Energy storage battery life evaluation method and related device

Abstract

The invention belongs to a battery life evaluation method, and aims to solve the technical problems that a method for evaluating the service life of a battery by simulating working conditions in a laboratory has relatively large working condition difference between test conditions and actual application scenes of the battery and cannot truly reflect the performance degradation trend of the energy storage battery under the actual application working conditions. According to the energy storage battery service life evaluation method and the related device, the service life of the energy storage battery can be rapidly evaluated by means of an energy storage battery service life attenuation function, and corresponding experimental data are obtained through a cycle life experiment and a calendar life experiment under different experimental simulation working conditions; the cycle life experiment data and the calendar life experiment data under different experiment simulation working conditions are fitted and then superposed, a cycle life attenuation function and a calendar life attenuation function are obtained, interval division is carried out through actual historical data of the energy storage battery, and simulation experiment results are corrected.

Description

Technical Field

[0001] The present application relates to a battery life evaluation method, and specifically to an energy storage battery life evaluation method and related devices. Background Art

[0002] Battery life is usually divided into cycle life and calendar life. Energy storage batteries face various dynamic and complex factors that cause the degradation of battery health status throughout their life cycle. Different factors have different mechanisms and degrees of influence on the cycle life and calendar life of energy storage batteries.

[0003] At present, the battery life is generally evaluated by simulating working conditions in the laboratory. However, when simulating working conditions, the cycle life or calendar life of the energy storage battery under a certain factor is mostly evaluated under a single factor. The test conditions are quite different from the working conditions in the actual application scenarios of the battery. In the context of continuous innovation in energy storage technology, accelerated product update and iteration rate, and continuous expansion of energy storage application scenarios, conventional evaluation methods cannot truly reflect the performance degradation trend of energy storage batteries under actual application conditions. Summary of the invention

[0004] The present application is directed to a method for evaluating battery life by simulating working conditions in a laboratory. However, there is a technical problem that the test conditions are quite different from the working conditions in the actual application scenarios of the battery and the performance degradation trend of the energy storage battery under the actual application conditions cannot be truly reflected. A method for evaluating the life of an energy storage battery and related devices are provided.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application proposes a method for evaluating the life of an energy storage battery, comprising: Obtain the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery; The real-time data of the energy storage battery is input into the energy storage battery life decay function to obtain the energy storage battery life evaluation result; the method for obtaining the energy storage battery life decay function includes: Acquire cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data; The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively. Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charge and discharge state and the static state according to the distribution of the historical cycle life influencing factor data under the charge and discharge state and the distribution of the historical calendar life influencing factor data under the static state; The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

[0006] Furthermore, the cycle life influencing factor data includes temperature, charge and discharge rate and charge and discharge depth; The calendar life influencing factor data include temperature and energy state.

[0007] Furthermore, the cycle life test data of the energy storage battery under different experimental simulation conditions is obtained, including: On the basis of the cycle life standard test simulation conditions, the data of each cycle life influencing factor are adjusted respectively, and a preset number of cycles are performed under each cycle life influencing factor data to obtain the energy decay rate under different experimental simulation conditions as the cycle life experimental data under different experimental simulation conditions; Obtain calendar life test data of energy storage batteries under different experimental simulation conditions, including: On the basis of calendar life standard test simulation conditions, the data of each calendar life influencing factor are adjusted respectively. The energy storage battery is left for a preset time under each calendar life influencing factor data to obtain the energy decay rate under different experimental simulation conditions as the calendar life experimental data under different experimental simulation conditions.

[0008] Furthermore, the calculation method of the cycle life attenuation function includes: Eloss -1 =λ1×Eloss -1-1 (T1) + λ2 × Eloss -1-2 (P) + λ3 × Eloss -1-3 (DOD) Among them, Eloss -1 is the cycle life attenuation function, λ1 is the cycle life attenuation function weight that changes with temperature, λ2 is the cycle life attenuation function weight that changes with charge and discharge rate, λ3 is the cycle life attenuation function weight that changes with charge and discharge depth, Eloss -1-1 (T1) is the cycle life attenuation function that changes with temperature, Eloss -1-2 (P) is the cycle life attenuation function that changes with the charge and discharge rate, Eloss -1-3(DOD) is the cycle life attenuation function that changes with the charge and discharge depth, T1 is the average battery temperature in the battery charge and discharge operating range, P is the battery charge and discharge power in the battery charge and discharge operating range, and DOD is the battery charge and discharge depth in the battery charge and discharge operating range.

[0009] Furthermore, the cycle life attenuation function that varies with temperature includes: E loss-1-1 (T1) = A1exp(-A2 / T1) × n A3 Among them, A1 is the correction coefficient in the cycle life attenuation function, A2 is the coefficient related to the activation energy in the cycle life attenuation function, A3 is the coefficient related to the battery material system in the cycle life attenuation function, and n is the number of charge and discharge cycles; The cycle life attenuation function that varies with the charge and discharge rate includes: E loss-1-2 (P) = f (P) Among them, f(P) is the function of cycle life changing with charge and discharge rate obtained by fitting the experimental data at different charge and discharge rates; The cycle life attenuation function that varies with charge and discharge depth includes: E loss-1-3 (DOD)=f(DOD).

[0010] Furthermore, the calculation method of the calendar life decay function includes: E loss-2 =η1×E loss-2-1 (T2)+η2×E loss-2-2 (SOE) Among them, E loss-2 is the calendar life decay function, E loss-2-1 (T2) is the battery calendar life decay function that changes with temperature, E loss-2-2 (SOE) is the battery calendar life decay function that changes with the energy state, T2 is the average temperature of the battery during the battery storage time, SOE is the energy state of the battery when it is stored, η1 is the weight of the battery calendar life decay function that changes with temperature, and η2 is the weight of the battery calendar life decay function that changes with the energy state.

[0011] Furthermore, the battery calendar life decay function that varies with temperature includes: E loss-2-1 (T2) = B1exp(-B2 / T2) × t B3 Among them, B1 is the correction coefficient in the battery calendar life decay function, B2 is the coefficient related to the activation energy in the battery calendar life decay function, and B3 is the coefficient related to the battery material system in the battery calendar life decay function; The battery calendar life decay function that changes with the energy state includes: E loss-2 (SOE) = f(SOE).

[0012] In a second aspect, the present application proposes a system for evaluating the life of an energy storage battery, comprising: An acquisition module is used to acquire the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery; The evaluation module is used to input the real-time data of the energy storage battery into the energy storage battery life decay function to obtain the energy storage battery life evaluation result; the method for obtaining the energy storage battery life decay function includes: Acquire cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data; The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively. Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charge and discharge state and the static state according to the distribution of the historical cycle life influencing factor data under the charge and discharge state and the distribution of the historical calendar life influencing factor data under the static state; The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

[0013] In a third aspect, the present application proposes an electronic device, comprising: a memory, and one or more processors; the memory is coupled to the processor; wherein computer program code is stored in the memory, and the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the steps of the above-mentioned energy storage battery life evaluation method.

[0014] In a fourth aspect, the present application proposes a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned energy storage battery life evaluation method are implemented.

[0015] Compared with the prior art, this application has the following beneficial effects: The present application proposes a method for evaluating the life of an energy storage battery. It only needs to obtain the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery, and the energy storage battery life attenuation function can be used to quickly complete the evaluation of the energy storage battery life, and the present application comprehensively considers the overall evaluation of the cycle life and calendar life. The present application first obtains the corresponding experimental data through the cycle life experimental data and calendar life experimental data under different experimental simulation conditions, and respectively fits the cycle life experimental data and calendar life experimental data under different experimental simulation conditions and superimposes them to obtain the cycle life attenuation function and the calendar life attenuation function, and then divides the intervals through the actual historical data of the energy storage battery, corrects the simulated experimental results, and then obtains the energy storage battery life attenuation function for evaluation that is more in line with the actual working conditions. The present application makes the battery life attenuation closely related to the actual application scenario, can intuitively evaluate the impact of the dynamic changes of key influencing factors on the battery life, and facilitates more accurate evaluation of the health status of the energy storage battery.

[0016] The present application also proposes an energy storage battery life evaluation system, an electronic device and a computer storage medium, which have all the advantages of the above-mentioned energy storage battery life evaluation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A first flow chart of a method for evaluating the life of an energy storage battery in this application; Figure 2 A second flow chart of a method for evaluating the life of an energy storage battery according to the present application; Figure 3 A schematic diagram of an energy storage battery life evaluation system for the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0021] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0022] In the description of the embodiments of the present application, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the invented product is usually placed when used. It is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0023] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0024] In the description of the embodiments of the present application, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0025] The assessment of battery life is a key link in ensuring the reliability and economy of energy storage systems, and is directly related to the battery's operating cost, maintenance frequency, and overall system energy efficiency. Battery life is usually divided into two dimensions: cycle life and calendar life. Cycle life refers to the process in which the performance (such as capacity, internal resistance, etc.) of a battery drops to a preset threshold after a certain number of charge and discharge cycles. Calendar life refers to the time span from the date of production of the battery, regardless of whether it is used, until the performance gradually declines over time until it no longer meets the application requirements.

[0026] During their entire life cycle, energy storage batteries are affected by a variety of dynamic and complex internal and external factors, which work together to affect the health of the battery, causing its performance to gradually deteriorate. Internal factors may include aging of battery materials, electrolyte decomposition, loss of active substances, etc.; external factors include temperature changes, charge and discharge rates, discharge depth, overcharge and overdischarge, and environmental factors (such as humidity, vibration, etc.). These factors not only act alone, but may also be intertwined to form a complex coupling effect, further exacerbating the complexity of battery performance degradation.

[0027] Currently, laboratory simulation of working conditions is one of the mainstream methods for evaluating battery life, but this method has significant limitations. First, simulation conditions often simplify or focus on a single factor, such as only considering temperature effects, specific charge and discharge cycle modes, etc., while ignoring the combined effects and dynamic changes of these factors in actual applications. Secondly, it is difficult for the laboratory environment to fully replicate the complex working conditions in actual use scenarios, such as irregular scheduling requirements in power grid energy storage systems, which will lead to large deviations between laboratory test results and actual application performance.

[0028] Based on the above situation, the present application proposes a method for evaluating the life of an energy storage battery, which is described in detail below in conjunction with embodiments and drawings.

[0029] like Figure 1 As shown, it is a first flow chart of the energy storage battery life evaluation method of the present application, which may include: S101, obtaining current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery.

[0030] In practical applications, when evaluating energy storage batteries, it is necessary to first obtain the current real-time status information of the energy storage batteries for subsequent life assessment. Cycle life influencing factor data may include charge and discharge current, charge and discharge depth, charge and discharge rate, charge and discharge times, temperature changes during charge and discharge, etc.; while calendar life influencing factor data may include battery storage temperature, storage time, storage energy state, etc. These data can be obtained in real time through the battery management system or other monitoring equipment. The specific selected influencing factors can be adjusted according to the evaluation requirements.

[0031] S102, inputting the real-time data of the energy storage battery into the energy storage battery life decay function to obtain the energy storage battery life evaluation result.

[0032] It should be noted that the energy storage battery life evaluation results are used to characterize the energy storage battery life attenuation, and integrate the calendar life and cycle life.

[0033] The method for obtaining the energy storage battery life decay function includes: (1) Obtaining cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data.

[0034] In a laboratory environment, by simulating various possible operating conditions (such as different charging and discharging conditions, temperature conditions, etc.), the energy storage battery can be tested for cycle life and calendar life. These tests will generate a large amount of experimental data, which may include battery capacity attenuation and internal resistance changes under different operating conditions.

[0035] (2) The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively.

[0036] Analyze the collected cycle life test data and calendar life test data, and use mathematical or statistical methods (such as regression analysis, neural network, etc.) to fit the data to obtain a function that describes the change of battery performance with cycle number and time. Then, superimpose the cycle life attenuation function and calendar life attenuation function to comprehensively consider the impact of both on battery life. (3) Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charging and discharging state and the static state according to the distribution of the historical cycle life influencing factor data under the charging and discharging state and the distribution of the historical calendar life influencing factor data under the static state.

[0037] Collect the operation data of energy storage batteries in the past period of time, including historical cycle life influencing factor data and historical calendar life influencing factor data. These data will be used to further refine the life decay function to improve the accuracy of the assessment. By analyzing historical data, we can understand the performance change characteristics of energy storage batteries under different conditions. According to these characteristics, the battery life decay process is divided into multiple intervals, each of which corresponds to a different charge and discharge state or static state. This can more accurately describe the life decay law of energy storage batteries under different conditions.

[0038] (4) The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

[0039] The present application can obtain a battery life decay function that can comprehensively consider the effects of cycle life and calendar life and is described in segments. This function can be used to evaluate the remaining life of the battery at different time points and under different conditions.

[0040] like Figure 2As shown, it is a first flow chart of the energy storage battery life evaluation method of the present application, which may include: S201, determine the main influencing factors of the energy storage battery life.

[0041] In practical applications, the energy decay of energy storage batteries during cyclic charge and discharge, i.e., cycle life, is mainly related to factors such as temperature, charge and discharge rate, and charge and discharge depth, which can be used as factors affecting cycle life. Among them, too high or too low temperature may cause the chemical reaction inside the battery to accelerate or slow down, thus affecting the battery life. The charge and discharge rate refers to the speed at which the battery is charged and discharged. If the charge and discharge speed is too fast, the battery temperature will rise or the electrode material structure will be damaged, resulting in a shortened life. The charge and discharge depth refers to the percentage of the battery's charge and discharge each time. Deep charge and discharge will accelerate the aging of the battery because the battery is more vulnerable to damage when fully charged and fully discharged.

[0042] The energy decay of energy storage batteries during storage, i.e., calendar life, is mainly related to temperature and energy state, which can be used as factors affecting calendar life. Temperature is also an important factor affecting calendar life, and a suitable storage temperature can extend the calendar life of the battery. Regarding energy state, it is better to store the battery in a partially charged state than in a fully charged or fully discharged state.

[0043] S202, designing experimental simulation conditions, obtaining battery life experimental data of energy storage batteries under the experimental simulation conditions, and establishing an energy storage battery simulation condition database.

[0044] Energy storage battery manufacturers usually define the rated charge and discharge power as 1P, and use the 1P 100%DOD full charge and discharge cycle condition at 25°C as the standard experimental simulation condition for the battery cycle life, and the battery calendar life under 50%SOE shelf conditions at 25°C as the standard test condition for the battery calendar life.

[0045] For the cycle life of energy storage batteries, there are three main influencing factors: temperature, charge and discharge rate, and charge and discharge depth. On the basis of the standard experimental simulation conditions of the cycle life, the values ​​of the three main influencing factors are adjusted respectively, and orthogonal cycle charge and discharge tests with different temperatures, charge and discharge rates, and charge and discharge depths are carried out. In practical applications, the temperature can be set to 25°C, 45°C, 5°C, etc., the charge and discharge rate can be set to 1P, 0.5P, etc., and the charge and discharge depth can be set to 100% DOD, 90% DOD (5%~95% SOE), 50% DOD (25%~75% SOE), 20% DOD (40%~60% SOE), etc. For every 50 cycles, the charge and discharge energy calibration is carried out to obtain the energy decay rate under different simulation conditions, and establish a battery cycle life simulation condition database under different experimental simulation conditions.

[0046] The calendar life of energy storage batteries mainly has two influencing factors: temperature and energy state. Based on the calendar life standard experimental simulation conditions, the values ​​of the two main influencing factors are adjusted respectively, and shelf tests are carried out at different temperatures and different energy states. The temperature can be set to 25°C, 45°C, 5°C, etc., and the energy state can be set to 50% SOE, 100% SOE, 10% SOE, etc. Every half a month of shelving, a charge and discharge energy calibration is carried out to obtain the energy decay rate at different shelving time nodes, and a battery calendar life simulation condition database under different experimental simulation conditions is established.

[0047] The above charge and discharge energy calibration is to obtain the actual charge and discharge energy of the battery by subjecting the battery to charge and discharge cycles at 1P at 25°C.

[0048] S203, fitting the data of the energy storage battery under different cycle life experimental simulation conditions, and obtaining the energy attenuation rate function of the energy storage battery under single variables such as temperature, charge and discharge rate, and charge and discharge depth.

[0049] Battery cycle life decay function as a function of temperature: E loss-1-1 (T1) = A1exp(-A2 / T1) × n A3 Among them, A1 is the correction coefficient in the cycle life attenuation function, A2 is the coefficient related to the activation energy in the cycle life attenuation function, and A3 is the coefficient related to the battery material system in the cycle life attenuation function, all of which are obtained by fitting the experimental data at different temperatures, n is the number of charge and discharge cycles, and T1 is the average battery temperature in the battery charge and discharge operating range.

[0050] Cycle life decay function with charge and discharge rate: E los-1-2 (P) = f (P) Among them, f(P) is the function of cycle life changing with charge and discharge rate obtained by fitting the experimental data at different charge and discharge rates.

[0051] Cycle life decay function that varies with charge and discharge depth, including: E loss-1-3 (DOD)=f(DOD).

[0052] DOD is the battery charge and discharge depth in the battery charge and discharge operating range.

[0053] Therefore, the battery cycle life attenuation function Eloss -1 for: Eloss -1 =λ1×Eloss -1-1 (T1) + λ2 × Eloss -1-2(P) + λ3 × Eloss -1-3 (DOD) Among them, λ1 is the weight of the cycle life attenuation function that changes with temperature, λ2 is the weight of the cycle life attenuation function that changes with charge and discharge rate, and λ3 is the weight of the cycle life attenuation function that changes with charge and discharge depth. Battery cycle life attenuation function Eloss -1 It is obtained by fitting the battery cycle attenuation data under multiple variables such as temperature, charge and discharge rate, and charge and discharge depth.

[0054] S204, fitting the data of the energy storage battery under different calendar life test simulation conditions, and obtaining the energy decay rate function of the energy storage battery under single variables such as temperature and energy state.

[0055] Battery calendar life decay function E as it changes with temperature loss-2-1 (T2): E loss-2-1 (T2) = B1exp(-B2 / T2) × t B3 Among them, B1 is the correction coefficient in the battery calendar life decay function, B2 is the coefficient related to the activation energy in the battery calendar life decay function, and B3 is the coefficient related to the battery material system in the battery calendar life decay function, which are obtained by fitting the experimental data at different temperatures.

[0056] Battery calendar life decay function E as the energy state changes loss-2 (SOE): E loss-2 (SOE) = f(SOE) Among them, T2 is the average temperature of the battery during the battery storage time, and SOE is the energy state of the battery during the storage time.

[0057] Therefore, the calendar life decay function E loss-2 : E loss-2 =η1×E loss-2-1 (T2)+η2×E loss-2-2 (SOE) Among them, η1 is the weight of the battery calendar life decay function that changes with temperature, and η2 is the weight of the battery calendar life decay function that changes with energy state. The calendar life decay function is obtained by fitting the battery calendar life decay data under multiple variables such as temperature and energy state.

[0058] S205, obtaining historical operating parameters of the energy storage battery in the energy storage system within a certain time range, determining the main distribution of battery parameters under charging, discharging and static conditions, and dividing the entire life decay time of the battery into multiple intervals according to different charging and discharging cycle conditions and storage conditions.

[0059] Historical operating parameters may include temperature, charge and discharge power, charge and discharge depth, energy status and other data.

[0060] S206, determining the energy storage battery life decay function.

[0061] The energy storage battery life decay function is: E loss =

[0062] Among them, m is the number of operating condition intervals. That is, the energy storage battery life decay function is equal to the sum of the cycle life decay function and the calendar life decay function under multiple operating condition intervals.

[0063] This application determines the main influencing factors of the life of energy storage batteries, establishes a database of simulated working conditions for energy storage batteries, fits the simulated working condition data, establishes the cycle life and calendar life attenuation model functions, and combines the actual operating condition data of energy storage batteries to obtain the battery total life attenuation function. It can accurately evaluate the life of energy storage batteries.

[0064] like Figure 3 As shown, it is a schematic diagram of a storage battery life evaluation system of the present application, which may include: An acquisition module is used to acquire the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery; The evaluation module is used to input the real-time data of the energy storage battery into the energy storage battery life decay function to obtain the energy storage battery life evaluation result; the method for obtaining the energy storage battery life decay function includes: Acquire cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data; The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively. Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charge and discharge state and the static state according to the distribution of the historical cycle life influencing factor data under the charge and discharge state and the distribution of the historical calendar life influencing factor data under the static state; The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

[0065] It should be noted that in the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of each module is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another device, or some features can be ignored or not executed. The module described as a separate component may or may not be physically separated. The component displayed as a module may be a physical unit or multiple physical units, that is, it may be located in one place, or it may be distributed in multiple different places. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0066] In addition, each module in each embodiment of the present invention may be integrated into a processing unit, each module may exist physically separately, or two or more modules may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0067] An embodiment of the present application also provides an electronic device, which may include one or more processors, a memory, and a communication interface.

[0068] The memory, the communication interface and the processor are coupled, for example, the memory, the communication interface and the processor may be coupled together via a bus.

[0069] The communication interface is used for data transmission with other devices. The memory stores computer program code. The computer program code includes computer instructions. When the computer instructions are executed by the processor, the electronic device executes the steps of the above-mentioned energy storage battery life evaluation method.

[0070] Wherein, the processor can be a processor or a controller, for example, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the present disclosure. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of DSP and microprocessors, and the like. The processor can be used to support electronic devices to execute the method steps provided in the above embodiments.

[0071] The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The above bus may be divided into an address bus, a data bus, a control bus, etc.

[0072] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of evaluating the life of the energy storage battery are implemented.

[0073] The computer-readable storage medium involved in the present application includes random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in the technical field.

[0074] For the description of the relevant parts of the energy storage battery life evaluation system, electronic device, and computer-readable storage medium provided in the embodiments of the present application, please refer to the detailed description of the corresponding parts in the energy storage battery life evaluation method provided in the embodiments of the present application, which will not be repeated here. In addition, the parts of the above technical solutions provided in the embodiments of the present application that are consistent with the implementation principles of the corresponding technical solutions in the prior art are not described in detail to avoid excessive elaboration.

[0075] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating the life of an energy storage battery, characterized in that: include: Obtain the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery; Input the real-time data of the energy storage battery into the energy storage battery life decay function to obtain the energy storage battery life evaluation result; The method for obtaining the energy storage battery life decay function includes: Acquire cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data; The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively. Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charge and discharge state and the static state according to the distribution of the historical cycle life influencing factor data under the charge and discharge state and the distribution of the historical calendar life influencing factor data under the static state; The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

2. A method for evaluating the life of an energy storage battery according to claim 1, characterized in that: The cycle life influencing factor data include temperature, charge and discharge rate and charge and discharge depth; The calendar life influencing factor data include temperature and energy state.

3. A method for evaluating the life of an energy storage battery according to claim 2, characterized in that: Obtain the cycle life test data of energy storage batteries under different experimental simulation conditions, including: On the basis of the cycle life standard test simulation conditions, the data of each cycle life influencing factor are adjusted respectively, and a preset number of cycles are performed under each cycle life influencing factor data to obtain the energy decay rate under different experimental simulation conditions as the cycle life experimental data under different experimental simulation conditions; Obtain calendar life test data of energy storage batteries under different experimental simulation conditions, including: On the basis of the calendar life standard test simulation conditions, the data of each calendar life influencing factor are adjusted respectively. The energy storage battery is placed for a preset time under each calendar life influencing factor data to obtain the energy decay rate under different experimental simulation conditions as the calendar life experimental data under different experimental simulation conditions.

4. A method for evaluating the life of an energy storage battery according to claim 3, characterized in that: The calculation method of the cycle life attenuation function comprises: Elos -1 =λ1×Eloss -1-1 (T1)+λ2×Eloss -1-2 (P)+λ3×Eloss -1-3 (DEAD) Among them, Eloss -1 is the cycle life attenuation function, λ1 is the cycle life attenuation function weight that changes with temperature, λ2 is the cycle life attenuation function weight that changes with charge and discharge rate, λ3 is the cycle life attenuation function weight that changes with charge and discharge depth, Eloss -1-1 (T1) is the cycle life attenuation function that changes with temperature, Eloss -1-2 (P) is the cycle life attenuation function that changes with the charge and discharge rate, Eloss -1-3 (DOD) is the cycle life attenuation function that changes with the charge and discharge depth, T1 is the average battery temperature in the battery charge and discharge operating range, P is the battery charge and discharge power in the battery charge and discharge operating range, and DOD is the battery charge and discharge depth in the battery charge and discharge operating range.

5. A method for evaluating the life of an energy storage battery according to claim 4, characterized in that: The cycle life attenuation function that varies with temperature includes: <h2 style=";text-align:left;direction:ltr">E<h2 style=";text-align:left;direction:ltr"> loss-1-1 <h2 style=";text-align:left;direction:ltr"> (T1)=A1exp(-A2 / T1)×n<h2 style=";text-align:left;direction:ltr"> A3 Among them, A1 is the correction coefficient in the cycle life attenuation function, A2 is the coefficient related to the activation energy in the cycle life attenuation function, A3 is the coefficient related to the battery material system in the cycle life attenuation function, and n is the number of charge and discharge cycles; The cycle life attenuation function that varies with the charge and discharge rate includes: E loss-1-2 (P)=f(P) Among them, f(P) is the function of cycle life changing with charge and discharge rate obtained by fitting the experimental data at different charge and discharge rates; The cycle life attenuation function that varies with charge and discharge depth includes: IN loss-1-3 (DOD)=f(DOD)。 6. A method for evaluating the life of an energy storage battery according to claim 3, characterized in that: The calculation method of the calendar life decay function includes: AND loss-2 =η1×E loss-2-1 (T2)+η2×E loss-2-2 (SOE) Among them, E loss-2 is the calendar life decay function, E loss-2-1 (T2) is the battery calendar life decay function that changes with temperature, E loss-2-2 (SOE) is the battery calendar life decay function that changes with the energy state, T2 is the average temperature of the battery during the battery storage time, SOE is the energy state of the battery when it is stored, η1 is the weight of the battery calendar life decay function that changes with temperature, and η2 is the weight of the battery calendar life decay function that changes with the energy state.

7. A method for evaluating the life of an energy storage battery according to claim 6, characterized in that: The battery calendar life decay function that varies with temperature includes: <h2 style=";text-align:left;direction:ltr">E<h2 style=";text-align:left;direction:ltr"> loss-2-1 <h2 style=";text-align:left;direction:ltr"> (T2) = B1exp(-B2 / T2)×t<h2 style=";text-align:left;direction:ltr"> B3 Among them, B1 is the correction coefficient in the battery calendar life decay function, B2 is the coefficient related to the activation energy in the battery calendar life decay function, and B3 is the coefficient related to the battery material system in the battery calendar life decay function; The battery calendar life decay function that changes with the energy state includes: AND loss-2 (SOE)=f(SOE)。 8. A storage battery life evaluation system, characterized in that: include: An acquisition module is used to acquire the current cycle life influencing factor data and calendar life influencing factor data of the energy storage battery as real-time data of the energy storage battery; An evaluation module is used to input the real-time data of the energy storage battery into the energy storage battery life decay function to obtain the energy storage battery life evaluation result; The method for obtaining the energy storage battery life decay function includes: Acquire cycle life test data and calendar life test data of the energy storage battery under different experimental simulation conditions; the different experimental simulation conditions include different settings of cycle life influencing factor data and calendar life influencing factor data; The cycle life test data and calendar life test data under different experimental simulation conditions are fitted and superimposed to obtain the cycle life attenuation function and calendar life attenuation function respectively. Obtain historical cycle life influencing factor data and historical calendar life influencing factor data of the energy storage battery within a preset time range, and divide the energy storage battery life decay time into multiple intervals according to the charge and discharge state and the static state according to the distribution of the historical cycle life influencing factor data under the charge and discharge state and the distribution of the historical calendar life influencing factor data under the static state; The sum of the cycle life decay function and the calendar life decay function in each interval is taken as the energy storage battery life decay function.

9. An electronic device, characterized in that: include: A memory and one or more processors; the memory is coupled to the processor; wherein the memory stores computer program code, the computer program code includes computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the steps of the energy storage battery life evaluation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the energy storage battery life evaluation method according to any one of claims 1 to 7 are implemented.

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