and an average rest temperature based on the time when the BESS is not undergoing a charge and discharge cycle (e.g., when the charge rate is zero).

[0076] Thermal model 1206 can model the heat generation and dissipation capacity due to electrical losses. The charging rate affects current flow, which contributes to the Joule heating (I0). 2 Heat generation (R loss) occurs, and the state of equilibrium (SOH) affects the internal resistance, with degraded batteries (lower SOH) having higher internal resistance, leading to increased heat generation. Thermal model 1206 can calculate heat generation and then use thermal capacity and thermal resistance parameters to determine how heat generation affects the battery's average temperature, taking into account ambient temperature and cooling mechanisms.

[0077] Figure 6This is a flowchart 1300 illustrating an implementation of a system and / or method for estimating battery degradation of a battery essential energy storage (BESS) without using an average temperature lookup table, according to one aspect of this disclosure. In this case, a power demand profile 1302 specifies the charge or discharge power of the battery over time, and the temperature is calculated directly using a thermal model 1206, resulting in a time series 1304 of power, temperature, and state of charge (SOC). The time series 1304 then undergoes classification 1306 to determine the mode type (e.g., peak shift, frequency regulation, or quiescence), which is used in the cell degradation equation 1114.

[0078] Figure 7 This is a flowchart illustrating a pattern classifier 1306 according to one aspect of this disclosure. Data file 1402 may include average BESS site power, average BESS site SOC, and maximum BESS module temperature over a time period (e.g., hours, days, months, etc.). Data file 1402 may be divided into multiple time intervals (e.g., each time interval is 1 hour, 24 hours, etc.), which may correspond to reference... Figure 4 The described iteration. The logic of the pattern classifier 1110 can vary based on the unit type or module type configured in the BESS configuration 1102. At step 1404, data for a time interval (e.g., 24 hours) can be extracted, and this time interval can be further divided into sub-time intervals (e.g., one minute long, where 24...). (60 = 14440 sub-time intervals). At step 1406, noise in the SOC data can be reduced; for example, changes in SOC less than 1% can be ignored. At step 1408, the start time of charging within the time interval (e.g., a sub-time interval) can be marked as a charging point. At step 1410, the time period between two charging points that is greater than or equal to the SOC difference threshold can be marked as... Time period. In some cases, when the SOC difference threshold is greater than or equal to approximately 5%, greater than or equal to approximately 10%, greater than or equal to approximately 15%, greater than or equal to approximately 20%, greater than or equal to approximately 25%, greater than or equal to approximately 30%, greater than or equal to approximately 35%, greater than or equal to approximately 40%, greater than or equal to approximately 45%, or greater than or equal to approximately 50%, the time period can be marked as [missing information]. The time period is not limited to this. At step 1412, the data for each sub-interval can be classified as a rest interval, a PS interval, or a FR interval. For example, if the maximum SOC and minimum SOC are equal within a sub-interval (e.g., within one minute), that sub-interval can be classified as a rest interval. If the sub-interval is in... Within a given time period, the sub-interval can be classified as a PS interval. If the sub-interval is neither a rest interval nor a PS interval, it can be classified as an FR interval. The output pattern classification 1418 can then be used to adjust the monomer degradation equation 1114.

[0079] Figure 8 This is a graph 1500 showing an estimate of the SOH of the BESS as a time series according to one aspect of this disclosure. The horizontal axis may represent time (e.g., in years), and the vertical axis may represent SOH (e.g., in %) and AC energy (electricity output to the grid after DC-to-AC conversion; e.g., in MWh). (See reference...) Figure 4 The SOH value 1116 determined during the described iteration process can be displayed on curve 1502. The AC energy corresponding to the SOH value of curve 1502 can be displayed on curve 1506. A reference SOH value can be displayed on curve 1504 (for comparison purposes). In some cases, a user interface (e.g., a monitor) can display graph 1500.

[0080] Figure 9 The diagram is a reference to an implementation of one aspect of this disclosure. Figures 4 to 8 A schematic diagram of one or more controllers 1600 of the described system and / or method.

[0081] The controller 1600 may include one or more processors 1602 (i.e., processing modules) configured to execute program instructions held in memory 1604 (i.e., memory modules). In this respect, the processors 1602 of the controller 1600 may execute any of the various methods, processes, steps, logic flows, and / or algorithms described throughout this disclosure, for example, referring to... Figure 4 and Figure 6 The flowcharts 1100 and 1300, describing the implementation of systems and / or methods for estimating battery degradation in BESS, are referenced. Figure 5 The flowchart describing the generation of the LUT is shown in Figure 1200. (Reference) Figure 7 The described pattern classifier 1110, and references Figure 8 The description shows the display of chart 1500.

[0082] Controller 1600 (i.e., computing device) may include a desktop computer, mainframe computer system, workstation, graphics computer, parallel processor, or any other computer system (e.g., networked computer). One or more processors 1602 of controller 1600 may include any processing element known in the art. In this sense, one or more processors 1602 may include any microprocessor type device configured to execute algorithms and / or instructions, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), parallel processors, graphics processing units (GPUs), central processing units (CPUs), other chipsets, logic circuits, and / or electronic processors. It should also be appreciated that the term "processor" can be broadly defined to encompass any device having one or more processing elements that execute program instructions from non-transitory memory 1604. Furthermore, the steps described throughout this disclosure may be performed by a single controller 1600 or alternatively by multiple controllers. Additionally, controller 1600 may include one or more controllers housed in a common housing or multiple housings. In this manner, any controller or combination of controllers may be individually packaged as a module for integration into BESS.

[0083] Memory 1604 may include any storage medium known in the art suitable for storing program instructions executable by one or more associated processors 1602. For example, memory 1604 may include non-transitory memory media. As another example, memory medium 1604 may include, but is not limited to, read-only memory, random access memory, magnetic or optical storage devices (e.g., magnetic disks), magnetic tape, solid-state drives, etc. It should also be noted that memory 1604 may be housed together with processor 1602 in a common controller housing. In some cases, memory 1604 may be remotely located relative to the physical location of processor 1602 and controller 1600. For example, one or more processors 1602 of controller 1600 may access remote memory (e.g., a server or cloud) or be accessible via a network (e.g., the Internet, an intranet, etc.).

[0084] The systems and / or methods associated with flowcharts 1100, 1200, 1300, and 1110 can be implemented as computer programs stored in memory 1604. Computer programs (also referred to as programs, program instructions, software, software applications, scripts, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and can be deployed in any form, including as standalone programs or as modules, components, subroutines, objects, or other units suitable for use in a computing environment. Computer programs may, but do not necessarily, correspond to files in a file system. Programs can be stored as a portion of a file containing other programs or data (e.g., one or more scripts stored in a markup language document), a single file dedicated to the program under discussion, or multiple coordinating files (e.g., files storing one or more modules, subroutines, or code portions). Computer programs can be deployed to execute on a single computer or on multiple computers located at a site or distributed across multiple sites and interconnected via a communication network.

[0085] To provide interaction with the user, embodiments of the subjects described in this specification (such as Figure 1500) may be displayed on a user interface 1606, such as a display device, for example, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user, and a keyboard and pointing device, such as a mouse or trackball, through which the user can provide input to the computer.

[0086] The present disclosure has been described in more detail above with reference to the accompanying drawings and various aspects. However, the configurations described in the drawings or the aspects in the specification are merely aspects of the present disclosure and do not represent all the technical ideas of the present disclosure. Therefore, it should be understood that various equivalents and variations may exist in place of them at the time of filing this application, and these equivalents and variations are covered by the claims.

Claims

1. A system for estimating battery degradation in a battery energy storage system, comprising: The controller includes one or more processing modules and one or more non-transitory memory modules, the one or more non-transitory memory modules storing computation instructions, which are configured to: (a) An iterative process is performed within a predefined time period, wherein the predefined time period is divided into multiple iterations, wherein each of the multiple iterations includes: (1) The average temperature of the battery storage system for the current iteration of the plurality of iterations is determined by inputting the following into an average temperature lookup table: the state of equilibrium (SOH) of the battery storage system for the current iteration and the charging rate of the battery storage system for the current iteration; and (2) Input the determined average temperature into a set of single-cell degradation equations to determine the SOH of the battery energy storage system for the next iteration of the plurality of iterations.

2. The system according to claim 1, wherein, The average temperature lookup table is generated by inputting different combinations of SOH and charging rate into the thermal model.

3. The system according to claim 1, wherein, The controller is configured to: Repeat steps (1) and (2) until the last iteration of the iterative process has been performed.

4. The system according to claim 1, wherein, The controller is configured to: The user interface is instructed to display a time series showing the SOH determined for each iteration within the predefined time period, wherein the horizontal axis of the time series represents time and the vertical axis of the time series represents SOH.

5. The system according to claim 1, wherein, The SOH for the first iteration is the initial SOH of the battery energy storage system.

6. The system according to claim 1, wherein, The charging rate of the battery energy storage system in the current iteration is determined based on the usage profile of the battery energy storage system and the rated energy capacity of the battery energy storage system within the predefined time period.

7. The system according to claim 6, wherein, The usage profile of the battery energy storage system within the predefined time period is derived from the historical usage data of the battery energy storage system.

8. The system according to claim 6, wherein, The usage profile of the battery energy storage system within the predefined time period is derived based on future usage data of the battery energy storage system.

9. The system according to claim 1, wherein, The average temperature lookup table includes the average cycle temperature considering the charging and discharging cycles of the battery energy storage system and the average rest temperature based on the time when the battery energy storage system is not undergoing a charging and discharging cycle.

10. The system according to claim 1, wherein, The average temperature lookup table for the current iteration is generated based on the cell type and module type of the battery energy storage system.

11. A method for estimating battery degradation in a battery energy storage system, comprising: (a) An iterative process is performed within a predefined time period, wherein the predefined time period is divided into multiple iterations, wherein each of the multiple iterations includes: (1) The average temperature of the battery storage system for the current iteration of the plurality of iterations is determined by inputting the following into an average temperature lookup table: the state of equilibrium (SOH) of the battery storage system for the current iteration and the charging rate of the battery storage system for the current iteration; and (2) Input the determined average temperature into a set of single-cell degradation equations to determine the SOH of the battery energy storage system for the next iteration of the plurality of iterations.

12. The method according to claim 11, wherein, The average temperature lookup table is generated by inputting different combinations of SOH and charging rate into the thermal model.

13. The method of claim 11, further comprising: Repeat steps (1) and (2) until the last iteration of the iterative process has been performed.

14. The method of claim 11, further comprising: The user interface is instructed to display a time series showing the SOH determined for each iteration within the predefined time period, wherein the horizontal axis of the time series represents time and the vertical axis of the time series represents SOH.

15. The method according to claim 11, wherein, The SOH for the first iteration is the initial SOH of the battery energy storage system.

16. The method according to claim 11, wherein, The charging rate of the battery energy storage system in the current iteration is determined based on the usage profile of the battery energy storage system and the rated energy capacity of the battery energy storage system within the predefined time period.

17. The method according to claim 16, wherein, The usage profile of the battery energy storage system within the predefined time period is derived from the historical usage data of the battery energy storage system.

18. The method according to claim 16, wherein, The usage profile of the battery energy storage system within the predefined time period is derived based on future usage data of the battery energy storage system.

19. The method according to claim 11, wherein, The average temperature lookup table includes the average cycle temperature considering the charging and discharging cycles of the battery energy storage system and the average rest temperature based on the time when the battery energy storage system is not undergoing a charging and discharging cycle.

20. The method according to claim 11, wherein, The average temperature lookup table for the current iteration is generated based on the cell type and module type of the battery energy storage system.

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