Lithium battery discharge capacity estimation model acquisition method, estimation method, electronic device and storage medium

Abstract

The embodiments of the present invention relate to the field of lithium battery technology, and in particular to a method for obtaining a lithium battery dischargeable capacity estimation model, a lithium battery dischargeable capacity estimation method, an electronic device, and a storage medium, wherein the acquisition method comprises: testing the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test; based on the test data, fitting the model parameters of the dischargeable capacity estimation model to obtain the dischargeable capacity estimation model. The method for obtaining a lithium battery dischargeable capacity estimation model provided by the embodiments of the present invention only requires a small amount of testing of the lithium battery under preset experimental conditions, and the dischargeable capacity estimation model is obtained by fitting the test data obtained from the test, thereby greatly reducing the test time and cost.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of lithium batteries, and in particular to a method for obtaining a lithium battery dischargeable capacity estimation model, a lithium battery dischargeable capacity estimation method, an electronic device, and a storage medium. Background Art

[0002] At present, lithium-ion batteries have the advantages of high energy density, high power density, many cycles, and long storage time. They have broad application prospects in large and medium-sized electric equipment such as electric vehicles and energy storage facilities. The discharge capacity / current capacity of lithium batteries is indispensable in the estimation of lithium battery SOC (State of Charge, which refers to the ratio of the current remaining power of the battery to the current capacity of the battery, usually expressed as a percentage). The lithium battery SOC to a certain extent indicates the approximate remaining power and working time of the lithium battery when maintaining the current working conditions. For power lithium batteries, it can effectively help estimate the remaining mileage.

[0003] In the prior art, the discharge capacity under different working conditions is usually obtained through a large number of experiments, and then the real-time discharge capacity of the lithium battery during operation is directly obtained by the table lookup method. However, the table lookup method requires a large number of offline tests for different types of lithium batteries, which consumes a lot of testing time and has high testing costs. In addition, the real-time discharge capacity under different operating processes is easily affected by other environmental factors. The discharge capacity of the lithium battery obtained by the table lookup method may be inaccurate, resulting in a decrease in the accuracy of the lithium battery capacity estimation. Summary of the invention

[0004] In view of this, an object of an embodiment of the present invention is to provide a method for obtaining a lithium battery dischargeable capacity estimation model, a lithium battery dischargeable capacity estimation method, an electronic device and a storage medium. The method performs a small amount of tests on the lithium battery under preset experimental conditions, and obtains a dischargeable capacity estimation model by fitting the test data obtained from the test, thereby greatly reducing testing time and cost.

[0005] To solve the above technical problems, the embodiments of the present invention provide the following technical solutions:

[0006] In a first aspect, an embodiment of the present invention provides a method for obtaining a dischargeable capacity estimation model of a lithium battery, the method comprising:

[0007] Testing the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test;

[0008] Based on the test data, model parameters of the dischargeable capacity estimation model are fitted to obtain the dischargeable capacity estimation model.

[0009] In some embodiments, the test data includes: the test capacity and the rated capacity of the lithium battery, and the model parameters of the dischargeable capacity estimation model are fitted based on the test data, including:

[0010] The rated capacity of the lithium battery, various temperatures and various currents, and the test capacity corresponding to the temperature and current are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain model parameters of the dischargeable capacity estimation model.

[0011] In some embodiments, the model parameters have initial values, and the rated capacity, various temperatures, and various currents of the lithium battery, as well as the test capacity corresponding to the temperature and current are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain the model parameters of the dischargeable capacity estimation model, including the following steps:

[0012] S1: Substituting the rated capacity, temperature, current and current model parameters of the lithium battery into the dischargeable capacity estimation model to obtain an estimated capacity;

[0013] S2: Obtaining a capacity estimation error based on the estimated capacity and the test capacity corresponding to the temperature and current;

[0014] S3: updating the current model parameters based on the capacity estimation error;

[0015] S4: Repeat the above steps S1 to S3 until the capacity estimation error is less than or equal to the first threshold value, the dischargeable capacity estimation model converges, and the model parameters of the dischargeable capacity estimation model are obtained.

[0016] In some embodiments, the testing of the lithium battery under preset experimental conditions includes:

[0017] At a current preset temperature, testing the lithium battery with a plurality of constant preset currents corresponding to the current preset temperature;

[0018] After the lithium battery test is completed at the current preset temperature with several constant preset currents corresponding to the current preset temperature, the lithium battery is continued to be tested at the next preset temperature with several constant preset currents corresponding to the next preset temperature until the lithium battery test is completed under all preset experimental conditions.

[0019] In some embodiments, the discharge capacity estimation model is formulated as follows:

[0020]

[0021]

[0022] in, , , , , and are model parameters of the dischargeable capacity estimation model, and are the test capacity and rated capacity of the lithium battery respectively, and are the current and temperature of the lithium battery respectively.

[0023] In some embodiments, the test is a hybrid power pulse characteristic test.

[0024] In some embodiments, the nonlinear fitting algorithm is any one of an iterative least squares algorithm, a recursive least squares algorithm, a recursive augmented least squares algorithm, and a recursive least squares algorithm with a forgetting factor.

[0025] In a second aspect, an embodiment of the present invention provides a method for estimating the dischargeable capacity of a lithium battery, comprising:

[0026] Acquire status data of the lithium battery to be estimated, wherein the status data includes the rated capacity, current temperature and current current of the lithium battery to be estimated;

[0027] Based on the state data, using a dischargeable capacity estimation model, estimating the dischargeable capacity of the lithium battery to be estimated;

[0028] The dischargeable capacity estimation model is obtained by adopting any of the lithium battery dischargeable capacity estimation model acquisition methods proposed in the first aspect.

[0029] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0030] A processor and a memory communicatively connected to the processor;

[0031] The memory stores computer program instructions executable by the processor. When the computer program instructions are called by the processor, the processor executes any one of the lithium battery dischargeable capacity estimation model acquisition methods proposed in the first aspect, or executes the lithium battery dischargeable capacity estimation method proposed in the second aspect.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which computer program instructions executable by a processor are stored. When the computer program instructions are called by the processor, the processor executes any one of the lithium battery dischargeable capacity estimation model acquisition methods proposed in the first aspect, or executes the lithium battery dischargeable capacity estimation method proposed in the second aspect.

[0033] Beneficial effects of the embodiments of the present invention: Different from the prior art, the method for obtaining a dischargeable capacity estimation model of a lithium battery provided by the embodiments of the present invention includes: testing the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test; based on the test data, fitting the model parameters of the dischargeable capacity estimation model to obtain the dischargeable capacity estimation model.

[0034] The method for obtaining a lithium battery dischargeable capacity estimation model provided by an embodiment of the present invention only requires a small amount of testing of the lithium battery under preset experimental conditions, and the dischargeable capacity estimation model is obtained by fitting the test data obtained from the test, which greatly reduces the test time and cost. The dischargeable capacity estimation model fully considers the influence of temperature and current on the estimated lithium battery capacity. When the dischargeable capacity estimation model is used to estimate the capacity of the lithium battery, the accurate lithium battery capacity can be obtained, thereby improving the accuracy of the lithium battery capacity estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following is a brief introduction to the drawings required for the description of the prior art or the embodiments. Obviously, the drawings described below only illustrate certain embodiments of the present invention and should not be regarded as limiting the scope of protection. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative work.

[0036] Figure 1 is a schematic diagram of an application scenario of a model for estimating the dischargeable capacity of a lithium battery in some embodiments of the present invention;

[0037] Figure 2 is a schematic diagram of the structure of an electronic device provided by some embodiments of the present invention;

[0038] Figure 3 It is a flow chart of a method for obtaining a lithium battery discharge capacity estimation model provided by some embodiments of the present invention;

[0039] Figure 4 is a fitting schematic diagram of a discharge capacity estimation model provided by some embodiments of the present invention;

[0040] Figure 5is a schematic flow chart of a method for estimating the dischargeable capacity of a lithium battery provided by some embodiments of the present invention;

[0041] Figure 6 It is a schematic diagram of effect verification of the lithium battery discharge capacity estimation model provided by some embodiments of the present invention;

[0042] Figure 7 is a schematic diagram of the structure of a device for obtaining a dischargeable capacity estimation model of a lithium battery provided in some embodiments of the present invention;

[0043] Figure 8 It is a schematic diagram of the structure of a lithium battery dischargeable capacity estimation device provided in some embodiments of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose and advantages of the embodiments of the present invention easier to understand, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The detailed description of the embodiments of the present invention in the drawings below does not limit the scope of protection claimed by the present invention, but only represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] It should be noted that, if no conflict is constituted, the various technical features involved in the embodiments of the present invention described below can be combined with each other, and are all within the scope of protection of the present invention. In addition, although the functional modules are divided in the device or structural schematic diagram, and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order than the module division in the device, or in a different order than in the flow chart. In addition, the "first", "second", "third" and other similar expressions used herein do not limit the data and execution order, but are only for the purpose of convenience of explanation and to distinguish between the same or similar items with basically the same functions and effects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features.

[0046] Unless otherwise defined, the technical terms and scientific terms used in this specification have the same meanings as those generally understood by those of ordinary skill in the art of the present invention. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. It should be understood that the term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0047] Rated capacity: refers to the maximum amount of charge that a battery can release under the standard test conditions specified by the manufacturer, usually expressed in ampere-hours (Ah). This is the theoretical capacity value of the battery in the best condition, measured at a specific discharge rate and ambient temperature.

[0048] Dischargeable capacity / current capacity: refers to the actual available capacity of the battery in its current state. This value will gradually decrease as the battery is used more and more times. Each charge and discharge cycle will cause a certain degree of loss to the battery. As time goes by, the internal resistance of the battery will increase and the efficiency will decrease. Therefore, the actual amount of power it can provide (i.e., discharge capacity / current capacity) will be less than its initial rated capacity. At the same time, the dischargeable capacity / current capacity will also change due to the influence of temperature, charge / discharge rate, storage time, etc.

[0049] The dischargeable capacity / current capacity of a lithium battery is indispensable in the estimation of the SOC of a lithium battery. The SOC of a lithium battery indicates to a certain extent the approximate remaining power and working time of the battery when the current working condition is maintained. For power lithium batteries, it can effectively help estimate the remaining mileage. In related technologies, a large number of experiments are usually conducted to obtain the dischargeable capacity under different working conditions, and then the table lookup method is directly used to obtain the real-time dischargeable capacity of the lithium battery during operation.

[0050] However, the table lookup method requires a large number of offline tests for different styles and models of lithium batteries, which consumes a lot of test time and cost, and is not conducive to the replacement of lithium batteries. In addition, the real-time discharge capacity of lithium batteries in different operating processes is easily affected by other environmental factors (such as temperature and current, etc.). The discharge capacity of lithium batteries obtained by the table lookup method may be inaccurate, resulting in a reduction in the accuracy of lithium battery SOC estimation.

[0051] In view of this, an object of an embodiment of the present invention is to provide a method for obtaining a dischargeable capacity estimation model of a lithium battery, by performing a small amount of tests on the lithium battery under preset experimental conditions to obtain relevant test data, the preset experimental conditions include temperature and current, and the test data includes the rated capacity and test capacity (i.e., dischargeable capacity / current capacity) of the lithium battery, etc. Then, the model parameters of the dischargeable capacity estimation model are fitted using the test data, thereby obtaining the dischargeable capacity estimation model.

[0052] Since only a small amount of testing of lithium batteries is required under preset experimental conditions, the test time and test cost can be greatly reduced, which is conducive to the replacement of lithium batteries. In addition, the dischargeable capacity estimation model fully considers the influence of temperature and current on the estimated lithium battery capacity. When the dischargeable capacity estimation model is used to estimate the capacity of lithium batteries, the accurate dischargeable capacity of lithium batteries can be obtained, thereby improving the accuracy of lithium battery SOC estimation.

[0053] See also Figure 1 , Figure 1 A schematic diagram of an application scenario for obtaining a lithium battery discharge capacity estimation model in some embodiments of the present invention is schematically shown.

[0054] like Figure 1 As shown, the application scenario includes a lithium battery dischargeable capacity estimation model acquisition system 1000, and the lithium battery dischargeable capacity estimation model acquisition system 1000 includes a lithium battery 100, a test device 200 and an electronic device 300. Among them, the electronic device 300 is connected to the test device 200 through network communication, and the network can be the Internet, an enterprise intranet, a local area network, a mobile communication network, and a combination thereof.

[0055] Specifically, preset experimental conditions (ie, set temperature and current) are set, the lithium battery 100 is placed in a constant temperature box adjusted to the set temperature, and the lithium battery 100 is connected to the test equipment 200 to measure the current of the lithium battery 100 through the test equipment 200.

[0056] During the test, the lithium battery 100 may be subjected to a charge test and / or a discharge test to obtain relevant test data, the test data including the rated capacity and the test capacity of the lithium battery 100. If the test is a charge test, the lithium battery 100 is connected to an external power source ( Figure 1 The test equipment 200 collects the charging current of the lithium battery 100, and after the charging test, the capacity of the lithium battery 100 (i.e., the test capacity and the rated capacity) is calculated using the ampere-hour integration method or other methods. If it is a discharge test, the lithium battery 100 is connected to an external load ( Figure 1 (not shown) is discharged from a fully charged state, and the discharge current of the lithium battery 100 is collected by the test equipment 200. After the discharge test is completed, the capacity of the lithium battery 100 (i.e., the test capacity and the rated capacity) is calculated using the ampere-hour integration method or other methods. It should be understood that for the same batch of lithium batteries, the rated capacity of the lithium battery 100 is constant, and the rated capacity obtained by the charging test and / or discharge test performed at different temperatures and different currents is the same. Therefore, after the rated capacity of the lithium battery is calculated under certain preset experimental conditions, the rated capacity of the lithium battery does not need to be calculated when performing subsequent tests under the preset experimental conditions, thereby saving calculations. Of course, the rated capacity of the lithium battery cell / lithium battery is generally also marked when it leaves the factory, so the rated capacity can also directly use the calibrated value.

[0057] After completing the test of a set of preset experimental conditions (i.e., a temperature and a current), the temperature of the thermostat is adjusted to the temperature corresponding to the next set of preset experimental conditions, and the current corresponding to the next set of preset experimental conditions of the lithium battery 100 is continuously tested until the test of all preset experimental conditions is completed, and the test data corresponding to all preset experimental conditions are obtained. After obtaining the test data, the test data is transmitted to the electronic device 300, and the electronic device 300 fits the model parameters of the dischargeable capacity estimation model of the lithium battery 100 based on the test data and in combination with the preset experimental conditions, thereby obtaining the dischargeable capacity estimation model.

[0058] In some embodiments, after obtaining the lithium battery dischargeable capacity estimation model, the dischargeable capacity estimation model is stored in the local storage of the electronic device 300. In the process of actually estimating the dischargeable capacity of the lithium battery, the electronic device 300 obtains the rated capacity, current temperature and current current of the lithium battery to be estimated through the temperature sensor, current detection circuit and other required components, devices or equipment set in the lithium battery, and then inputs the rated capacity, current temperature and current current of the lithium battery to be estimated into the lithium battery dischargeable capacity estimation model, and outputs the dischargeable capacity of the lithium battery to be estimated after the prediction and estimation of the dischargeable capacity estimation model.

[0059] In some embodiments, the test equipment 200 may be a lithium battery cell charge and discharge test cabinet commonly found on the market. The cell test cabinet is capable of monitoring the current of the battery / cell charge and discharge, has multiple channels, can test multiple cells of a lithium battery at the same time, and monitor the current of multiple cells during the test. The electronic device 300 may be a desktop computer, which has certain control and computing capabilities. After receiving the test data, it processes the test data and preset experimental conditions, and fits the model parameters of the dischargeable capacity estimation model of the lithium battery 100, thereby obtaining the dischargeable capacity estimation model.

[0060] It is easy to understand that in Figure 1 In the application scenario shown in the embodiment, the test device 200 and the electronic device 300 in the acquisition system 1000 of the lithium battery discharge capacity estimation model are respectively a test cabinet and a desktop computer, but it does not impose any restrictions on any situation such as the structure and type of the test device 200 and the electronic device 300 in other application scenarios. For example, in some other application scenarios, the electronic device 300 can also be a single-chip microcomputer, a tablet computer or other suitable types of devices. In addition, the electronic device 300 in some other application scenarios can also include Figure 1 The desktop computer shown may have more or fewer components, or may have Figure 1 Different configurations of desktop computers are shown.

[0061] In order to facilitate understanding of the lithium battery dischargeable capacity estimation model acquisition method and the lithium battery dischargeable capacity estimation method provided in the embodiment of the present invention, the electronic device 300 provided in the embodiment of the present invention is firstly introduced in detail.

[0062] See also Figure 2 , Figure 2 The structural diagram of the electronic device 300 provided in some embodiments of the present invention is schematically shown.

[0063] like Figure 2 As shown, the electronic device 300 includes at least one processor 310 and a memory 320 that are communicatively connected. Figure 2 In the figure, a processor is connected to the bus system 330 as an example. The components in the electronic device 300 are coupled together through the bus system 330, and the bus system 330 is used to realize the connection and communication between these components. It is easy to understand that the bus system 330 includes a power bus, a control bus, and a status signal bus in addition to a data bus. However, for the sake of clarity and brevity, Figure 2 In the figure, various buses are labeled as bus system 330. It can be understood that Figure 2 The structure shown in the embodiment is only for illustration and does not impose any limitation on the structure of the electronic device 300. For example, the electronic device 300 may also include Figure 2 More or fewer components as shown, or with Figure 2 Different configurations are shown.

[0064] Specifically, the processor 310 is used to provide computing and control capabilities to control the electronic device 300 to perform corresponding tasks. For example, the electronic device 300 is controlled to perform any of the lithium battery discharge capacity estimation model acquisition methods and lithium battery discharge capacity estimation methods provided in the embodiments of the present invention. Those skilled in the art can understand that the processor 310 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0065] The memory 320, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, instructions and modules, such as the programs, instructions and modules corresponding to the method for obtaining the dischargeable capacity estimation model of a lithium battery and the method for estimating the dischargeable capacity of a lithium battery in the embodiment of the present invention. In some embodiments, the memory 320 may include a program storage area and a data storage area, and the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the processor 310, etc. The processor 310 executes various functional applications and data processing of the electronic device 300 by running the non-transitory software programs, instructions and modules stored in the memory 320, so as to implement any of the methods for obtaining the dischargeable capacity estimation model of a lithium battery and the method for estimating the dischargeable capacity of a lithium battery provided in the embodiment of the present invention. Among them, the memory 320 may include a high-speed random access memory, and may also include a non-transitory memory. For example, at least one disk storage device, a flash memory device or other non-transitory solid-state storage device. In some embodiments, the memory 320 may also include a memory remotely arranged relative to the processor 310, and these remotely arranged memories may be connected to the processor 310 via a communication network. It can be understood that examples of the above-mentioned communication network include but are not limited to the Internet, corporate intranet, local area network, mobile communication network and combinations thereof.

[0066] It is easy to understand that the implementation subject of any of the methods for obtaining a lithium battery dischargeable capacity estimation model and the method for estimating a lithium battery dischargeable capacity provided by the embodiments of the present invention can be any suitable type of electronic device with certain computing and control capabilities. In some feasible implementations, any of the methods for obtaining a lithium battery dischargeable capacity estimation model and the method for estimating a lithium battery dischargeable capacity provided by the embodiments of the present invention can be implemented by a processor calling computer program instructions stored in a memory.

[0067] It can be understood from the above that the lithium battery dischargeable capacity estimation model acquisition method and the lithium battery dischargeable capacity estimation method provided in the embodiments of the present invention can be implemented by various suitable types of electronic devices with certain computing and control capabilities, for example, they can be implemented and executed by the above-mentioned electronic device 300. The following will be combined with the exemplary application and implementation of the electronic device provided by the embodiment of the present invention to describe in detail the lithium battery dischargeable capacity estimation model acquisition method and the lithium battery dischargeable capacity estimation method provided by the embodiment of the present invention.

[0068] See also Figure 3 , Figure 3 The flowchart of the method for obtaining the dischargeable capacity estimation model of a lithium battery provided by some embodiments of the present invention is schematically shown.

[0069] It should be understood that the lithium battery dischargeable capacity estimation model acquisition method provided in the embodiment of the present invention can be applied to the above electronic device (eg, electronic device 300). Specifically, the lithium battery dischargeable capacity estimation model acquisition method is executed by one or at least two processors of the electronic device.

[0070] like Figure 3 As shown, the method for obtaining the lithium battery discharge capacity estimation model includes but is not limited to the following steps S100-S200:

[0071] S100: Testing the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test.

[0072] Specifically, the lithium battery is tested under preset experimental conditions, which include temperature and current. The test process may include charging test, discharging test or a combination of the two. By testing the lithium battery, test data such as the test capacity and rated capacity of the lithium battery are collected.

[0073] In some embodiments, the test equipment is connected to the lithium battery, and the lithium battery is connected to an external power supply or an external load, and a charging test and / or a discharging test is performed on the lithium battery, and the current of the lithium battery is collected by the test equipment. After the charging test and / or the discharging test is completed, the capacity of the lithium battery (i.e., the test capacity and the rated capacity) is calculated using the ampere-hour integration method or other methods, thereby obtaining the test data of the lithium battery.

[0074] In some embodiments, the charging test or discharging test performed on the lithium battery may be a hybrid power pulse characterization test (HPPC).

[0075] HPPC testing is a comprehensive dynamic testing method that combines the features of pulse testing and step response testing. It includes a series of pulse charging and discharging of the battery at different states of charge (SOC) while also considering the battery's regeneration capacity, providing a more comprehensive view of battery performance.

[0076] In the HPPC test, the battery goes through the following steps: 1) charging to a full state; 2) discharging to a specific state of charge; 3) a period of rest to allow the battery to reach thermal equilibrium; 4) applying a series of current pulses, usually including smaller pulses and larger pulses, to simulate the transient working conditions of the battery in actual applications; 5) recording the voltage response curve during each pulse; 6) performing regenerative charging, that is, applying reverse pulses to evaluate the battery's energy recovery capability.

[0077] In some embodiments, the lithium battery is tested under preset experimental conditions, including but not limited to the following steps S110-S120:

[0078] S110: Testing the lithium battery at a current preset temperature with a plurality of constant preset currents corresponding to the current preset temperature.

[0079] S120: After the lithium battery test is completed at the current preset temperature with a number of constant preset currents corresponding to the current preset temperature, the lithium battery test continues at the next preset temperature with a number of constant preset currents corresponding to the next preset temperature until the lithium battery test is completed under all preset experimental conditions.

[0080] Specifically, in order to avoid frequent switching of experimental temperatures and improve experimental efficiency, several groups of preset experimental conditions are first screened according to the preset temperature to obtain one or more preset currents corresponding to one or more preset temperatures. For example, several groups of preset experimental conditions are [15°C, 0.5C], [15°C, 0.8C], [15°C, 1.0C], [15°C, 1.5C], [20°C, 0.8C] and [25°C, 1.0C]. It can be understood that "C" represents the charging or discharging rate of the battery. For example, if a 100Ah lithium battery is charged at 1C, the charging current is 100A.

[0081] After screening the preset temperatures, the preset temperature of 15°C corresponds to multiple preset currents, namely: 0.5C, 0.8C, 1.0C and 1.5C, the preset temperature of 20°C corresponds to a preset current of 0.8C, and the preset temperature of 25°C corresponds to a preset current of 1.0C.

[0082] For any current preset temperature (for example, 15°C), at the current preset temperature, the lithium battery is tested with several constant preset currents (i.e., 0.5C, 0.8C, 1.0C and 1.5C) corresponding to the current preset temperature, that is, at the current preset temperature, the lithium battery is subjected to constant current charging test and / or constant current discharging test with several preset currents corresponding to the current preset temperature.

[0083] After the lithium battery is tested at the current preset temperature (for example, 15°C) with several constant preset currents corresponding to the current preset temperature (i.e., 0.5C, 0.8C, 1.0C and 1.5C), the experimental temperature is adjusted to the next preset temperature (for example, 20°C), and the lithium battery is tested at the next preset temperature with several constant preset currents (i.e., 0.8C) corresponding to the next preset temperature, until the lithium battery is tested under all preset experimental conditions, the test data under each preset experimental condition is obtained, that is, the test capacity and rated capacity of the lithium battery under each preset experimental condition (temperature and current) are obtained.

[0084] It is understandable that for the same batch of lithium batteries, the rated capacity of the lithium battery is constant, and the rated capacity obtained from the charging test and / or discharging test at different temperatures and currents is the same. Therefore, after the rated capacity of the lithium battery is calculated under a certain preset experimental condition, the rated capacity of the lithium battery can be no longer calculated when performing subsequent tests under the preset experimental conditions, thereby reducing the amount of calculation. Of course, the rated capacity of lithium cells / lithium batteries is generally marked when they leave the factory, so the rated capacity can also be directly used as the calibrated value.

[0085] S200: fitting model parameters of a dischargeable capacity estimation model based on the test data to obtain a dischargeable capacity estimation model.

[0086] Specifically, after obtaining the test data of the lithium battery under each preset experimental condition, and combining the preset experimental conditions (i.e., temperature and current), a preliminary dischargeable capacity estimation model that can reflect the change in the dischargeable capacity of the lithium battery is constructed, and initial values ​​are set for the model parameters of the dischargeable capacity estimation model. In the embodiment of the present invention, the change in the dischargeable capacity of the lithium battery is closely related to factors such as temperature and current, showing an exponential or logarithmic relationship, so an exponential or logarithmic dischargeable capacity estimation model can be constructed.

[0087] Then, the test data is processed and analyzed, that is, the test data and the temperature and current corresponding to the preset experimental conditions corresponding to the test data are substituted into the dischargeable capacity estimation model, and the model parameters of the dischargeable capacity estimation model are fitted using an appropriate fitting algorithm (for example, least squares method, genetic algorithm and particle swarm optimization, etc.). After fitting the model parameters of the dischargeable capacity estimation model, the final dischargeable capacity estimation model is generated, that is, the dischargeable capacity estimation model of the lithium battery is obtained.

[0088] Exemplarily, in some embodiments, based on the test data, model parameters of the dischargeable capacity estimation model are fitted, specifically including but not limited to the following steps S210:

[0089] S210: Substitute the rated capacity of the lithium battery, various temperatures and various currents, and the test capacity corresponding to the temperature and current into the dischargeable capacity estimation model, and use a nonlinear fitting algorithm to perform parameter fitting on the dischargeable capacity estimation model to obtain model parameters of the dischargeable capacity estimation model.

[0090] Specifically, a suitable dischargeable capacity estimation model is determined to describe the change in the dischargeable capacity of the lithium battery. For example, in some embodiments, a nonlinear dischargeable capacity estimation model is used, which may be an exponential model. The exponential model is suitable for a scenario in which the dischargeable capacity of the lithium battery changes exponentially with factors such as current and temperature. For example, the formula of the nonlinear dischargeable capacity estimation exponential model may be:

[0091]

[0092] in, is the discharge capacity of the lithium battery, is the rated capacity of the lithium battery, is the temperature of the lithium battery, is the current of the lithium battery, , and Model parameters to be fitted for the discharge capacity estimation model.

[0093] In some embodiments, the nonlinear dischargeable capacity estimation model may be a polynomial model. The polynomial model is applicable to the case where the dischargeable capacity of the lithium battery presents a relatively complex change with factors such as current and temperature. For example, the formula of the nonlinear dischargeable capacity estimation polynomial model may be:

[0094]

[0095] in, is the discharge capacity of the lithium battery, is the rated capacity of the lithium battery, is the temperature of the lithium battery, is the current of the lithium battery, , , , , and Model parameters to be fitted for the discharge capacity estimation model.

[0096] In the embodiment of the present invention, the formula of the discharge capacity estimation model is:

[0097]

[0098]

[0099] in, , , , , and are the model parameters of the discharge capacity estimation model, and They are the test capacity and rated capacity of lithium batteries respectively. and are the current and temperature of the lithium battery respectively.

[0100] Of course, the nonlinear dischargeable capacity estimation model may also be any other suitable model, and the initial values ​​of the model parameters may be set according to the determined nonlinear dischargeable capacity estimation model, so as to fit the final model parameters according to the test data.

[0101] After determining the lithium battery dischargeable capacity estimation model, the rated capacity of the lithium battery, each preset experimental condition (i.e., temperature and current), and the test capacity of the lithium battery under each preset experimental condition (i.e., the dischargeable capacity of the lithium battery actually measured under different temperature and current conditions) are substituted into the dischargeable capacity estimation model, and the model parameters of the dischargeable capacity estimation model are iteratively fitted using a commonly used nonlinear fitting algorithm (e.g., Levenberg-Marquardt algorithm or gradient descent method, etc.), and the model parameters are continuously adjusted so that the difference between the actual test capacity and the predicted capacity of the dischargeable capacity estimation model is gradually reduced. In each iterative fitting, the nonlinear fitting algorithm calculates the capacity error between the dischargeable capacity predicted by the dischargeable capacity estimation model and the actual test capacity, and updates the model parameters until the capacity error converges to an acceptable range. In this case, the model parameters of the dischargeable capacity estimation model are considered to be fitted, and the dischargeable capacity estimation model is obtained.

[0102] For the discharge capacity estimation model of the embodiment of the present invention, that is:

[0103]

[0104]

[0105] When fitting the model parameters of the discharge capacity estimation model, the model parameters , , , , and The initial values ​​of are set to [-0.17, 0, 13, 13, 1.07, 6] respectively. Then, based on the initial values ​​of each model parameter, the test data (i.e., rated capacity and test capacity) and temperature and current are substituted into the dischargeable capacity estimation model, and the model parameters of the dischargeable capacity estimation model are iteratively fitted to obtain the dischargeable capacity estimation model.

[0106] See also Figure 4 , Figure 4 The figure shows a schematic diagram of the fitting of the dischargeable capacity estimation model provided by some embodiments of the present invention. The colored surface is the effect schematic surface of the dischargeable capacity estimation model, and the blue points represent the data points obtained by testing the lithium battery under certain preset experimental conditions. The coordinates of the data points include temperature, discharge rate (a form of current) and relative discharge capacity. The relative discharge capacity is the ratio of the dischargeable capacity to the rated capacity, and 1 represents the rated capacity.

[0107] Depend on Figure 4 It can be seen that the embodiment of the present invention only needs to perform a small amount of testing on the lithium battery under the preset experimental conditions to obtain test data such as the rated capacity and the test capacity. Based on the test data, and in combination with the temperature and current corresponding to the preset experimental conditions, the dischargeable capacity estimation model is parameter-fitted, and finally the dischargeable capacity estimation model is obtained, which can greatly reduce the test time and test cost, and is conducive to the replacement of lithium batteries.

[0108] In some embodiments, the nonlinear fitting algorithm may adopt any one of an iterative least squares algorithm, a recursive least squares algorithm, a recursive augmented least squares algorithm, and a recursive least squares algorithm with a forgetting factor.

[0109] In some embodiments, the rated capacity, various temperatures and various currents of the lithium battery, and the test capacity corresponding to the temperature and current are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain model parameters of the dischargeable capacity estimation model, specifically including but not limited to the following steps S1-S4:

[0110] S1: Substitute the rated capacity, temperature, current and current model parameters of the lithium battery into the dischargeable capacity estimation model to obtain the estimated capacity.

[0111] For each iteration of fitting model parameters, the rated capacity of the lithium battery, the temperature and current corresponding to each preset experimental condition, and the current model parameters of the dischargeable capacity estimation model are substituted into the dischargeable capacity estimation model to obtain several estimated capacities of the lithium battery (i.e., the estimated capacity of the lithium battery under each preset experimental condition).

[0112] S2: Obtain a capacity estimation error based on the estimated capacity and the test capacity corresponding to the temperature and current.

[0113] Specifically, the capacity estimation error is obtained according to several estimated capacities of the lithium battery (ie, the estimated capacity of the lithium battery under various preset experimental conditions) and the test capacity corresponding to the temperature and current (ie, the test capacity of the lithium battery under various preset experimental conditions).

[0114] In some feasible implementations, several estimated capacities of the lithium battery may be summed to obtain a first sum value. The test capacities of the lithium battery under various preset experimental conditions may be summed to obtain a second sum value. The first sum value is divided by the second sum value to obtain a ratio, and the ratio is used as the capacity estimation error.

[0115] In some embodiments, the capacity estimation error may be obtained as follows:

[0116] A plurality of estimated capacities of the lithium battery and the test capacities corresponding to the estimated capacities (ie, the test capacities of the lithium battery under various preset experimental conditions) are substituted into the first formula to obtain a first estimation error.

[0117] The first formula is:

[0118]

[0119] in, is the first estimation error, For the The test capacity corresponding to the preset experimental conditions is For the The estimated capacity corresponding to the preset experimental conditions, The quantity for estimating capacity or testing capacity.

[0120] The estimated capacities of the lithium battery are averaged to obtain an estimated capacity average value, and then the estimated capacities of the lithium battery and the estimated capacity average value are substituted into the second formula to obtain a second estimation error.

[0121] The second formula is:

[0122]

[0123] in, is the second estimation error, For the The test capacity corresponding to the preset experimental conditions is To estimate the average capacity, The quantity for estimating capacity or testing capacity.

[0124] Then, the ratio of the first estimation error to the second estimation error is subtracted from the preset error reference value to obtain the capacity estimation error. The preset error reference value is 1.

[0125] S3: Update the current model parameters based on the capacity estimation error.

[0126] S4: Repeat the above steps S1 to S3 until the capacity estimation error is less than or equal to the first threshold value, the dischargeable capacity estimation model converges, and the model parameters of the dischargeable capacity estimation model are obtained.

[0127] Specifically, after obtaining the capacity estimation error, it is compared with a preset first threshold to determine whether the model parameters of the dischargeable capacity estimation model are fitted. In some embodiments, if the capacity estimation error is greater than the first threshold, it is considered that the dischargeable capacity estimation model has not reached convergence, and the model parameters of the dischargeable capacity estimation model have not been fitted, and the model parameters of the dischargeable capacity estimation model are continued to be adjusted and fitted using a nonlinear fitting algorithm. Repeat the above steps S1 to S3 until the capacity estimation error is less than or equal to the first threshold, then it is considered that the dischargeable capacity estimation model has converged, that is, the model parameters of the dischargeable capacity estimation model have been fitted.

[0128] It should be understood that those skilled in the art may determine the first threshold value according to actual fitting requirements and test data settings, and the embodiments of the present invention do not impose any limitation on this.

[0129] In summary, the method for obtaining a dischargeable capacity estimation model for a lithium battery provided in an embodiment of the present invention includes: testing a lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test; based on the test data, fitting model parameters of the dischargeable capacity estimation model to obtain the dischargeable capacity estimation model.

[0130] The method for obtaining a lithium battery dischargeable capacity estimation model provided in an embodiment of the present invention only requires a small amount of testing of the lithium battery under preset experimental conditions, and the dischargeable capacity estimation model is obtained by fitting the test data obtained from the test, thereby greatly reducing the test time and test cost.

[0131] See also Figure 5 , Figure 5 The flowchart of the method for estimating the dischargeable capacity of a lithium battery provided by some embodiments of the present invention is schematically shown.

[0132] It should be understood that the method for estimating the dischargeable capacity of a lithium battery provided in the embodiment of the present invention can be applied to the above electronic device (eg, the electronic device 300). Specifically, the method for estimating the dischargeable capacity of a lithium battery is executed by one or at least two processors of the electronic device.

[0133] like Figure 5 As shown, the method for estimating the dischargeable capacity of a lithium battery includes but is not limited to the following steps S10-S20:

[0134] S10: Acquire status data of the lithium battery to be estimated, wherein the status data includes the rated capacity, current temperature and current current of the lithium battery to be estimated.

[0135] S20: based on the state data, using a dischargeable capacity estimation model, estimating the dischargeable capacity of the lithium battery to be estimated, wherein the dischargeable capacity estimation model is obtained by using any of the lithium battery dischargeable capacity estimation model acquisition methods provided in the embodiments of the present invention.

[0136] Specifically, when actually estimating the dischargeable capacity of a lithium battery, the electronic device obtains the rated capacity, current temperature and current current of the lithium battery to be estimated through a temperature sensor, current detection circuit and other required components, devices or equipment provided on the lithium battery, that is, obtains the status data of the lithium battery to be estimated through necessary auxiliary components, devices or equipment. It should be understood that the status data includes the rated capacity, current temperature and current current of the lithium battery.

[0137] Then, the rated capacity, current temperature and current current of the lithium battery to be estimated are input into the lithium battery dischargeable capacity estimation model provided in the embodiment of the present invention, and the dischargeable capacity of the lithium battery to be estimated is output after prediction and estimation by the dischargeable capacity estimation model. The lithium battery dischargeable capacity estimation model of this embodiment is obtained by adopting the lithium battery dischargeable capacity estimation model acquisition method provided in the above embodiment of the present invention.

[0138] The method for obtaining the lithium battery dischargeable capacity estimation model provided by the above-mentioned embodiment of the present invention is to test the lithium battery under preset experimental conditions (i.e., temperature and current) to obtain test data, and to obtain the dischargeable capacity estimation model based on the test data obtained by the test and in combination with the preset experimental conditions. The dischargeable capacity estimation model fully considers the influence of temperature and current on the estimated lithium battery capacity. When the dischargeable capacity estimation model is used to estimate the capacity of the lithium battery, the accurate lithium battery capacity can be obtained, thereby improving the accuracy of the lithium battery capacity estimation.

[0139] In summary, the method for estimating the dischargeable capacity of a lithium battery provided in an embodiment of the present invention includes: obtaining status data of a lithium battery to be estimated, wherein the status data includes the rated capacity, current temperature and current current of the lithium battery to be estimated; based on the status data, estimating the dischargeable capacity of the lithium battery to be estimated by using a dischargeable capacity estimation model, wherein the dischargeable capacity estimation model is obtained by using any of the methods for obtaining a dischargeable capacity estimation model of a lithium battery provided in an embodiment of the present invention.

[0140] The method for estimating the dischargeable capacity of a lithium battery provided in an embodiment of the present invention, after obtaining the state data of the lithium battery to be estimated, uses the dischargeable capacity estimation model provided in an embodiment of the present invention to estimate the dischargeable capacity of the lithium battery to be estimated. Since the dischargeable capacity estimation model fully considers the influence of temperature and current on the estimated lithium battery capacity, when the capacity of the lithium battery is estimated using the dischargeable capacity estimation model, an accurate lithium battery capacity can be obtained, thereby improving the accuracy of the lithium battery capacity estimation.

[0141] Verify the above discharge capacity estimation model. Figure 6 , Figure 6 The schematic diagram schematically shows the effect verification of the discharge capacity estimation model provided by some embodiments of the present invention.

[0142] The verification process is as follows:

[0143] 1) Cool down the fully charged battery to = -10℃, and place it in an environment with an ambient temperature of Ten = 25℃;

[0144] 2) With current = 0.5C constant current discharge until the battery is completely discharged, that is, discharge from SOC100% to 0%;

[0145] 3) Real-time recording of battery temperature during discharge , , ,……, Final battery temperature = 20℃, the actual total discharge is 0.92 ,in is the rated capacity.

[0146] According to the temperature of each battery recorded during the verification process as above , , , ,……, and current =0.5C, substitute it into the following discharge capacity estimation model, and calculate the discharge capacity corresponding to each battery temperature moment , , , ,……, .

[0147]

[0148]

[0149] The estimated discharge capacity is as follows: Figure 6 The curve shown in (d).

[0150] The total estimated dischargeable capacity is equal to the average value of all real-time estimated dischargeable capacities, which is calculated to be 0.92Cap. This estimated value is equal to the actual value of the experimental test, proving that the above dischargeable capacity estimation model can accurately estimate the dischargeable capacity of the lithium battery to be estimated.

[0151] See also Figure 7 , Figure 7 The schematic diagram of the structure of the lithium battery dischargeable capacity estimation model acquisition device 400 provided in some embodiments of the present invention is schematically shown. It is easy to understand that the lithium battery dischargeable capacity estimation model acquisition device 400 can be configured in an electronic device, or the lithium battery dischargeable capacity estimation model acquisition device 400 can also exist independently of the electronic device.

[0152] like Figure 7 As shown, the lithium battery dischargeable capacity estimation model acquisition device 400 includes:

[0153] A test module 410 is used to test the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charge test and / or a discharge test;

[0154] The fitting module 420 is used to fit the model parameters of the dischargeable capacity estimation model based on the test data to obtain the dischargeable capacity estimation model.

[0155] In some embodiments, the test data includes the test capacity and the rated capacity of the lithium battery, and the fitting module 420 is specifically used for:

[0156] The rated capacity of the lithium battery, various temperatures and various currents, and the test capacity corresponding to the temperature and current are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain model parameters of the dischargeable capacity estimation model.

[0157] In some embodiments, the model parameters have initial values, and the fitting module 420 is further configured to:

[0158] Substitute the rated capacity, temperature, current and current model parameters of the lithium battery into the dischargeable capacity estimation model to obtain the estimated capacity;

[0159] Based on the estimated capacity and the test capacity corresponding to the temperature and current, the capacity estimation error is obtained;

[0160] Update current model parameters based on capacity estimation errors;

[0161] The above steps are repeatedly performed until the capacity estimation error is less than or equal to the first threshold value, the dischargeable capacity estimation model converges, and the model parameters of the dischargeable capacity estimation model are obtained.

[0162] In some embodiments, the testing module 410 is specifically used to:

[0163] At the current preset temperature, the lithium battery is tested with a number of constant preset currents corresponding to the current preset temperature;

[0164] After the lithium battery test is completed at the current preset temperature with several constant preset currents corresponding to the current preset temperature, the lithium battery is continued to be tested at the next preset temperature with several constant preset currents corresponding to the next preset temperature until the lithium battery test is completed under all preset experimental conditions.

[0165] In some embodiments, the discharge capacity estimation model is formulated as follows:

[0166]

[0167]

[0168] in, , , , , and are the model parameters of the discharge capacity estimation model, and They are the test capacity and rated capacity of lithium batteries respectively. and are the current and temperature of the lithium battery respectively.

[0169] In some embodiments, the test is a hybrid power pulse characteristic test.

[0170] In some embodiments, the nonlinear fitting algorithm is any one of an iterative least squares algorithm, a recursive least squares algorithm, a recursive augmented least squares algorithm, and a recursive least squares algorithm with a forgetting factor.

[0171] It is worth noting that, for the sake of simplicity and brevity of description, the above-mentioned lithium battery dischargeable capacity estimation model acquisition device 400 can execute the functional modules and beneficial effects corresponding to the lithium battery dischargeable capacity estimation model acquisition method provided in the embodiment of the present invention. For technical details not fully described in the embodiment of the lithium battery dischargeable capacity estimation model acquisition device 400, reference can be made to the lithium battery dischargeable capacity estimation model acquisition method provided in the embodiment of the present invention. The specific working process of the above-mentioned lithium battery dischargeable capacity estimation model acquisition device 400 can also refer to the specific execution process corresponding to the lithium battery dischargeable capacity estimation model acquisition method provided in the aforementioned embodiment of the present invention, and will not be described one by one here.

[0172] See also Figure 8 , Figure 8 The schematic diagram of the structure of the lithium battery dischargeable capacity estimation device 500 provided by some embodiments of the present invention is shown. It is easy to understand that the lithium battery dischargeable capacity estimation device 500 can be configured in an electronic device, or the lithium battery dischargeable capacity estimation device 500 can also exist independently of the electronic device.

[0173] like Figure 8 As shown, the lithium battery dischargeable capacity estimation device 500 includes:

[0174] An acquisition module 510 is used to acquire status data of the lithium battery to be estimated, wherein the status data includes the rated capacity, current temperature and current current of the lithium battery to be estimated;

[0175] The estimation module 520 is used to estimate the dischargeable capacity of the lithium battery to be estimated based on the state data using a dischargeable capacity estimation model, wherein the dischargeable capacity estimation model is obtained using any of the lithium battery dischargeable capacity estimation model acquisition methods provided in the embodiments of the present invention.

[0176] It is worth noting that, for the sake of simplicity and brevity of description, the above-mentioned lithium battery dischargeable capacity estimation device 500 can execute the corresponding functional modules and beneficial effects of the lithium battery dischargeable capacity estimation method provided in the embodiment of the present invention. For technical details not fully described in the embodiment of the lithium battery dischargeable capacity estimation device 500, reference can be made to the lithium battery dischargeable capacity estimation method provided in the embodiment of the present invention. The specific working process of the above-mentioned lithium battery dischargeable capacity estimation device 500 can also refer to the specific execution process corresponding to the lithium battery dischargeable capacity estimation method provided in the above-mentioned embodiment of the present invention, and will not be described one by one here.

[0177] The lithium battery dischargeable capacity estimation model acquisition device 400 and the lithium battery dischargeable capacity estimation device 500 provided in the embodiments of the present invention can be software modules, and the software modules include a number of instructions stored in a memory. The processor can access the memory and call the instructions for execution to complete the lithium battery dischargeable capacity estimation model acquisition method and the lithium battery dischargeable capacity estimation method described in the above-mentioned embodiments.

[0178] In some embodiments, the lithium battery dischargeable capacity estimation model acquisition device 400 and the lithium battery dischargeable capacity estimation device 500 can also be constructed by hardware devices. For example, the lithium battery dischargeable capacity estimation model acquisition device 400 and the lithium battery dischargeable capacity estimation device 500 can be constructed by one or more chips, and each chip can work in coordination with each other to implement the lithium battery dischargeable capacity estimation model acquisition method and the lithium battery dischargeable capacity estimation method described in the above embodiments. In some embodiments, the lithium battery dischargeable capacity estimation model acquisition device 400 and the lithium battery dischargeable capacity estimation device 500 can also be constructed by various logic devices, such as: general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), single-chip microcomputers, field programmable gate arrays (FPGAs), ARM (Acorn RISC Machines) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or any combination of these devices or components.

[0179] An embodiment of the present invention provides a computer-readable storage medium, on which computer program instructions executable by a processor are stored. When the computer program instructions are called by the processor, the processor executes any one of the lithium battery dischargeable capacity estimation model acquisition methods and lithium battery dischargeable capacity estimation methods provided in the embodiments of the present invention.

[0180] In some embodiments, the storage medium may be a flash memory, a hard disk, an optical disk, a register, a magnetic surface storage, a removable disk, a CD-ROM, a random access memory (RAM), a read-only memory (ROM), an electrically programmable ROM, and an electrically erasable programmable ROM, or any other form of storage medium known in the technical field, or may be various devices including one or any combination of the above storage media.

[0181] In some embodiments, computer program instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0182] As an example, computer program instructions may, but need not, correspond to a file in a file system, may be stored as part of a file storing other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0183] As an example, the computer program instructions may be deployed to be executed on a computing device (including devices such as smart terminals and servers), or on multiple computing devices located at one location, or on multiple computing devices distributed at multiple locations and interconnected by a communication network. It is easy to understand that all or part of the steps of the method described in the embodiments provided by the present invention above can be directly implemented using electronic hardware or processor executable computer program instructions, or a combination of the two.

[0184] Those skilled in the art will appreciate that the embodiments provided by the present invention are only illustrative, and the order of writing the steps in the method of the embodiment does not mean a strict execution order and does not constitute any limitation on the implementation process. The order can be adjusted, merged and deleted according to actual needs, and the modules or sub-modules, units or sub-units in the device or system of the embodiment can be merged, divided and deleted according to actual needs. For example, the division of units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0185] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course can also be implemented by hardware. Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0186] It should be noted that the above embodiments are intended to illustrate the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the content of the present invention and implement it accordingly, and cannot be used to limit the scope of protection of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiments can be implemented according to the technical solutions recorded in the embodiments of the present invention, or some of the technical features can be equivalently replaced. It can be understood that these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and should be regarded as equal changes and modifications based on the embodiments of the present invention, and should all fall within the scope of the claims of the present invention.

Claims

1. A method for obtaining a lithium battery discharge capacity estimation model, characterized in that: The method comprises: Testing the lithium battery under preset experimental conditions to obtain test data, wherein the preset experimental conditions include temperature and current, and the test includes a charging test and / or a discharging test; Based on the test data, model parameters of the dischargeable capacity estimation model are fitted to obtain the dischargeable capacity estimation model. The formula of the dischargeable capacity estimation model is: in, , , , , and are model parameters of the dischargeable capacity estimation model, and are the test capacity and rated capacity of the lithium battery respectively, and are the current and temperature of the lithium battery respectively.

2. The method according to claim 1, characterized in that The test data includes: the test capacity and the rated capacity of the lithium battery. The model parameters of the dischargeable capacity estimation model are fitted based on the test data, including: The rated capacity of the lithium battery, various temperatures and various currents, and the test capacity corresponding to the temperature and current are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain model parameters of the dischargeable capacity estimation model.

3. The method according to claim 2, characterized in that The model parameters have initial values, and the rated capacity, various temperatures, various currents, and test capacities corresponding to the temperatures and currents of the lithium battery are substituted into the dischargeable capacity estimation model, and the dischargeable capacity estimation model is parameter-fitted using a nonlinear fitting algorithm to obtain the model parameters of the dischargeable capacity estimation model, including the following steps: S1: Substituting the rated capacity, temperature, current and current model parameters of the lithium battery into the dischargeable capacity estimation model to obtain an estimated capacity; S2: Obtaining a capacity estimation error based on the estimated capacity and the test capacity corresponding to the temperature and current; S3: updating the current model parameters based on the capacity estimation error; S4: Repeat the above steps S1 to S3 until the capacity estimation error is less than or equal to the first threshold value, the dischargeable capacity estimation model converges, and the model parameters of the dischargeable capacity estimation model are obtained.

4. The method according to claim 2, characterized in that: The testing of the lithium battery under preset experimental conditions includes: At a current preset temperature, testing the lithium battery with a plurality of constant preset currents corresponding to the current preset temperature; After the lithium battery test is completed at the current preset temperature with several constant preset currents corresponding to the current preset temperature, the lithium battery is continued to be tested at the next preset temperature with several constant preset currents corresponding to the next preset temperature until the lithium battery test is completed under all preset experimental conditions.

5. The method according to any one of claims 1 to 4, characterized in that The test is a hybrid power pulse characteristic test.

6. The method according to any one of claims 2 to 4, characterized in that: The nonlinear fitting algorithm is any one of an iterative least squares algorithm, a recursive least squares algorithm, a recursive augmented least squares algorithm and a recursive least squares algorithm with a forgetting factor.

7. A method for estimating the dischargeable capacity of a lithium battery, characterized in that: The method comprises: Acquire status data of the lithium battery to be estimated, wherein the status data includes the rated capacity, current temperature and current current of the lithium battery to be estimated; Based on the state data, using a dischargeable capacity estimation model, estimating the dischargeable capacity of the lithium battery to be estimated; Wherein, the dischargeable capacity estimation model is obtained by using the lithium battery dischargeable capacity estimation model acquisition method as described in any one of claims 1-6.

8. An electronic device, characterized in that: include: A processor and a memory communicatively connected to the processor; The memory stores computer program instructions executable by the processor, and when the computer program instructions are called by the processor, the processor executes the method for obtaining a lithium battery dischargeable capacity estimation model as described in any one of claims 1 to 6, or executes the method for estimating the dischargeable capacity of a lithium battery as described in claim 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions executable by a processor. When the computer program instructions are called by the processor, the processor executes the method for obtaining a lithium battery dischargeable capacity estimation model as described in any one of claims 1 to 6, or executes the method for estimating the dischargeable capacity of a lithium battery as described in claim 7.

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