Method for calculating state of charge based on industrial and commercial energy storage, energy storage system, device

Abstract

The present application relates to the calculation method of the state of charge based on the industrial and commercial energy storage, energy storage system and equipment, the method does not need high-precision voltage and current acquisition module, and is integrated with the energy storage converter, does not need to increase additional cost, uses the full battery of energy storage equipment every day to judge the error adjustment of battery SOC, on the basis of the full battery state as the reference, the relative discharge capacity compared with the full battery state can estimate the SOC of the non-full battery state, so that the calculation is simple, the full battery setting SOC value and the relative discharge capacity calculation SOC value based on the full battery state as the reference state have high precision, so that the dual-core SOC of the industrial and commercial energy storage makes the cost, complexity, precision and real-time performance of the industrial and commercial energy storage system reach a high degree of unity. The control effect of the energy storage system makes the battery pack run in a better state for a long time, and since the battery pack health life curve is obtained by charging and discharging in the better state of the battery pack, the simulation method has high scientificity for the energy storage system.

Description

Technical Field

[0001] This invention relates to the field of nuclear power calculation methods, and more particularly to a method for calculating the state of charge based on industrial and commercial energy storage, an energy storage system, equipment, and storage medium. Background Technology

[0002] With the rapid development of lithium-ion batteries and new energy equipment in recent years, especially the development of new energy electric vehicles, BMS (Battery Management System) algorithms have emerged in large numbers. These algorithms were born out of the rapid development of electric vehicles. In recent years, driven by peak-valley electricity pricing policies, the market potential of industrial and commercial energy storage has grown rapidly, and many electrical and energy companies have invested a lot of R&D efforts in industrial and commercial energy storage. Due to technological inertia, many industrial and commercial energy storage R&D personnel are limited to BMS (Battery Management Systems) developed based on electric vehicles, or make minor modifications and apply them to industrial and commercial energy storage systems, completely ignoring the specific application scenarios of industrial and commercial energy storage. Although the Kalman filter algorithm developed based on electric vehicles can be directly applied to industrial and commercial energy storage systems, industrial and commercial energy storage has a huge advantage in calculating SOC (State of Charge) by dynamically adjusting the error every day, which is not applicable to electric vehicles. Therefore, simply applying the BMS (Battery Management Unit) of electric vehicles to industrial and commercial energy storage systems cannot maximize benefits.

[0003] Existing hardware and software technologies for estimating the State of Charge (SOC) of commercial and industrial energy storage systems are incompatible with various high-performance systems and suffer from one or more of the following shortcomings:

[0004] 1. Using the open-circuit voltage curve, the equivalent physical model of the battery pack is established to identify parameters. Then, Kalman filtering and its variant algorithms are used to estimate the SOC (state of charge) of the battery. Since the battery is a nonlinear element and its physical state changes greatly due to environmental changes, the linear equivalent physical model has a large error. Furthermore, the Kalman filtering algorithm has certain requirements for the performance of the computing chip. Therefore, this method is computationally complex, lacks versatility, and is costly.

[0005] 2. Using the open-circuit voltage curve, the battery's terminal voltage is measured to estimate its SOC (State of Charge). Although this method is relatively simple to calculate, the battery terminal voltage changes only slightly with changes in SOC, and the use of a high-precision ADC module increases material costs. Furthermore, the battery needs to be left to stand for a period of time before the terminal voltage stabilizes before the measurement can be performed, thus limiting its practicality.

[0006] 3. Existing 3S energy storage systems are dual-module designs, meaning that the 2S components – BMS (Battery Management Unit) and PCS (Power Conversion System) – are dual-module designs. This design has functional redundancy in industrial and commercial energy storage, and the communication between the two modules is uncertain. Furthermore, the BMS and EMS undergo two levels of communication. It does not have advantages in terms of real-time performance, cost, and error. Summary of the Invention

[0007] The technical problem this invention aims to solve is that existing calculation methods for industrial and commercial energy storage are complex, impractical, and suffer from poor real-time communication, high costs, and frequent communication errors. To address these shortcomings, this invention provides a method for calculating the state of charge (SOC) based on industrial and commercial energy storage, an energy storage system based on industrial and commercial energy storage, an energy storage device based on industrial and commercial energy storage, and a computer-readable storage medium.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0009] A method for calculating the state of charge (SOC) based on industrial and commercial energy storage is constructed, including:

[0010] Obtain the battery pack capacity and battery charging cycle threshold;

[0011] The relative discharge amount of the battery pack relative to the previous state of charge setting is calculated by sampling.

[0012] Calculate the state of charge (SOC) value using the current battery pack capacity;

[0013] The battery pack is charged to replenish its state of charge. If the state of charge reaches a preset value, the relative discharge of the battery pack is set to zero. The current actual battery pack capacity is calculated and then the relative discharge of the battery pack relative to the previous state of charge is calculated and repeated.

[0014] If the charging state has not reached the preset value, the relative discharge amount of the battery pack relative to the previous state of charge setting will continue to be sampled and calculated.

[0015] Preferably, before the step of sampling and calculating the relative discharge amount of the battery pack relative to the previous state of charge setting, the method further includes:

[0016] A function relating the number of charge / discharge cycles to the battery health is obtained based on the number of charging cycles. When the battery pack's charging state reaches a preset value, the battery health decays according to the function.

[0017] Preferably, in the function that obtains the relationship between the number of charge / discharge cycles and the battery health status based on the number of charge / discharge cycles;

[0018] A quadratic polynomial was used to fit the function relating the number of charge-discharge cycles to the battery health status, and the result of the quadratic polynomial fitting was positively correlated with the function relating the number of charge-discharge cycles to the battery health status.

[0019] The process of charging the battery pack to replenish its state of charge, and then reducing the relative discharge of the battery pack to zero if the state of charge reaches a preset value, also includes:

[0020] The relationship between the battery health level and the number of charge-discharge cycles is calculated based on the quadratic polynomial, and the actual capacity value of the battery pack is calculated based on the calculated battery health level.

[0021] Preferably, during the process of charging the battery pack to replenish its state of charge;

[0022] If the state of charge (SOC) does not reach the preset value, the actual capacity of the battery pack will not change; if the SOC reaches the preset value, the actual capacity of the battery pack will change and decrease.

[0023] Construct an energy storage system based on industrial and commercial energy storage, including:

[0024] The energy management system calculates the relative discharge and state of charge (SOC) of the battery pack, and then calculates the relative discharge or battery health based on the state of charge to determine the actual capacity of the battery pack.

[0025] The battery management system provides battery pack information and charging count thresholds, and obtains a function that determines the relationship between the number of charging cycles and battery health based on the charging count thresholds.

[0026] Preferably, the energy management system samples and calculates the relative discharge amount of the battery pack relative to the previous state of charge setting;

[0027] Calculate the state of charge (SOC) value using the current battery pack capacity;

[0028] The battery pack is charged to replenish its state of charge. If the state of charge reaches a preset value, the relative discharge of the battery pack is set to zero. The current actual battery pack capacity is calculated and then the relative discharge of the battery pack relative to the previous state of charge is calculated and repeated.

[0029] If the charging state has not reached the preset value, the relative discharge amount of the battery pack relative to the previous state of charge setting will continue to be sampled and calculated.

[0030] Preferably, the battery management system uses a quadratic polynomial to fit the function relating the number of charge-discharge cycles to the battery health level, and the result of the quadratic polynomial fitting is positively correlated with the function relating the number of charge-discharge cycles to the battery health level.

[0031] Preferably, the energy management system and the battery management system each contain a set of CPU cores, and there is a shared area between the two cores for data interaction.

[0032] A smart terminal device is constructed, characterized in that the smart terminal device includes at least one memory, at least one processor, and a method program for calculating the state of charge based on industrial and commercial energy storage, which is stored in the memory and can run on the processor. When the method program for calculating the state of charge based on industrial and commercial energy storage is executed by the processor, it implements the steps of the method for calculating the state of charge based on industrial and commercial energy storage as described above.

[0033] A computer-readable storage medium is constructed, characterized in that the computer-readable storage medium stores a method program for calculating the state of charge based on industrial and commercial energy storage, and when the method program for calculating the state of charge based on industrial and commercial energy storage is executed by a processor, it implements the steps of the method for calculating the state of charge based on industrial and commercial energy storage as described above.

[0034] The beneficial effects of this invention are as follows: When charging the battery pack, if the charging reaches a set value, the battery pack is considered fully charged. The set value can be set as needed, such as 100% or 95%. When the battery pack reaches this set value, it is considered fully charged, and then step S6 is performed. If the set value is not reached during charging, the relative discharge amount of the battery pack is calculated according to step S3, and the state of charge (SOC) value is calculated. This method does not require a high-precision voltage and current acquisition module and integration with the energy storage converter, thus avoiding additional costs. It only uses the daily full-charge judgment of the energy storage device to adjust the battery SOC error. Based on this, using the full-charge state as a reference, the relative discharge amount compared to the full-charge state can be calculated to estimate the SOC of the non-full-charge state. This estimation method simplifies the calculation. Therefore, the dual-core SOC of this industrial and commercial energy storage system achieves a high degree of unity in cost, complexity, accuracy, and real-time performance. Using the full-charge state to set the SOC value and designing the relative discharge amount based on the full-charge state to calculate the SOC value has high accuracy. The control function of the energy storage system keeps the battery pack in optimal condition for a long time. Since the battery pack's healthy lifespan curve is derived from charging and discharging the battery pack under optimal conditions, the simulation method is highly scientific for energy storage systems. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort:

[0036] Figure 1 This is a flowchart illustrating the calculation method of a preferred embodiment of the present invention;

[0037] Figure 2 This is a logic flowchart of the calculation method according to a preferred embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of the energy storage system according to a preferred embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of the dual-core communication structure according to a preferred embodiment of the present invention;

[0040] Figure 5 This is a schematic diagram of the dual-core shared structure of the energy storage system according to a preferred embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram of the internal structure of a smart terminal device according to a preferred embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, a clear and complete description will be provided below in conjunction with the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the protection scope of the present invention.

[0043] A preferred embodiment of the present invention provides a method for calculating the state of charge (SOC) of industrial and commercial energy storage; such as... Figure 1-2 The diagram shown is a flowchart illustrating the method for calculating the state of charge based on industrial and commercial energy storage according to an embodiment of the present invention. This method can be executed by a device, which can be implemented by software and / or hardware.

[0044] Specifically, in this embodiment, the method for calculating the state of charge (SOC) of industrial and commercial energy storage includes the following steps:

[0045] Step S1: Obtain the battery pack capacity and charging cycle threshold;

[0046] In a preferred embodiment of the present invention, the state of charge (SOC) is based on the characteristics of industrial and commercial energy storage. Industrial and commercial energy storage systems utilize peak shaving and valley filling to profit from electricity price differences. Therefore, industrial and commercial manufacturers will configure energy storage converters that can fully charge the energy storage system during off-peak electricity periods, and utilize these periods to fully charge the system's SOC, then output it during peak electricity periods to generate profit. First, the battery pack capacity needs to be obtained. The capacity (in Ah) is indicated on the nameplate of a newly purchased battery pack, and at this time, the battery pack's health is 100%, with 0 charge cycles. However, as the battery is used and charged, the number of charge-discharge cycles will gradually increase, and the battery health will gradually decrease. At this point, the actual capacity of the battery pack will no longer be the same as the capacity marked on the nameplate, and is often determined by the battery health. The actual capacity of the battery pack is the product of the battery pack's rated capacity and its battery health. The number of charge and discharge cycles is determined by the battery pack cells. Typically, when the battery pack reaches the set charging value, the number of charge and discharge cycles is incremented by 1, and the battery health level decreases by 1. Therefore, the charging cycle threshold can be obtained when acquiring the battery pack, and the degree of battery health degradation after each charge and discharge cycle can be determined based on this threshold.

[0047] It should be noted that, in this invention, the battery pack cells undergo battery life testing before leaving the factory. The test measures the relationship between the battery capacity decay and the number of charging cycles, with the independent variable being the number of charge-discharge cycles and the function being the battery health status (SOH). Therefore, this threshold is the current state of charge value when the battery pack is discharged to a certain state during the test, which is considered as one charge-discharge cycle.

[0048] Step S2: Obtain the function relating the number of charge / discharge cycles to the battery health based on the number of charging cycles;

[0049] In a preferred embodiment of the present invention, to facilitate the calculation of the relationship between the number of charge-discharge cycles and the battery health, the present invention uses a polynomial to fit the curve of the number of charge-discharge cycles and the battery health life, making it a quadratic polynomial. The fitted quadratic polynomial is positively correlated with the curve of the number of charge-discharge cycles and the battery health life, and the correlation is as high as 99.7%. This yields a functional relationship between the number of charge-discharge cycles and the battery health life. After each effective charge-discharge cycle, the degree of battery health degradation can be calculated based on the fitted functional relationship, and the actual capacity value of the battery pack can be calculated based on the degree of degradation.

[0050] Step S3: Sample and calculate the relative discharge amount of the battery pack relative to the previous state of charge setting;

[0051] Step S4: Calculate the state of charge (SOC) value using the current battery pack capacity;

[0052] In a preferred embodiment of the present invention, the capacity of the battery pack will decrease during the recharge process. For example, if the new battery capacity is 3000AH, the SOC will increase or decrease by 1 when the ampere-hour integration method is used to calculate 3AH. However, since the actual capacity of the battery is constantly decreasing during use, it is necessary to calculate the actual capacity of the battery at this time using the battery health status. For example, after a 300AH battery is charged and discharged 1000 times, the SOH is 66.7%, so the actual capacity of the battery at this time is 200AH. Then, the SOC will increase or decrease by 1 when the ampere-hour integration method is used to calculate 2AH. After the battery pack is fully charged, the battery is subsequently discharged. The discharge amount can be calculated by using an ADC to measure the discharge current and integrating it over discrete time. The percentage of the discharge amount relative to the battery's actual capacity is the amount consumed. For example, if the initial capacity of the battery pack (as stated on the battery nameplate) is 500AH and the battery health is 80%, then the actual battery capacity is 400AH. If 100AH ​​is discharged relative to the fully charged state, the discharged capacity is 25% of the actual capacity of 400AH, meaning the state of charge (SOC) is 75%. If 50AH is charged at this point, the relative discharge amount is 100 - 50 = 50AH, and the SOC is 87.5%.

[0053] The actual battery capacity is calculated as follows: ,in This refers to the actual capacity of the battery pack. The rated capacity of the battery pack (the capacity recorded on the battery pack nameplate). This refers to the health status of the battery.

[0054] Relative discharge capacity of the battery pack , This refers to the current measured at the positive and negative terminals of the battery at this time (the discharge current is used as evidence, and the charging current is negative). Given the timer's period, the cumulative unit relative to the fully charged state is ampere-seconds, which is then converted to ampere-hours. The State of Charge (SOC) is then calculated as follows:

[0055]

[0056] In the formula, The calculation is performed by accumulating over a 1-second timer, and the final unit is ampere-seconds, which needs to be converted to ampere-hours. Q is the battery's factory capacity, and SOH is the battery's health status.

[0057] Step S5: Charge the battery pack. If the state of charge reaches the preset value, proceed to step S6. If the preset value is not reached, repeat step S3.

[0058] In a preferred embodiment of the present invention, when the battery pack is charged, if the charging reaches a set value, the battery pack is considered fully charged. The set value can be set as needed, such as 100% or 95%. When the battery pack reaches this set value, it is considered fully charged, and then step S6 is performed. If the set value is not reached during the charging process, the relative discharge amount of the battery pack is calculated according to step S3, and the state of charge (SCC) value is calculated. It should be noted that as long as the charging state is entered and the charging reaches the set value, it is considered fully charged. Since industrial and commercial energy storage often needs to be charged once a day, it is often considered fully charged once the set value is reached. If it is not fully charged, since the actual capacity of the battery pack is still the actual capacity of the incomplete state, only the SCC value of the charged battery is calculated, and the current SCC value is calculated based on the charged battery.

[0059] Step S6: Set the relative discharge level of the battery pack to zero and the state of charge to 100%, and calculate the battery health status;

[0060] Step S7: Calculate the current actual battery pack capacity using the battery health status, and then loop back to step S3;

[0061] In a preferred embodiment of the present invention, when the battery pack reaches a set charging value, the charging count is incremented by 1, and the relative discharge amount of the battery pack is reset to 0. At this time, the state of charge (SOC) is 100%. The current battery health life value can be determined based on the curve of battery charge / discharge cycles and battery health life. The actual capacity value of the current battery pack is then calculated based on this battery health life value. The process continues to repeat step S3 for discharge and charge cycles to calculate the SOC. It should be noted that the SOC of the battery pack is calculated based on the battery's previous 100% full charge state using the ampere-hour integration method to calculate the relative discharge amount relative to the full charge state. For example, if the initial capacity of the battery is 300AH and the current SOH is 66.7, then the actual capacity of the battery is 200AH. If the current state involves a 100AH ​​discharge and a 50AH charge relative to the previous full charge state, then the relative discharge amount is 50AH. Since 50AH is 25% of the actual capacity of the battery pack, it means that only 25% of the battery pack capacity has been discharged relative to the full charge state. Therefore, the current SOC is 75%.

[0062] The above method calculates the state of charge (SOC). It utilizes full-charge setting and uses full charge as a reference. Taking advantage of the energy storage device's near-daily charge-discharge cycle, it adjusts for 100% charge error. The SOC of the discharge state is calculated using this 100% state as the baseline reference. Specifically, if the energy storage system continuously charges at a current below a certain threshold, the SOC is considered 100%. Furthermore, the system calculates the actual battery pack capacity and adjusts for SOC error daily. Based on this, by comparing the relative discharge amount at 100%, the SOC value for non-100% states is calculated. This method offers high accuracy and is cost-effective as it does not require high-precision modules.

[0063] Corresponding to a method for calculating the state of charge based on industrial and commercial energy storage, this invention also provides a method based on industrial and commercial energy storage systems, specifically, such as... Figure 3 As shown, the energy storage system includes an energy management system 100 and a battery management system 200. Figure 4 As shown, the energy management system and battery management system are integrated using a dual-core chip design, which improves communication speed and accuracy, and further reduces production costs. Figure 5 As shown, the dual-core design selects a DSP chip with two CPU cores as the main core of the battery management system. CPU1 handles tasks from the battery management system module, while CPU2 handles tasks from the energy management system module. Both can run simultaneously, moving data requiring interaction into a shared area to save on the cost of an external bus chip and completely avoid communication errors and interruptions caused by high magnetic field variations and wiring issues. This dual-core design simplifies the existing traditional 3S energy storage structure, reduces production costs, optimizes communication between the battery management system and the energy management system, and improves the stability and real-time performance of data transmission. Furthermore, the dual-core design allows battery information to be directly uploaded to the energy management system, enabling the energy management system to make immediate decisions.

[0064] The energy management system 100 calculates the relative discharge amount and state of charge value of the battery pack, and calculates the relative discharge amount or battery health status based on the charging status to calculate the actual capacity of the battery pack.

[0065] Furthermore, after setting the battery pack to full charge and subsequently discharging the battery, the discharge amount can be calculated. This is done by using an ADC to measure the discharge current and integrating it over discrete time. The percentage of the discharge amount relative to the battery's actual capacity is the consumption. For example, if the initial capacity of the battery pack (the capacity on the battery nameplate) is 500AH and the battery health level is 80%, then the actual battery capacity is 400AH. If 100AH ​​is discharged relative to the full charge state, then the discharged amount accounts for 25% of the actual capacity of 400AH, meaning the state of charge (SOC) is 75%. If 50AH is charged at this point, the relative discharge amount is 100-50=50AH, and the SOC is 87.5%.

[0066] The actual battery capacity is calculated as follows: ,in This refers to the actual capacity of the battery pack. The rated capacity of the battery pack (the capacity recorded on the battery pack nameplate). This refers to the health status of the battery.

[0067] Relative discharge capacity of the battery pack , This refers to the current measured at the positive and negative terminals of the battery at this time (the discharge current is used as evidence, and the charging current is negative). Given the timer's period, the cumulative unit relative to the fully charged state is ampere-seconds, which is then converted to ampere-hours. The State of Charge (SOC) is then calculated as follows:

[0068]

[0069] In the formula, The calculation is performed by accumulating over a 1-second timer, and the final unit is ampere-seconds, which needs to be converted to ampere-hours. Q is the battery's factory capacity, and SOH is the battery's health status.

[0070] Furthermore, when charging the battery pack, if the charging reaches a set value, the battery pack is considered fully charged. This set value can be configured as needed, such as 100% or 95%. If the set value is not reached during charging, the relative discharge amount of the battery pack is calculated, and the state of charge (SOC) value is determined. It should be noted that once the charging state is entered and the set value is reached, it is considered fully charged. Since commercial and industrial energy storage often requires charging once a day, reaching the set value is often considered a full charge. However, if the battery pack is not fully charged, since the actual capacity of the battery pack is still the actual capacity of the partially charged state, only the SOC value of the charged portion needs to be calculated, and the current SOC value is determined based on the charged portion.

[0071] The battery management system 200 provides battery pack information and charging count thresholds, and obtains a function that determines the relationship between the number of charging cycles and the battery health based on the charging count thresholds.

[0072] Furthermore, the first step is to obtain the battery pack's capacity. The capacity (in Ah) will be indicated on the nameplate of a newly purchased battery pack, and at this time, the battery pack's health is 100%, with 0 charge cycles. However, as the battery is used and charged, the number of charge-discharge cycles will gradually increase, and the battery's health will gradually decrease. At this point, the actual capacity of the battery pack will no longer be the same as the capacity marked on the nameplate, and is often determined by the battery's health. The actual capacity of the battery pack is the product of the battery pack's rated capacity and its health status. The number of charge-discharge cycles is determined by the battery cells. Typically, when the battery pack reaches a set charging value, the charge-discharge cycle is incremented by one, and the battery's health status decreases by one. Therefore, when acquiring the battery pack, its charge cycle threshold can be obtained, and this threshold can be used to determine the degree of battery health degradation after each charge-discharge cycle.

[0073] Furthermore, to facilitate the calculation of the relationship between the number of charge-discharge cycles and battery health, this invention uses a polynomial to fit the curve of the number of charge-discharge cycles and battery health life, making it a quadratic polynomial. The fitted quadratic polynomial is positively correlated with the curve of the number of charge-discharge cycles and battery health life, with a correlation as high as 99.7%. This yields a functional relationship between the number of charge-discharge cycles and battery health life. After each effective charge-discharge cycle, the degree of battery health degradation can be calculated based on the fitted functional relationship, and the actual capacity value of the battery pack can be calculated based on this degree of degradation.

[0074] Based on the above embodiments, the present invention also provides a smart terminal device, the principle block diagram of which is as follows: Figure 6 As shown, the aforementioned intelligent terminal device includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores a program for calculating the state of charge (SOC) based on industrial and commercial energy storage. The memory provides an environment for the operation of the operating system in the non-volatile storage medium and the SOC calculation program. The network interface of the intelligent terminal device is used for communication with external terminals via a network connection. When the processor executes the SOC calculation program, it implements the steps of any of the aforementioned SOC calculation methods based on industrial and commercial energy storage. The display screen of the intelligent terminal can be a liquid crystal display (LCD) or other types of display screens.

[0075] Those skilled in the art will understand that Figure 6The block diagram shown is merely a partial structural diagram related to the present invention and does not constitute a limitation on the smart terminal device to which the present invention is applied. A specific smart terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0076] In this embodiment of the invention, a smart terminal is provided, which includes a memory, a processor, and a safe item identification program stored in the memory and executable on the processor. When the safe item identification program is executed by the processor, it performs the following operation instructions:

[0077] Obtain the battery capacity and charging cycle threshold of the battery pack;

[0078] A function that determines the relationship between the number of charge / discharge cycles and battery health based on the number of charging cycles;

[0079] The relative discharge amount of the battery pack relative to the previous state of charge setting is calculated by sampling.

[0080] Calculate the state of charge (SOC) value using the current battery pack capacity;

[0081] The battery pack is charged. If the state of charge reaches the preset value, the relative discharge of the battery pack is reduced to zero, and the state of charge is 100%. The battery health is then calculated.

[0082] The current actual battery pack capacity is calculated using the battery health status, and the relative discharge amount of the battery pack relative to the previous state of charge setting is also calculated.

[0083] If the state of charge does not reach the preset value, the relative discharge amount of the battery pack relative to the previous state of charge setting is calculated.

[0084] Repeat the above steps.

[0085] This invention also provides a computer-readable storage medium storing a method program for calculating the state of charge (SOC) based on industrial and commercial energy storage. When executed by a processor, the method program implements the steps of any of the SOC calculation methods provided in this invention.

[0086] It should be understood that the present invention has been described through some embodiments, and those skilled in the art will recognize that various changes or equivalent substitutions can be made to these features and embodiments without departing from the spirit and scope of the invention. Furthermore, under the teachings of the present invention, these features and embodiments can be modified to adapt to specific situations and materials without departing from the spirit and scope of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application are within the protection scope of the present invention.

Claims

1. A method of calculating the state of charge of a commercial energy storage based on the state of charge of the commercial energy storage, characterized in that, The method comprises the following steps: Obtaining the battery pack capacity and the battery charge frequency threshold value; Obtaining the function relationship between the charge-discharge frequency and the battery health degree according to the charge frequency, and when the battery pack charge state reaches the preset value, the battery health degree is attenuated according to the function relationship; In the function relationship between the charge-discharge frequency and the battery health degree according to the charge frequency; Using a quadratic polynomial to fit the function relationship between the charge-discharge frequency and the battery health degree, and the result of the quadratic polynomial fitting is positively correlated with the function relationship between the battery pack charge-discharge frequency and the battery health degree; Sampling and calculating the relative discharge amount of the battery pack relative to the last state of charge adjustment; Using the current battery pack capacity to calculate the state of charge value; Charging the battery pack to supplement the state of charge, if the charge state reaches the preset value, the relative discharge amount of the battery pack is reset to zero, and the current actual battery pack capacity value is calculated, and then the relative discharge amount of the battery pack relative to the last state of charge adjustment is calculated in a loop; In the process of charging the battery pack to supplement the state of charge, if the charge state reaches the preset value, the relative discharge amount of the battery pack is reset to zero, and the current actual battery pack capacity value is calculated, and then the relative discharge amount of the battery pack relative to the last state of charge adjustment is calculated in a loop; If the charge state does not reach the preset value, the relative discharge amount of the battery pack relative to the last state of charge adjustment is continuously sampled and calculated. In the process of charging the battery pack to supplement the state of charge; 2. The computational method of claim 1, wherein: If the state of charge does not reach the preset value, the actual capacity of the battery pack does not change; if the state of charge reaches the preset value, the actual capacity of the battery pack changes and decreases. The method comprises the following steps:

3. An energy storage system employing the method of claim 1-2 for calculating the state of charge of the energy storage based on the business energy storage, characterized in that, An energy management system calculates the relative discharge amount and the state of charge value of the battery pack, and calculates the actual capacity of the battery pack according to the charge state by calculating the relative discharge amount or the battery health degree A battery management system provides battery pack information and a charge frequency threshold value, and obtains a function relationship between the charge frequency and the battery health degree according to the charge frequency threshold value. The energy management system samples and calculates the relative discharge amount of the battery pack relative to the last state of charge adjustment; 4. The energy storage system of claim 3, wherein: Using the current battery pack capacity to calculate the state of charge value; Charging the battery pack to supplement the state of charge, if the charge state reaches the preset value, the relative discharge amount of the battery pack is reset to zero, and the current actual battery pack capacity value is calculated, and then the relative discharge amount of the battery pack relative to the last state of charge adjustment is calculated in a loop; If the charge state does not reach the preset value, the relative discharge amount of the battery pack relative to the last state of charge adjustment is continuously sampled and calculated. The battery management system uses a quadratic polynomial to fit the function relationship between the charge-discharge frequency and the battery health degree, and the result of the quadratic polynomial fitting is positively correlated with the function relationship between the battery pack charge-discharge frequency and the battery health degree.

5. The energy storage system of claim 3, wherein: The energy management system and the battery management system each contain a group of CPU cores, and there is a shared area between the dual cores for data interaction.

6. The energy storage system of claim 3, wherein: ​ 7. An intelligent terminal device, characterized by The intelligent terminal device comprises at least one memory, at least one processor, and a program of a method for calculating the state of charge of industrial and commercial energy storage stored on the memory and capable of running on the processor, and the program of the method for calculating the state of charge of industrial and commercial energy storage is executed by the processor to realize the steps of the method for calculating the state of charge of industrial and commercial energy storage according to any one of claims 1-2.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a program of a method for calculating the state of charge of industrial and commercial energy storage, and the program of the method for calculating the state of charge of industrial and commercial energy storage is executed by the processor to realize the steps of the method for calculating the state of charge of industrial and commercial energy storage according to any one of claims 1-2.

Images