Method and device for detecting state of health of energy storage battery and energy storage system

Abstract

The application discloses a kind of energy storage battery health state detection method, device and energy storage system, belong to energy storage system field.The energy storage battery health state detection method includes: in the case where energy storage battery ends first round of charge-discharge cycle, based on the actual working parameter of the energy storage battery in the first round of charge-discharge cycle corresponding, determine the ohmic internal resistance corresponding to the next round of charge-discharge cycle of the energy storage battery;Based on the ohmic internal resistance, determine the initial state of charge value corresponding to the next round of charge-discharge cycle of the energy storage battery;Based on the initial state of charge value, determine the predicted health state value corresponding to the next round of charge-discharge cycle of the energy storage battery.The energy storage battery health state detection method of the application can fully consider the influence of battery internal resistance on SOH, significantly improve the accuracy and accuracy of the final predicted health state value, and is simple to operate and easy to implement.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of energy storage systems, and particularly relates to a method and device for detecting the state of health of an energy storage battery and an energy storage system. BACKGROUND

[0002] An energy storage system (ESS) stores power when power generation is surplus or the price is low, and supplies stored power to a unit when power demand is high or the price is high. For many electrochemical energy storage batteries such as lithium ion batteries, to reduce the risk of battery pack combustion and explosion and ensure the safety of the use of energy storage batteries, the state of health (SOH) and the state of charge (SOC) of the battery state management of the energy storage battery need to be predicted. For example, a battery management system (BMS) is used to manage the reliability and safety of the energy storage battery, and the SOC, SOH and internal impedance are calculated and predicted to limit overcurrent and overvoltage. In the related art, a large sample data set is mainly modeled and predicted by using a deep learning algorithm, or the SOH is calculated and predicted by real-time detection of the battery state. However, the accuracy and precision of the SOH results obtained by these methods are generally poor, which affects the accuracy of the subsequent fault diagnosis results. SUMMARY

[0003] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides a method and device for detecting the state of health of an energy storage battery and an energy storage system, which improves the accuracy and precision of the predicted state of health value obtained, and is simple to operate and easy to implement.

[0004] In a first aspect, the present application provides a method for detecting the state of health of an energy storage battery, which comprises:

[0005] In the case where the energy storage battery ends a first round of charge and discharge cycles, the Ohmic internal resistance corresponding to the next round of charge and discharge cycles of the energy storage battery is determined based on the actual working parameters of the energy storage battery corresponding to the first round of charge and discharge cycles.

[0006] Based on the Ohmic internal resistance, an initial state of charge value corresponding to the next round of charge and discharge cycles of the energy storage battery is determined.

[0007] Based on the initial state of charge value, a predicted state of health value corresponding to the next round of charge and discharge cycles of the energy storage battery is determined.

[0008] According to the state of health detection method of the energy storage battery, the real-time ohmic resistance after each round of charging and discharging cycle is calculated, and the initial state of charge value of the energy storage battery in the next round of charging and discharging cycle is calculated based on the obtained ohmic resistance, so that the accuracy of the initial state of charge value can be effectively improved. Then, the SOH is predicted based on the obtained initial state of charge value, the influence of the battery resistance on the SOH can be fully considered, the accuracy and accuracy of the finally obtained predicted state of health value can be significantly improved, and the operation is simple and easy to implement.

[0009] According to one embodiment of the present application, the initial state of charge value of the energy storage battery in the next round of charging and discharging cycle is determined based on the initial state of charge value, including:

[0010] Based on the initial state of charge value, the theoretical charging and discharging time required for the energy storage battery to end the next round of charging and discharging cycle is determined;

[0011] Based on the actual charging and discharging time used by the energy storage battery to end the next round of charging and discharging cycle, the theoretical charging and discharging time, and the calibration state of health value corresponding to the target round of charging and discharging cycle, the predicted state of health value is determined.

[0012] According to one embodiment of the present application, the theoretical charging and discharging time required for the energy storage battery to end the next round of charging and discharging cycle is determined based on the initial state of charge value, including:

[0013] Based on the initial state of charge value, the battery capacity of the energy storage battery and the target charging and discharging time, the first state of charge value corresponding to the energy storage battery after the target charging and discharging time ends is determined;

[0014] Based on the first state of charge value, the battery capacity and the charging and discharging current corresponding to the next round of charging and discharging cycle, the theoretical charging and discharging time required for the energy storage battery to end the next round of charging and discharging cycle is determined.

[0015] According to one embodiment of the present application, the initial state of charge value of the energy storage battery in the next round of charging and discharging cycle is determined based on the ohmic resistance, including:

[0016] Based on the ohmic resistance and the open circuit voltage of the energy storage battery, the initial state of charge value is determined.

[0017] According to one embodiment of the present application, the ohmic resistance of the energy storage battery in the next round of charging and discharging cycle is determined based on the actual working parameter corresponding to the first round of charging and discharging cycle of the energy storage battery, including:

[0018] Based on the actual working parameter, the battery loss of the energy storage battery in the first round of charging and discharging cycle is determined.

[0019] determining the ohmic internal resistance based on the battery loss and the actual working parameter.

[0020] According to one embodiment of the present application, the determining the ohmic internal resistance based on the battery loss and the actual working parameter comprises:

[0021] based on the formula:

[0022]

[0023] determining the ohmic internal resistance, wherein R is the ohmic internal resistance, η loss is the battery loss, V bat is the first round of charge-discharge cycle corresponding charge-discharge voltage, t is the first round of charge-discharge cycle corresponding first charge-discharge time, Q bat is the first round of charge-discharge cycle corresponding charge-discharge capacity.

[0024] According to one embodiment of the present application, the method further comprises:

[0025] resetting the real-time state of charge value of the energy storage battery in the case that the energy storage battery ends the first round of charge-discharge cycle.

[0026] According to one embodiment of the present application, after the determining the predicted state of health value of the energy storage battery in the next round of charge-discharge cycle based on the initial state of charge value, the method further comprises:

[0027] determining the predicted battery efficiency of the energy storage battery in the next round of charge-discharge cycle based on the actual charge-discharge parameter of the energy storage battery in the next round of charge-discharge cycle;

[0028] determining the state of health information of the energy storage battery based on the predicted battery efficiency and the predicted state of health value, the state of health information being used to control the working state of the energy storage battery.

[0029] According to one embodiment of the present application, the determining the state of health information of the energy storage battery based on the predicted battery efficiency and the predicted state of health value comprises:

[0030] determining that the energy storage battery is normal in the case that the predicted state of health value is greater than a first threshold value and the predicted battery efficiency is in a target range.

[0031] determining that the energy storage battery is abnormal in the case that the predicted state of health value is not greater than the first threshold value and / or the predicted battery efficiency is not in the target range.

[0032] According to one embodiment of the present application, the method for detecting the state of health of the energy storage battery is applied to an energy storage system, the energy storage system comprising a plurality of energy storage batteries, and the method further comprises:

[0033] After determining the predicted state of health value corresponding to the next round of charging and discharging cycles of the energy storage battery based on the initial state of charge value, determining the predicted state of health value corresponding to the next round of charging and discharging cycles of the energy storage system based on the average of the plurality of predicted state of health values corresponding to the plurality of energy storage batteries;

[0034] and / or,

[0035] In the case where the energy storage system ends the first round of charging and discharging cycles, determining the ohmic internal resistance corresponding to the next round of charging and discharging cycles of the energy storage system based on the actual working parameters corresponding to the first round of charging and discharging cycles of the energy storage system;

[0036] Determining the initial state of charge value corresponding to the next round of charging and discharging cycles of the energy storage system based on the ohmic internal resistance corresponding to the energy storage system;

[0037] Determining the predicted state of health value corresponding to the next round of charging and discharging cycles of the energy storage system based on the initial state of charge value corresponding to the energy storage system.

[0038] In a second aspect, the present application provides a device for detecting the state of health of an energy storage battery, the device comprising:

[0039] A first processing module is configured to, in the case where the energy storage battery ends the first round of charging and discharging cycles, determine the ohmic internal resistance corresponding to the next round of charging and discharging cycles of the energy storage battery based on the actual working parameters corresponding to the first round of charging and discharging cycles of the energy storage battery;

[0040] A second processing module is configured to determine the initial state of charge value corresponding to the next round of charging and discharging cycles of the energy storage battery based on the ohmic internal resistance;

[0041] A third processing module is configured to determine the predicted state of health value corresponding to the next round of charging and discharging cycles of the energy storage battery based on the initial state of charge value.

[0042] According to the device for detecting the state of health of an energy storage battery of the present application, the real-time ohmic internal resistance after each round of charging and discharging cycles is calculated, and the initial state of charge value of the energy storage battery in the next round of charging and discharging cycles is calculated based on the obtained ohmic internal resistance, which can effectively improve the accuracy of the initial state of charge value. Then, the SOH is predicted based on the obtained initial state of charge value, which can fully consider the influence of the battery internal resistance on the SOH, significantly improve the accuracy and accuracy of the final predicted state of health value, and is simple to operate and easy to implement.

[0043] In a third aspect, the present application provides a storage battery, comprising:

[0044] at least one storage battery;

[0045] The state of health detection device of the storage battery according to the second aspect is electrically connected with the at least one storage battery.

[0046] In a fourth aspect, the present application provides a non-transitory computer readable storage medium, having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the state of health detection method of the storage battery according to the first aspect.

[0047] In a fifth aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program, when executed by a processor, implements the state of health detection method of the storage battery according to the first aspect.

[0048] The one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0049] By calculating the real-time ohmic resistance at the end of each charging and discharging cycle, and calculating the initial state of charge value of the storage battery in the next charging and discharging cycle based on the obtained ohmic resistance, the accuracy of the initial state of charge value can be effectively improved. Then, based on the obtained initial state of charge value, the SOH is predicted, which can fully consider the influence of the battery resistance on the SOH, significantly improve the accuracy and accuracy of the finally obtained predicted state of health value, and is simple to operate and easy to implement.

[0050] Further, by using the method of combining open circuit voltage (OCV) and CCM to track SOC to determine the initial state of charge value, the initial error of CCM can be effectively reduced, and the accuracy and precision of the obtained initial state of charge value can be improved, thereby helping to improve the accuracy of subsequent calculation of the predicted state of health value.

[0051] Further, by using the theoretical charging and discharging time and the calibration of the calibration state of health value, and the actual charging and discharging time, the predicted state of health value of the storage battery at the end of the next charging and discharging cycle is predicted, which has high accuracy and precision, and is flexible to operate.

[0052] Further, based on the predicted state of health value and the predicted battery efficiency, the state of health information of the storage battery is determined based on the predicted state of health value, and the accuracy of the obtained result is high, and has high timeliness.

[0053] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0054] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the accompanying drawings.

[0055] Figure 1 is one of flow diagrams of a health state detection method of an energy storage battery provided by embodiments of the present application;

[0056] Figure 2 is another of flow diagrams of a health state detection method of an energy storage battery provided by embodiments of the present application;

[0057] Figure 3 is a third of flow diagrams of a health state detection method of an energy storage battery provided by embodiments of the present application;

[0058] Figure 4 is a structural diagram of a health state detection device of an energy storage battery provided by embodiments of the present application;

[0059] Figure 5 is a structural diagram of an energy storage battery provided by embodiments of the present application. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application will be clearly described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some, but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art belong to the scope of protection of the present application.

[0061] The terms "first", "second", and the like in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a particular order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than that illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of a kind and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / ", generally means that the objects before and after are in a "or" relationship.

[0062] The energy storage battery health state detection method, the energy storage battery health state detection device, the energy storage battery and the readable storage medium provided by the embodiments of the present application will be described in detail below with reference to the drawings and specific embodiments and their application scenarios.

[0063] The health state detection method of the energy storage battery can be applied to a terminal, and can be executed by hardware or software in the terminal.

[0064] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or a tablet computer. It should also be understood that, in some embodiments, the terminal can not be a portable communication device, but a desktop computer.

[0065] The health state detection method of the energy storage battery provided in the embodiments of the present application can be executed by the energy storage battery or a functional module or functional entity in the energy storage battery that can implement the health state detection method of the energy storage battery. The health state detection method of the energy storage battery provided in the embodiments of the present application is described below by taking the energy storage battery as an example.

[0066] As shown in FIG. 1, the health state detection method of the energy storage battery includes steps 110, 120 and 130. Figure 1

[0067] In step 110, in a case where the energy storage battery ends a first round of charge-discharge cycles, an ohmic internal resistance corresponding to a next round of charge-discharge cycles of the energy storage battery is determined based on actual working parameters of the energy storage battery in the first round of charge-discharge cycles.

[0068] In this step, the type of the energy storage battery can be a lithium battery, a lead-acid battery, a graphene battery, etc., which is not limited in the present application.

[0069] In the embodiments of the present application, one cycle of charging and / or one cycle of discharging completed by the energy storage battery is regarded as ending a round of charge-discharge cycles. After ending the charge-discharge cycles, the energy storage battery enters a resting state.

[0070] In some embodiments, in a case where the energy management system (EMS) is a daily EMS, one cycle represents one day of operation data. In this case, the ohmic internal resistance of the battery can be estimated based on actual working parameters (such as the difference between charging and discharging energy) of one day.

[0071] The actual working parameters of the energy storage battery corresponding to the first round of charge-discharge cycles are working parameters at the level of the energy storage battery.

[0072] The actual working parameters of the energy storage battery corresponding to the first round of charge-discharge cycles (i.e., battery state data) can include one or more of charging and discharging power, charging and discharging voltage, charging and discharging current, charging and discharging energy, and charging and discharging time.

[0073] The charging and discharging power includes charging power P ch arg e or discharging power P disch arg e . ​

[0074] The charge-discharge voltage includes a charge voltage or a discharge voltage.

[0075] The charge-discharge time includes a charge time or a discharge time.

[0076] The charge-discharge time is the actual time taken by the energy storage battery to complete a round of charging or a round of discharging.

[0077] The charge-discharge electric quantity includes a charge electric quantity or a discharge electric quantity.

[0078] It can be understood that, during the use and aging process of the energy storage battery, the internal resistance of the battery will increase, and the corresponding ohmic resistance will also change; that is, after the energy storage battery ends each charge-discharge cycle, the corresponding ohmic resistance may change compared with the previous round.

[0079] As shown in Figure 2 , in the actual execution process, whether the energy storage battery is currently in a charge-discharge cycle can be determined based on the charge-discharge current of the energy storage battery.

[0080] In the case where it is determined that the energy storage battery is in a static state, the ohmic resistance of the energy storage battery after the first round of charge-discharge cycle ends can be determined based on the actual working parameters of the energy storage battery in the first round of charge-discharge cycle, and the value is taken as the ohmic resistance of the energy storage battery in the next round of charge-discharge cycle.

[0081] Continuing to refer to Figure 2 , in some embodiments, the method can further include: resetting the real-time state of charge value of the energy storage battery in the case where the energy storage battery ends the first round of charge-discharge cycle.

[0082] In this embodiment, when the energy storage battery is in a static state, the real-time state of charge value of the battery of the energy storage battery can also be reset to improve the accuracy and accuracy of subsequent calculation of the initial state of charge value.

[0083] Continuing to refer to Figure 2 , in some embodiments, the method can further include: in the case where the energy storage battery does not end the first round of charge-discharge cycle, the real-time state of charge value of the energy storage battery is calculated in real time based on the integral method.

[0084] In some embodiments, step 110 can include:

[0085] determining the battery loss of the energy storage battery in the first round of charge-discharge cycle based on the actual working parameters;

[0086] determining the ohmic resistance based on the battery loss and the actual working parameters.

[0087] In this embodiment, the battery loss is the reduction value of the actual capacity of the energy storage battery after the first round of charge-discharge cycle ends.

[0088] The actual working parameter can include one or more of the following: charging and discharging power, charging and discharging voltage, charging and discharging current, charging and discharging electric quantity, and charging and discharging time.

[0089] In some embodiments, the battery loss can be determined based on the charging and discharging power.

[0090] In some embodiments, the battery loss can be determined based on the following formula:

[0091] η bat = 100 - η loss

[0092] wherein η loss is the battery loss; η bat is the battery efficiency of the energy storage battery; and 100 is used to represent the initial battery efficiency.

[0093] It can be understood that, due to the existence of the battery internal resistance, the battery efficiency will not be 1.

[0094] The battery efficiency, i.e., the battery conversion efficiency, is the ratio of the battery discharge electric quantity to the battery charge electric quantity in the case that the current is kept constant and the charging and discharging time is equal.

[0095] The battery efficiency is an effective energy conversion efficiency, including the charging battery efficiency and the discharging battery efficiency.

[0096] wherein the charging battery efficiency = actual battery charge electric quantity / power consumption electric quantity;

[0097] the discharging battery efficiency = actual discharge electric quantity / actual available battery electric quantity.

[0098] In a short charging and discharging cycle, without considering the leakage current, it can be approximately considered that the charging battery efficiency = the discharging battery efficiency = the battery efficiency.

[0099] In actual implementation, the actual charge electric quantity can be calculated by the Coulomb counting method (CCM), and the power consumption electric quantity can be measured by an electric meter.

[0100] For example, the battery efficiency η bat may be determined based on the following formula:

[0101]

[0102] wherein I is the actual charge current; and Q0 is the measurement value of the electric meter on the charging line.

[0103] After the battery efficiency η bat is obtained, the battery loss η loss may be further obtained based on the battery efficiency η bat .

[0104] In some embodiments, determining the ohmic internal resistance based on the battery loss and the actual working parameters can include:

[0105] Based on the formula:

[0106]

[0107] Determining the ohmic internal resistance, wherein R is the ohmic internal resistance, η loss is the battery loss, V bat is the charge-discharge voltage, t is the first charge-discharge time corresponding to the first round of charge-discharge cycle, Q bat is the charge-discharge capacity.

[0108] In this embodiment, the relationship between the battery loss and the charge-discharge current can be expressed as follows:

[0109]

[0110] Wherein, η loss is the battery loss, I bat is the charge-discharge current, V bat is the charge-discharge voltage, and R is the ohmic internal resistance.

[0111] Further, I bat can be determined by the following formula:

[0112]

[0113] Wherein, Q bat is the charge-discharge capacity (unit: A.H); and t is the first charge-discharge time.

[0114] Through the relationship between the battery loss and the charge-discharge current and the expression of the charge-discharge current, the expression of the above ohmic internal resistance can be determined.

[0115] Step 120, determining the initial state of charge value corresponding to the next round of charge-discharge cycle of the energy storage battery based on the ohmic internal resistance;

[0116] In this step, the state of charge (SOC) is the percentage of the remaining capacity of the battery.

[0117] SOC is used to represent the charge level of the battery relative to its capacity.

[0118] The initial state of charge value is an initial value for calculating the real-time state of charge value.

[0119] In actual implementation process, the initial state of charge value can be determined based on the ohmic internal resistance by any realizable manner, which is not limited herein.

[0120] In this step, by introducing the ohmic internal resistance as an influencing variable for subsequent calculation of the predicted health state value, the influence of the internal resistance change caused by the aging phenomenon of the energy storage battery on the final prediction result can be fully considered, the prediction error is reduced, and the accuracy and precision of the final prediction result are improved.

[0121] In some embodiments, step 120 can include determining the initial state of charge value based on the ohmic internal resistance and the open-circuit voltage of the energy storage battery.

[0122] In this embodiment, the SOC is tracked by combining the open-circuit voltage (OCV) and the CCM, and the battery efficiency is applied to the open-circuit voltage (OCV) to accurately calculate the SOC, so as to reduce the initial error of the CCM and improve the accuracy of the initial value of the SOC.

[0123] The CCM is also an ampere-hour integration method or a current integration method, and the real-time SOC value can be calculated by integrating the current during the charging and discharging of the battery to the initial value of the SOC.

[0124] For example, the initial state of charge value can be determined by the following formula:

[0125] SOC(t0)=f(V ocv , R)

[0126] Wherein, SOC(t0) is the initial state of charge value; f(V ocv is the open-circuit voltage; and R is the ohmic internal resistance.

[0127] According to the health state detection method of the energy storage battery provided in the embodiments of the present application, the initial state of charge value is determined by tracking the SOC by combining the open-circuit voltage (OCV) and the CCM, which can effectively reduce the initial error of the CCM and improve the accuracy and precision of the obtained initial state of charge value, thereby helping to improve the accuracy of the subsequent calculation of the predicted health state value.

[0128] Step 130, based on the initial state of charge value, determines the predicted health state value of the energy storage battery corresponding to the next round of charging and discharging cycle.

[0129] In this step, the health state (State Of Health, SOH) is used to represent the percentage of the current capacity of the battery in the energy storage battery to the factory capacity.

[0130] In actual execution process, any realizable way can be used to determine the predicted health state value of the energy storage battery corresponding to the next round of charging and discharging cycle based on the initial state of charge value, which is not limited by the present application.

[0131] For example, the real-time state of charge value can be calculated based on the initial state of charge value, and then the corresponding SOH value is predicted based on the OCV-SOC curve.

[0132] It can be understood that, as the battery operating time in the energy storage battery increases, the internal resistance thereof will gradually increase, which will result in a decrease in the SOH of the energy storage battery.

[0133] The inventors have found in the development process that, in the related art, there are methods of predicting the state of health by using a deep learning algorithm to establish a large sample data set modeling and by calculating the predicted state of health through real-time detection of the battery state, but these methods cannot introduce the influence of the internal resistance change caused by the aging phenomenon of the energy storage battery on the final prediction result, thereby resulting in poor accuracy of the final prediction result. Moreover, it is difficult to add the internal resistance change condition to the training condition of the deep learning algorithm in actual execution, which is difficult to operate and not easy to implement.

[0134] In the present application, by introducing the ohmic resistance, the initial state of charge value of the energy storage battery in the next round of charging and discharging cycle is predicted based on the current ohmic resistance of the energy storage battery after the end of the last round of charging and discharging cycle, and then the SOH is determined based on the determined initial state of charge value, which can refine the influence of variables on the prediction result and fully consider the influence of the battery internal resistance on the SOH, thereby improving the accuracy and accuracy of the final predicted state of health value and being simple to operate and easy to implement.

[0135] According to the method for detecting the state of health of the energy storage battery provided in the embodiments of the present application, the real-time ohmic resistance after the end of each round of charging and discharging cycle is calculated, and the initial state of charge value of the energy storage battery in the next round of charging and discharging cycle is calculated based on the obtained ohmic resistance, which can effectively improve the accuracy of the initial state of charge value. Then, the SOH is predicted based on the obtained initial state of charge value, which can fully consider the influence of the battery internal resistance on the SOH, significantly improve the accuracy and accuracy of the final predicted state of health value, and is simple to operate and easy to implement.

[0136] In some embodiments, step 130 can include:

[0137] Based on the initial state of charge value, a theoretical charging and discharging time required for the energy storage battery to end the next round of charging and discharging cycle is determined;

[0138] Based on the actual charging and discharging time used by the energy storage battery to end the next round of charging and discharging cycle, the theoretical charging and discharging time, and the calibration state of health value corresponding to the target round of charging and discharging cycle, a predicted state of health value is determined.

[0139] In this embodiment, the theoretical charging and discharging time is the charging and discharging time required to complete one round of charging and discharging under ideal conditions, which is predicted based on the current initial state of charge value of the energy storage battery.

[0140] The theoretical charge and discharge time can be determined by a formula method or a table lookup method, and the application does not make any limitation.

[0141] The target round of charge and discharge period can be the first round of charge and discharge period or any other round of charge and discharge period before the next round of charge and discharge period, and the application does not make any limitation.

[0142] It should be understood that in the case of the target round of charge and discharge period being the first round of charge and discharge period, the predicted state of health value determined based on the calibrated state of health value corresponding to the first round of charge and discharge period is more accurate.

[0143] In this embodiment, based on the calibrated state of health value corresponding to the target round of charge and discharge period, the predicted state of health value corresponding to the next round of charge and discharge period is determined, which can adjust the prediction result of the next round in real time based on the previous charge and discharge situation, and has high real-time and accuracy.

[0144] In some embodiments, based on the initial state of charge value, determining the theoretical charge and discharge time required for the energy storage battery to end the next round of charge and discharge period can include:

[0145] Based on the initial state of charge value, the battery capacity of the energy storage battery, and the target charge and discharge duration, determining a first state of charge value corresponding to the energy storage battery after the target charge and discharge duration ends;

[0146] Based on the first state of charge value, the battery capacity, and the charge and discharge current corresponding to the next round of charge and discharge period, determining the theoretical charge and discharge time required for the energy storage battery to end the next round of charge and discharge period.

[0147] In this embodiment, the target charge and discharge duration can be any charge and discharge time, and the specific value can be customized by the user.

[0148] The target charge and discharge duration can be a real-time changing value.

[0149] The first state of charge value is the real-time state of charge value corresponding to the energy storage battery after completing the charge and discharge of the target charge and discharge duration with the initial state of charge value as the initial value.

[0150] For example, the first state of charge value can be determined by the following formula.

[0151]

[0152] Wherein, SOC(t) is the first state of charge value; SOC(t0) is the initial state of charge value; I(t) is the real-time charge and discharge current at time t; C n is the battery capacity; and t is the target charge and discharge time.

[0153] Wherein, the unit of SOC is percentage (0% = empty; 100% = full).

[0154] The above formula is the relationship between the real-time state of charge value and the charging and discharging time length.

[0155] It can be understood that in actual application, the above formula can also be applied to the real-time tracking scene of SOC, and the initial SOC value determined based on the ohmic internal resistance before the start of each round of charging and discharging is used to track the real-time value of SOC in the round of charging and discharging through the integral algorithm, which can effectively reduce the initial error of CCM, improve the accuracy and precision of the obtained initial state of charge value, and thus improve the accuracy and precision of the SOC real-time tracking result.

[0156] The theoretical charging and discharging time is the time required for the energy storage battery to end the next round of charging and discharging cycle with the initial state of charge value as the initial value under the theoretical condition.

[0157] After obtaining the relationship between the real-time state of charge value and the charging and discharging time length, the calculation formula of the initial state of charge value is substituted, and the following formula is obtained:

[0158]

[0159] Wherein, t after is the theoretical charging and discharging time; C n is the battery capacity; SOC(t) is the first state of charge value; I bat is the charging and discharging current.

[0160] After obtaining the theoretical charging and discharging time corresponding to the next round of charging and discharging cycle, the SOH can be predicted based on the theoretical charging and discharging time, the actual charging and discharging time used by the next round of charging and discharging cycle, and the calibration state of health value corresponding to the target round of charging and discharging cycle.

[0161] Wherein, the actual charging and discharging time is the actual time length required for the energy storage battery to end the next round of charging and discharging cycle with the initial state of charge value as the initial value.

[0162] In some embodiments, determining the predicted state of health value based on the actual charging and discharging time used by the energy storage battery to end the next round of charging and discharging cycle, the theoretical charging and discharging time, and the calibration state of health value corresponding to the target round of charging and discharging cycle can include:

[0163] Determined by the formula:

[0164]

[0165] Wherein, SOH after is the predicted state of health value; SOH tbefore is the calibration state of health value; treal t represents the actual charge / discharge time. after This refers to the theoretical charge / discharge time.

[0166] In this embodiment, the calibrated health status value is used to evaluate the theoretical charge-discharge time t. after The SOH calibration value.

[0167] t after With SOH tbefore Calibration can be completed at any time during the battery life cycle.

[0168] In some embodiments, t after With SOH tbefore The calibration can be for a new battery; or it can be based on the previous charge-discharge cycle, such as the actual SOH value corresponding to the previous charge-discharge cycle; or it can be based on other previous charge-discharge cycles. This application does not limit the calibration.

[0169] For example, assuming a normal battery has a state of health (SOH) of 100% after leaving the factory (i.e., the calibrated state of health value), calculate its theoretical charge / discharge time t under constant current charge / discharge conditions. after ;

[0170] If, after 1-3 years, the same constant-current charging and discharging strategy is used to fully charge and discharge the battery, the actual time required (tr) will be... eal Therefore, the SOH of the battery at present (i.e., after 1-3 years) can be predicted according to the above formula.

[0171] In the embodiments of this application, the battery SOH is predicted based on the charging time after charging and discharging. The influence of battery running time on the SOH prediction result can be introduced. The internal resistance of the battery will gradually increase as the battery running time in the energy storage battery is normal, which will lead to a decrease in the SOH of the energy storage battery, thereby further improving the accuracy of the prediction result.

[0172] The energy storage battery health status detection method provided in the embodiments of this application predicts the energy storage battery's health status value after the next charge-discharge cycle by calibrating the theoretical charge-discharge time and the calibrated health status value, as well as the actual charge-discharge time. It has high accuracy and precision, and is flexible in operation.

[0173] like Figure 3 As shown, in some embodiments, after step 130, the method may further include:

[0174] Based on the actual charge and discharge parameters of the energy storage battery in the next charge and discharge cycle, the predicted battery efficiency of the energy storage battery in the next charge and discharge cycle is determined.

[0175] Based on the predicted battery efficiency and the predicted state of health value, the state of health information of the energy storage battery is determined, and the state of health information is used to control the working state of the energy storage battery.

[0176] In this embodiment, the battery efficiency is the ratio of the battery discharge capacity to the battery charge capacity in the case of constant current, equal charging and discharging time.

[0177] The determination methods of the conversion efficiency and the predicted state of health value have been described in the above embodiments, and will not be repeated here.

[0178] The state of health information includes normal and abnormal.

[0179] Based on the state of health information, an instruction for controlling the working state of the energy storage battery can be generated.

[0180] The working state includes ending charging and discharging and normal working.

[0181] With reference to the above Figure 3 In some embodiments, in the case of determining that the energy storage battery is abnormal, a charging and discharging termination signal can be issued to the BMS.

[0182] In this embodiment, the charging and discharging termination signal is used to instruct the energy storage battery to end charging and discharging.

[0183] According to the state of health detection method of the energy storage battery provided in the embodiments of the present application, by controlling the energy storage battery to end charging and discharging in the case of determining that the energy storage battery is abnormal, the risk of spontaneous combustion and explosion can be reduced in time and effectively, and the safety and efficiency of the energy storage battery in the running process can be improved.

[0184] In some embodiments, based on the predicted battery efficiency and the predicted state of health value, the state of health information of the energy storage battery can be determined, which can include:

[0185] In the case that the predicted state of health value is greater than a first threshold value and the predicted battery efficiency is within a target range, it is determined that the energy storage battery is normal.

[0186] In the case that the predicted state of health value is not greater than the first threshold value and / or the predicted battery efficiency is not within the target range, it is determined that the energy storage battery is abnormal.

[0187] In this embodiment, the first threshold value and the target range are preset values, which can be customized by the user or automatically determined by the system, and the present application is not limited.

[0188] The first threshold value and the target range can change correspondingly based on the changes of the battery state, the battery type and other factors.

[0189] For example, the target range can be set to 80% to 100%, 85% to 100% or any other range.

[0190] The first threshold value can be set to 40%, 55%, or any other value.

[0191] With reference to the foregoing Figure 3 , the battery information is detected by the BMS and the battery efficiency is evaluated (whether the value is out of the target range), and it is determined whether the charging continues,

[0192] If the predicted battery efficiency is in the target range, it can be further determined whether the predicted health state value is greater than the first threshold value.

[0193] If the predicted health state value is greater than the first threshold value, it can be approximately considered that the energy storage battery is in a normal state, and the charging and discharging can continue to be performed.

[0194] If the predicted health state value is not greater than the first threshold value, it can be approximately considered that the energy storage battery is in an abnormal state, and it is not recommended to continue to use.

[0195] If the predicted battery efficiency is not in the target range, it can be approximately considered that the energy storage battery is in an abnormal state, and it is not recommended to continue to use.

[0196] According to the method for detecting the health state of the energy storage battery provided in the embodiments of the present application, by further determining the health state information of the energy storage battery based on the predicted health state value and the predicted battery efficiency on the basis of the predicted health state value, the accuracy of the obtained result is high, and the timeliness of the determination is high.

[0197] It should be noted that the method for detecting the health state of the energy storage battery provided in the embodiments of the present application can also be applied to an energy storage system.

[0198] The energy storage system includes a plurality of energy storage batteries.

[0199] The SOH determination method of the energy storage system will be described from two aspects as follows.

[0200] I. SOH determination based on energy storage battery

[0201] In some embodiments, the method can further include: after determining the predicted health state value of the energy storage battery corresponding to the next round of charging and discharging cycle based on the initial state of charge value, determining the predicted health state value of the energy storage system corresponding to the next round of charging and discharging cycle based on the average value of the plurality of predicted health state values corresponding to the plurality of energy storage batteries.

[0202] In this embodiment, the energy storage system includes a plurality of energy storage batteries.

[0203] The predicted health state value corresponding to each energy storage battery can be determined based on the method for detecting the health state of the energy storage battery provided above.

[0204] After obtaining the predicted health state values corresponding to all the energy storage cells included in the energy storage system, the average value of the obtained predicted health state values is calculated, and the obtained average value is taken as the predicted health state value corresponding to the energy storage system.

[0205] II. Determination based on actual working parameters of the energy storage system

[0206] In some embodiments, the method can further include:

[0207] In the case where the energy storage system ends the first round of charge-discharge cycles, the ohmic internal resistance corresponding to the next round of charge-discharge cycles of the energy storage system is determined based on the actual working parameters of the energy storage system corresponding to the first round of charge-discharge cycles.

[0208] Based on the ohmic internal resistance corresponding to the energy storage system, the initial state of charge value corresponding to the next round of charge-discharge cycles of the energy storage system is determined.

[0209] Based on the initial state of charge value corresponding to the energy storage system, the predicted health state value corresponding to the next round of charge-discharge cycles of the energy storage system is determined.

[0210] It should be noted that in this embodiment, the actual working parameters of the energy storage system corresponding to the first round of charge-discharge cycles are parameters at the energy storage system level, rather than the actual working parameters of the energy storage cells corresponding to the first round of charge-discharge cycles as described above.

[0211] The actual working parameters of the energy storage system corresponding to the first round of charge-discharge cycles can include, but are not limited to, one or more of the charge-discharge power of the energy storage system, the charge-discharge voltage of the energy storage system, the charge-discharge current of the energy storage system, the charge-discharge electric quantity of the energy storage system, and the charge-discharge time of the energy storage system.

[0212] The initial state of charge value corresponding to the next round of charge-discharge cycles of the energy storage system is also an SOC value at the energy storage system level.

[0213] The specific calculation method is similar to that of the energy storage cell, and will not be described here.

[0214] According to the health state detection method of the energy storage cell provided in the embodiments of the present application, the predicted health state value of the energy storage system to which the energy storage cell belongs is determined through the predicted health state value of the energy storage cell, or the predicted health state value of the energy storage system is determined based on the SOH prediction method of the energy storage cell, which can quickly and accurately predict the predicted health state value of the energy storage system, and is simple to operate and easy to implement. In actual application, the best calculation method can be selected based on the actual situation, and the flexibility is high.

[0215] The energy storage battery health status detection method provided in this application can be executed by an energy storage battery health status detection device. This application uses an energy storage battery health status detection device executing the energy storage battery health status detection method as an example to illustrate the energy storage battery health status detection device provided in this application.

[0216] This application also provides a health status detection device for energy storage batteries.

[0217] like Figure 4 As shown, the energy storage battery health status detection device includes: a first processing module 410, a second processing module 420 and a third processing module 430.

[0218] The first processing module 410 is used to determine the ohmic internal resistance of the energy storage battery in the next charge-discharge cycle based on the actual working parameters of the energy storage battery in the first charge-discharge cycle after the energy storage battery has completed the first charge-discharge cycle.

[0219] The second processing module 420 is used to determine the initial state of charge value of the energy storage battery in the next charge and discharge cycle based on the ohmic internal resistance.

[0220] The third processing module 430 is used to determine the predicted health state value of the energy storage battery in the next charge-discharge cycle based on the initial state of charge value.

[0221] The energy storage battery health status detection device provided in the embodiments of this application calculates the real-time ohmic internal resistance after the end of each charge-discharge cycle, and calculates the initial state of charge (SOH) value of the energy storage battery in the next charge-discharge cycle based on the obtained ohmic internal resistance, which can effectively improve the accuracy of the initial SOH value; then, based on the obtained initial SOH value, the SOH value is predicted, which can fully consider the influence of the battery internal resistance on the SOH value, significantly improving the accuracy and precision of the final predicted health status value, and is simple to operate and easy to implement.

[0222] In some embodiments, the third processing module 430 can also be used for:

[0223] Based on the initial state of charge value, determine the theoretical charge and discharge time required for the energy storage battery to complete the next charge and discharge cycle;

[0224] Based on the actual charge / discharge time, theoretical charge / discharge time and calibrated health status value corresponding to the target charge / discharge cycle of the energy storage battery, the predicted health status value is determined.

[0225] In some embodiments, the third processing module 430 can also be used for:

[0226] determine, based on the initial state of charge value, a battery capacity of the energy storage battery, and a target charging and discharging duration, a first state of charge value corresponding to the energy storage battery at the end of the target charging and discharging duration;

[0227] determine, based on the first state of charge value, the battery capacity, and a charging and discharging current corresponding to a next round of charging and discharging cycle, a theoretical charging and discharging time required by the energy storage battery to end the next round of charging and discharging cycle.

[0228] In some embodiments, the second processing module 420 can be further configured to determine, based on the ohmic internal resistance and an open circuit voltage of the energy storage battery, the initial state of charge value.

[0229] In some embodiments, the first processing module 410 can be further configured to:

[0230] determine, based on the actual working parameter, a battery loss of the energy storage battery in the first round of charging and discharging cycle;

[0231] determine, based on the battery loss and the actual working parameter, the ohmic internal resistance.

[0232] In some embodiments, the first processing module 410 can be further configured to:

[0233] based on the formula:

[0234]

[0235] determine the ohmic internal resistance, where R is the ohmic internal resistance, η loss is the battery loss, V bat is a charging and discharging voltage corresponding to the first round of charging and discharging cycle, t is a first charging and discharging time corresponding to the first round of charging and discharging cycle, Q bat is a charging and discharging electric quantity corresponding to the first round of charging and discharging cycle.

[0236] In some embodiments, the apparatus can further include a fourth processing module configured to reset, in a case where the energy storage battery ends the first round of charging and discharging cycle, a real-time state of charge value of the energy storage battery.

[0237] In some embodiments, the apparatus can further include:

[0238] a fifth processing module configured to, after determining, based on the initial state of charge value, a predicted state of health value corresponding to the energy storage battery in a next round of charging and discharging cycle, determine, based on actual charging and discharging parameters of the energy storage battery in the next round of charging and discharging cycle, a predicted battery efficiency of the energy storage battery in the next round of charging and discharging cycle;

[0239] a sixth processing module configured to determine, based on the predicted battery efficiency and the predicted state of health value, health state information of the energy storage battery, the health state information being used to control a working state of the energy storage battery.

[0240] In some embodiments, the sixth processing module can be further configured to:

[0241] determine that the energy storage battery is normal in a case where the predicted health status value is greater than the first threshold value and the predicted battery efficiency is within the target range.

[0242] determine that the energy storage battery is abnormal in a case where the predicted health status value is not greater than the first threshold value and / or the predicted battery efficiency is not within the target range.

[0243] In some embodiments, the apparatus can further include:

[0244] a seventh processing module configured to determine, after determining the predicted health status value corresponding to the next round of charging and discharging cycles of the energy storage system based on the initial state of charge value, the predicted health status value corresponding to the next round of charging and discharging cycles of the energy storage system based on an average of the plurality of predicted health status values corresponding to the plurality of energy storage batteries.

[0245] In some embodiments, the apparatus can further include:

[0246] an eighth processing module configured to, in a case where the energy storage system ends the first round of charging and discharging cycles, determine the ohmic internal resistance corresponding to the next round of charging and discharging cycles of the energy storage system based on the actual operating parameters corresponding to the first round of charging and discharging cycles of the energy storage system.

[0247] a ninth processing module configured to determine the initial state of charge value corresponding to the next round of charging and discharging cycles of the energy storage system based on the ohmic internal resistance corresponding to the energy storage system.

[0248] a tenth processing module configured to determine the predicted health status value corresponding to the next round of charging and discharging cycles of the energy storage system based on the initial state of charge value corresponding to the energy storage system.

[0249] The energy storage battery health status detection apparatus in the embodiments of the present application can be an energy storage battery or a component in the energy storage battery, such as an integrated circuit or a chip. The energy storage battery can be a terminal or other devices other than a terminal.

[0250] The energy storage battery health status detection apparatus in the embodiments of the present application can be an apparatus with an operating system. The operating system can be an Android operating system, an IOS operating system, or other possible operating systems, and the embodiments of the present application are not limited in this regard.

[0251] The energy storage battery health status detection apparatus provided in the embodiments of the present application can implement the method embodiments Figures 1 to 3 The method embodiments implement various processes, and to avoid repetition, details are not described herein.

[0252] The application also provides a storage system.

[0253] The storage system comprises at least one storage battery and the health state detection device of the storage battery as described in any of the above embodiments.

[0254] In the embodiment, the at least one storage battery is electrically connected with the health state detection device of the storage battery.

[0255] In some embodiments, the electrical connection comprises direct electrical connection and indirect electrical connection; and the electrical connection can be in the form of wired electrical connection and wireless communication connection.

[0256] For example, the battery module and the health state detection device of the storage battery can be connected through Bluetooth, wireless broadband or 5G, etc.

[0257] For another example, in the case where the electrical connection is in the form of indirect connection, the battery module and the health state detection device of the storage battery can be connected through an indirect signal transmission path established by a collector or a controller.

[0258] In actual application, the best connection mode can be selected based on actual requirements, which is not limited in the application.

[0259] The storage battery can be a lithium battery, a lead-acid battery and a graphene battery, etc., which is not limited in the application.

[0260] The health state detection device of the storage battery is used to execute the health state detection method of the storage battery as described in any of the above embodiments.

[0261] Figure 5 An example is shown in a structural schematic diagram of a storage battery 500, which comprises a processor 501, a memory 502 and a computer program stored in the memory 502 and executable on the processor 501, the program is executed by the processor 501 to realize each process of the above-mentioned health state detection method of the storage battery, and the same technical effects can be achieved, to avoid repetition, which will not be described here.

[0262] According to the storage battery provided by the embodiment of the application, the real-time ohmic resistance after each round of charge and discharge cycle is calculated, and the initial state of charge value of the storage battery in the next round of charge and discharge cycle is calculated based on the obtained ohmic resistance, which can effectively improve the accuracy of the initial state of charge value; then the SOH is predicted based on the obtained initial state of charge value, which can fully consider the influence of the battery resistance on the SOH, significantly improve the accuracy and accuracy of the finally obtained predicted health state value, and is simple to operate and easy to implement.

[0263] The embodiment of the present application further provides a non-transitory computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement each process of the health state detection method for the energy storage battery and achieve the same technical effects. To avoid repetition, details are not described herein.

[0264] The processor is the processor in the energy storage battery in the above-mentioned embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0265] The embodiment of the present application further provides a computer program product, which includes a computer program. The computer program is executed by a processor to implement the health state detection method for the energy storage battery.

[0266] The processor is the processor in the energy storage battery in the above-mentioned embodiments. The readable storage medium includes a computer readable storage medium, such as a computer readable only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0267] The embodiment of the present application further provides a chip, which includes a processor and a communication interface. The communication interface is coupled with the processor. The processor is configured to run a program or an instruction to implement each process of the health state detection method for the energy storage battery and achieve the same technical effects. To avoid repetition, details are not described herein.

[0268] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system level chip, a system chip, a chip system or a system on chip, etc.

[0269] It should be noted that, in this document, the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of additional identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the present application is not limited to the order of performing the functions shown or discussed, but can also include performing the functions in a substantially simultaneous manner or in a reverse order, for example, the described method can be performed in an order different from that described, and various steps can be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0270] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned example methods can be realized by means of software and necessary general hardware platforms, and of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer software product in essence or in the form of a part of the prior art that makes a contribution. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disc, an optical disc), and includes a plurality of instructions for causing a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0271] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above-mentioned specific embodiments, and the above-mentioned specific embodiments are only illustrative and not restrictive. Those skilled in the art can make many forms under the inspiration of the present application without departing from the scope of the present application and the scope protected by the claims.

[0272] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an illustrative embodiment", "an example", "a specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily mean the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0273] Although the embodiments of the present application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and purposes of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for detecting a state of health of an energy storage battery, characterized by, The method comprises: in the case that the energy storage battery ends a first round of charge and discharge cycle, determining an ohmic internal resistance corresponding to a next round of charge and discharge cycle of the energy storage battery based on actual working parameters of the energy storage battery corresponding to the first round of charge and discharge cycle; determining an initial state of charge value corresponding to the next round of charge and discharge cycle of the energy storage battery based on the ohmic internal resistance; determining a predicted state of health value corresponding to the next round of charge and discharge cycle of the energy storage battery based on the initial state of charge value; the determination of the ohmic internal resistance corresponding to the next round of charge and discharge cycle of the energy storage battery based on the actual working parameters of the energy storage battery corresponding to the first round of charge and discharge cycle comprises: determining a battery loss of the energy storage battery in the first round of charge and discharge cycle based on the actual working parameters; determining the ohmic internal resistance based on the battery loss and the actual working parameters; the determination of the ohmic internal resistance based on the battery loss and the actual working parameters comprises: based on the formula: determining the ohmic internal resistance, wherein R is the ohmic internal resistance, is the battery loss, is the first round of charge-discharge cycle corresponding charge-discharge voltage, t is the first round of charge-discharge cycle corresponding first charge-discharge time, is the first round of charge-discharge cycle corresponding charge-discharge electric quantity.

2. The method of state of health detection of an energy storage battery according to claim 1, characterized in that, the determination of the predicted state of health value corresponding to the next round of charge and discharge cycle of the energy storage battery based on the initial state of charge value comprises: determining a theoretical charge and discharge time required for the energy storage battery to end the next round of charge and discharge cycle based on the initial state of charge value; determining the predicted state of health value based on an actual charge and discharge time used by the energy storage battery to end the next round of charge and discharge cycle, the theoretical charge and discharge time, and a calibration state of health value corresponding to a target round of charge and discharge cycle.

3. The method of state of health detection of an energy storage cell according to claim 2, characterized in that the determination of the theoretical charge and discharge time required for the energy storage battery to end the next round of charge and discharge cycle based on the initial state of charge value comprises: determining a first state of charge value corresponding to the energy storage battery after a target charge and discharge time based on the initial state of charge value, a battery capacity of the energy storage battery, and the target charge and discharge time; determining the theoretical charge and discharge time required for the energy storage battery to end the next round of charge and discharge cycle based on the first state of charge value, the battery capacity, and a charge and discharge current corresponding to the next round of charge and discharge cycle.

4. The method of state of health detection of an energy storage cell according to any one of claims 1 to 3, characterized in that the determination of the initial state of charge value corresponding to the next round of charge and discharge cycle of the energy storage battery based on the ohmic internal resistance comprises: determining the initial state of charge value based on the ohmic internal resistance and an open circuit voltage of the energy storage battery.

5. The method of state of health detection of an energy storage cell according to any one of claims 1 to 3, characterized in that The method further comprises: in the case that the energy storage battery ends the first round of charge and discharge cycle, resetting a real-time state of charge value of the energy storage battery.

6. The method of state of health detection of an energy storage cell according to any one of claims 1 to 3, characterized in that after the determination of the predicted state of health value corresponding to the next round of charge and discharge cycle of the energy storage battery based on the initial state of charge value, the method further comprises: determining a predicted battery efficiency of the energy storage battery in the next round of charge and discharge cycle based on actual charge and discharge parameters of the energy storage battery in the next round of charge and discharge cycle; determining health state information of the energy storage battery based on the predicted battery efficiency and the predicted state of health value, the health state information being used to control a working state of the energy storage battery.

7. The method of state of health detection of an energy storage cell according to claim 6, characterized in that determining the state of health information of the energy storage battery based on the predicted battery efficiency and the predicted state of health value, comprises: in the case that the predicted state of health value is greater than a first threshold and the predicted battery efficiency is in a target range, determining that the energy storage battery is normal; in the case that the predicted state of health value is not greater than the first threshold and / or the predicted battery efficiency is not in the target range, determining that the energy storage battery is abnormal.

8. The method of state of health detection of an energy storage cell according to any one of claims 1 to 3, characterized in that The state of health detection method of the energy storage battery is applied to an energy storage system, the energy storage system comprising a plurality of energy storage batteries, and the method further comprises: after determining the predicted state of health value of the energy storage battery corresponding to the next round of charging and discharging cycle based on the initial state of charge value, determining a predicted state of health value of the energy storage system corresponding to the next round of charging and discharging cycle based on an average value of a plurality of predicted state of health values corresponding to the plurality of energy storage batteries; and / or, in the case that the energy storage system ends the first round of charging and discharging cycle, determining an ohmic internal resistance of the energy storage system corresponding to the next round of charging and discharging cycle based on actual working parameters of the energy storage system corresponding to the first round of charging and discharging cycle; determining an initial state of charge value of the energy storage system corresponding to the next round of charging and discharging cycle based on the ohmic internal resistance of the energy storage system; determining a predicted state of health value of the energy storage system corresponding to the next round of charging and discharging cycle based on the initial state of charge value of the energy storage system.

9. A device for detecting a state of health of an energy storage battery, characterized by comprises: a first processing module configured to, in the case that the energy storage battery ends the first round of charging and discharging cycle, determine an ohmic internal resistance of the energy storage battery corresponding to the next round of charging and discharging cycle based on actual working parameters of the energy storage battery corresponding to the first round of charging and discharging cycle; a second processing module configured to determine an initial state of charge value of the energy storage battery corresponding to the next round of charging and discharging cycle based on the ohmic internal resistance; a third processing module configured to determine a predicted state of health value of the energy storage battery corresponding to the next round of charging and discharging cycle based on the initial state of charge value; the first processing module is further configured to determine a battery loss of the energy storage battery in the first round of charging and discharging cycle based on the actual working parameters, and determine the ohmic internal resistance based on the battery loss and the actual working parameters; based on the formula: determining the ohmic internal resistance, wherein R is the ohmic internal resistance, is the battery loss, is the first round of charge-discharge cycle corresponding charge-discharge voltage, t is the first round of charge-discharge cycle corresponding first charge-discharge time, is the first round of charge-discharge cycle corresponding charge-discharge electric quantity.

10. An energy storage system characterized by, comprises: at least one energy storage battery; The state of health detection device of the energy storage battery according to claim 9 is electrically connected with the at least one energy storage battery.

11. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the state of health detection method of the energy storage battery according to any one of claims 1-8.

12. A computer program product comprising a computer program, characterized in that, The computer program is executed by a processor to implement the state of health detection method of the energy storage battery according to any one of claims 1-8.

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