Lithium battery health state estimation method and device, electronic equipment and storage medium

Abstract

The invention relates to a lithium battery health state estimation method and device, electronic equipment and a storage medium, and the lithium battery health state estimation method comprises the steps: estimating the battery temperature of a lithium battery according to the first imaginary part impedance of the lithium battery at a first target frequency and a first mapping relation between the imaginary part impedance and the battery temperature; and determining a second target frequency for accurately measuring the health state of the battery according to the current battery temperature of the lithium battery, so that the health state of the lithium battery can be estimated according to the second imaginary part impedance measured at the second target frequency and a preset second mapping relation between the imaginary part impedance and the health state. The imaginary part impedance is less influenced by a peripheral circuit, and the second mapping relation between the imaginary part impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, so that the influence of temperature change on the imaginary part impedance is eliminated, and the joint estimation of the battery temperature and the battery health state is accurately realized.

Description

Technical Field

[0001] The present application relates to the field of lithium battery technology, and in particular to a lithium battery health status estimation method, device, electronic device and storage medium. Background Art

[0002] With the continuous development of new energy technologies, lithium batteries are widely used in new energy vehicles, large-scale energy storage systems, aerospace and many other fields. However, during the use of lithium batteries, battery aging is inevitable, resulting in battery capacity decay and reduced battery life, thus affecting the use of equipment. Battery aging will not only cause battery capacity decay, but also affect the battery's charge and discharge performance and self-discharge rate, leading to increased internal battery temperature and gas generation, which can easily lead to safety hazards. The battery state of health (SOH) is defined as the ratio of the current available capacity of the battery to the initial rated capacity, and is usually used as an indicator to evaluate the battery aging level. Therefore, how to accurately estimate the health status of lithium-ion batteries has become an urgent problem to be solved. Summary of the invention

[0003] The present application provides a lithium battery health state estimation method, device, electronic device and storage medium to solve the technical problem of how to accurately estimate the health state of a lithium-ion battery.

[0004] In a first aspect, the present application provides a method for estimating the health status of a lithium battery, the method comprising:

[0005] Measuring a first imaginary impedance of the lithium battery at a first target frequency;

[0006] estimating the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature;

[0007] determining a second target frequency for measuring a health state according to the battery temperature;

[0008] measuring a second imaginary impedance of the lithium battery at the second target frequency;

[0009] The health state of the lithium battery is estimated according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

[0010] Optionally, before estimating the battery temperature of the lithium battery according to the preset first mapping relationship and the first imaginary impedance, the method further includes:

[0011] Acquire the first mapping relationship and the second mapping relationship;

[0012] The generation process of the first mapping relationship and the second mapping relationship includes:

[0013] When the lithium battery is offline, the lithium battery is charged and discharged cyclically;

[0014] During the cyclic charge and discharge process, the maximum available capacity corresponding to each cycle number is recorded, and the battery impedance spectrum at different temperatures is measured at each cycle number; wherein the maximum available capacity is used to calculate the health status of the lithium battery at the current cycle number;

[0015] According to the battery impedance spectra of the same number of cycles at different temperatures, fitting a first mapping relationship between the imaginary impedance and the battery temperature in a first frequency interval; wherein the first target frequency is within the first frequency interval;

[0016] According to the battery impedance spectra of the same target temperature with different cycle numbers, a third mapping relationship between the imaginary impedance and the health state in the second frequency interval at the target temperature is obtained; wherein the second target frequency is within the range of the second frequency interval;

[0017] According to the third mapping relationship at all different target temperatures within the target temperature range, a second mapping relationship between the imaginary impedance and the health state is determined.

[0018] Optionally, after obtaining a third mapping relationship between the imaginary impedance in the second frequency interval and the health state at the target temperature according to the battery impedance spectra at the same target temperature and different cycle numbers, the method further includes:

[0019] Determine a characteristic frequency at each target temperature from the second frequency interval; wherein, at the characteristic frequency, the difference in imaginary impedance between different cycle times at the same target temperature is greater than a preset threshold;

[0020] A fourth mapping relationship is obtained according to the characteristic frequencies corresponding to the respective target temperatures and the respective target temperatures.

[0021] Optionally, determining a second target frequency for measuring the health state according to the battery temperature includes:

[0022] determining a target characteristic frequency according to the battery temperature and the fourth mapping relationship;

[0023] The target characteristic frequency is used as the second target frequency for measuring the health state at the battery temperature.

[0024] Optionally, according to the battery impedance spectra of the same target temperature with different cycle numbers, a third mapping relationship between the imaginary impedance in the second frequency interval at the target temperature and the health state is obtained, including:

[0025] According to the battery impedance spectra of the same target temperature with different cycle numbers, a first functional relationship between the imaginary impedance and the cycle number in the second frequency range at the target temperature and a second functional relationship between the cycle number and the health state in the second frequency range at the target temperature are obtained;

[0026] The third mapping relationship is determined according to the first functional relationship and the second functional relationship.

[0027] Optionally, during the cyclic charge and discharge process, the maximum available capacity corresponding to each cycle number is recorded, and the battery impedance spectrum at different temperatures is measured at each cycle number, including:

[0028] During the cyclic charge and discharge process, recording the current maximum available capacity of the lithium battery after every ten cycles; and

[0029] After every ten cycles and when the battery is discharged to a state of charge of 50%, the lithium battery is placed in a thermostat to measure the battery impedance spectrum of the lithium battery at different temperatures set by the thermostat.

[0030] Optionally, the second frequency interval includes 0.2 Hz-1 kHz.

[0031] In a second aspect, the present application provides a lithium battery health status estimation device, the device comprising:

[0032] A first measuring module, used to measure a first imaginary impedance of the lithium battery at a first target frequency;

[0033] A first estimation module, used for estimating the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature;

[0034] a determination module, configured to determine a second target frequency for measuring a health state according to the battery temperature;

[0035] A second measuring module, used to measure a second imaginary impedance of the lithium battery at the second target frequency;

[0036] The second estimation module is used to estimate the health state of the lithium battery according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

[0037] In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0038] Memory, used to store computer programs;

[0039] The processor is used to implement the lithium battery health status estimation method described in any embodiment of the first aspect when executing the program stored in the memory.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for estimating the health status of a lithium battery as described in any embodiment of the first aspect is implemented.

[0041] The above-mentioned technical scheme provided by the embodiment of the present application has the following advantages compared with the prior art: the method provided by the embodiment of the present application measures the first imaginary impedance of the lithium battery at the first target frequency; estimates the battery temperature of the lithium battery according to the preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is the mapping relationship between the imaginary impedance and the battery temperature; determines the second target frequency for measuring the health state according to the battery temperature; measures the second imaginary impedance of the lithium battery at the second target frequency; estimates the health state of the lithium battery according to the preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is the mapping relationship between the imaginary impedance and the health state. The method can estimate the battery temperature of the lithium battery according to the first imaginary impedance of the lithium battery at the first target frequency and the first mapping relationship between the imaginary impedance and the battery temperature, and then determine the second target frequency for accurately measuring the battery health state according to the current battery temperature of the lithium battery, so that the health state of the lithium battery can be estimated according to the second imaginary impedance measured at the second target frequency and the preset second mapping relationship between the imaginary impedance and the health state. Since the imaginary impedance is less affected by the peripheral circuit, and the second mapping relationship between the imaginary impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, the influence of temperature change on the imaginary impedance is eliminated, thereby accurately realizing the joint estimation of the battery temperature and the battery health state. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0045] Figure 1 A system architecture diagram of a lithium battery health status estimation method provided in one embodiment of the present application;

[0046] Figure 2 A schematic diagram of a flow chart of a lithium battery health status estimation method provided in one embodiment of the present application;

[0047] Figure 3 A schematic diagram of the imaginary impedance of a battery at different SOCs at 45°C provided by an embodiment of the present application;

[0048] Figure 4 A schematic diagram showing the relationship between the imaginary impedance and the number of cycles when the SOC is 50% provided in one embodiment of the present application;

[0049] Figure 5 A schematic diagram of selecting time-frequency points at different temperatures provided by an embodiment of the present application;

[0050] Figure 6 A schematic diagram of frequency point selection at 0°C provided in one embodiment of the present application;

[0051] Figure 7 A schematic diagram of a method for jointly estimating temperature and SOH based on imaginary impedance provided by an embodiment of the present application;

[0052] Figure 8 A schematic diagram of the relationship between the number of cycles, imaginary impedance and frequency at 30°C provided in one embodiment of the present application;

[0053] Fig. 9 A schematic diagram of the relationship between the imaginary impedance of a battery and the number of cycles provided in one embodiment of the present application;

[0054] Fig.10 A schematic diagram of the relationship between a battery health status and a number of cycles provided in one embodiment of the present application;

[0055] Fig.11 A schematic diagram of the relationship between the number of cycles and the imaginary impedance at 30°C provided in one embodiment of the present application;

[0056] Fig.12 A schematic diagram of the structure of a lithium battery health status estimation device provided by one embodiment of the present application;

[0057] Fig.13A schematic diagram of the structure of an electronic device provided in accordance with an embodiment of the present application. DETAILED DESCRIPTION

[0058] 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, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0059] The disclosure below provides many different embodiments or examples to realize the different structures of the present application. In order to simplify the disclosure of the present application, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present application. In addition, the present application can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0060] At present, there are three main methods for estimating the health status of lithium batteries. The first is the data-driven method, which mainly measures the battery's current, voltage, temperature and other parameters, extracts features that are highly correlated with SOH changes, and uses them as training data for accurate modeling, thereby achieving real-time estimation of the battery's SOH. However, this method is highly dependent on data. If the data contains errors or is incomplete, it will cause large deviations in the SOH predicted by the model. The second method is the model-building method, which is mainly based on circuit elements to simulate the electrochemical process inside the battery. Through a large number of experiments and analyses, a correlation model between circuit elements and the battery's health status is constructed to estimate the battery's SOH. However, this model not only relies on high-quality models, but also requires continuous updating of model parameters during use, which will make the model calculation load heavy. The third method is the impedance method, which mainly establishes the relationship between SOH and impedance after measuring the electrochemical impedance spectrum of the battery under certain conditions. For example, by estimating the number of battery cycles, and then obtaining the battery's SOH through the number of cycles, however, the impedance obtained by these methods generally ignores the influence of the peripheral circuit on the battery under actual conditions. When the peripheral circuit is different, the real impedance of the battery, the charge transfer resistance, that is, the size of the semicircle of the impedance spectrum and the impedance amplitude will change. Therefore, the number of battery cycles can only be estimated under ideal conditions without a peripheral circuit. In addition, although the imaginary impedance is less affected by changes in the peripheral circuit, it is more affected by temperature changes. It is impossible to accurately estimate the number of battery cycles under temperature changes, and therefore, it is impossible to accurately estimate the battery SOH.

[0061] In order to solve the technical problem of how to accurately estimate the health state of lithium-ion batteries in the prior art, the present application provides a lithium battery health state estimation method, device, electronic device and storage medium. Since the imaginary impedance is less affected by the peripheral circuit, and the second mapping relationship between the imaginary impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, the influence of temperature changes on the imaginary impedance is eliminated, thereby accurately realizing the joint estimation of the battery temperature and the battery health state. The lithium battery health state estimation method can also be called a temperature and SOH joint estimation method based on imaginary impedance.

[0062] The first embodiment of the present application provides a method for estimating the health status of a lithium battery. The method can be applied to Figure 1 The system architecture shown includes at least a health status estimation module 101 and a lithium battery 102 . The health status estimation module 101 can perform online health status estimation on the lithium battery 102 .

[0063] Next, based on the system architecture, the lithium battery health status estimation method is described in detail, such as Figure 2 , the lithium battery health state estimation method includes:

[0064] Step 201, measuring a first imaginary impedance of a lithium battery at a first target frequency.

[0065] The first imaginary impedance of the lithium battery at the first target frequency can be measured online, for example, by applying a disturbance signal to the lithium battery, collecting the voltage signal and current signal of the lithium battery under the disturbance signal, and measuring the imaginary impedance at the disturbance signal frequency based on the voltage signal and the current signal. Alternatively, during the charging process of the lithium battery, the voltage signal and the current signal output to the lithium battery by the power conversion circuit are collected, the second harmonic amount of the voltage signal and the current signal is extracted, and the first imaginary impedance at the first target frequency is determined based on the second harmonic amount. For example, the first target frequency can select a temperature characteristic frequency that is sensitive to temperature, or select any frequency in the first frequency range that is sensitive to temperature, for example, the first target frequency can be 100 Hz.

[0066] Step 202, estimating the battery temperature of the lithium battery according to a preset first mapping relationship and a first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature.

[0067] In this embodiment, the first mapping relationship may be a mapping relationship between the imaginary impedance and the battery temperature obtained offline in advance, for example, by offline measuring the electrochemical impedance spectrum (EIS or impedance spectrum) of the lithium battery in a temperature range, obtaining the imaginary impedance of the lithium battery at each temperature in the temperature range based on the impedance spectrum, and fitting the first mapping relationship based on the imaginary impedance corresponding to each temperature and each temperature. The current battery temperature of the lithium battery can be estimated based on the first mapping relationship and the first imaginary impedance.

[0068] Step 203: Determine a second target frequency for measuring the health status according to the battery temperature.

[0069] In this embodiment, the second target frequency for measuring the health status of the lithium battery can be determined according to the current battery temperature of the lithium battery. The second target frequency can select any frequency in the second frequency range that is sensitive to the number of charge and discharge cycles. For example, the second target frequency is a characteristic frequency that characterizes the number of charge and discharge cycles of the lithium battery at the battery temperature. That is, at the second target frequency, the number of cycles can be accurately calculated according to the measured imaginary impedance, and then the accurate health status can be corresponded according to the number of cycles. Specifically, the second frequency range can be, for example, 0.2Hz-1kHz.

[0070] Step 204: measuring a second imaginary impedance of the lithium battery at a second target frequency.

[0071] In this embodiment, the second imaginary impedance of the lithium battery at the second target frequency can be measured online, for example, by applying a disturbance signal to the lithium battery, collecting the voltage signal and current signal of the lithium battery under the disturbance signal, and measuring the imaginary impedance at the disturbance signal frequency based on the voltage signal and the current signal. Alternatively, during the charging process of the lithium battery, the voltage signal and the current signal output to the lithium battery by the power conversion circuit are collected, the second harmonic amount of the voltage signal and the current signal is extracted, and the second imaginary impedance at the second target frequency is determined based on the second harmonic amount.

[0072] Step 205 , estimating the health state of the lithium battery according to a preset second mapping relationship and a second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

[0073] The second mapping relationship includes a set of mapping relationships between the imaginary impedance and the health status corresponding to each temperature at different temperatures, such as the mapping relationship between the imaginary impedance and the health status at each temperature in the temperature range of 0-70°C. Therefore, when estimating the health status of the lithium battery, the mapping relationship at the current battery temperature of the lithium battery can be selected in combination with the measured second imaginary impedance at the second target frequency to achieve accurate estimation of the health status of the lithium battery.

[0074] The method can estimate the battery temperature of the lithium battery according to the first imaginary impedance of the lithium battery at the first target frequency and the first mapping relationship between the imaginary impedance and the battery temperature, and then determine the second target frequency for accurately measuring the battery health state according to the current battery temperature of the lithium battery, so that the health state of the lithium battery can be estimated according to the second imaginary impedance measured at the second target frequency and the preset second mapping relationship between the imaginary impedance and the health state. Since the imaginary impedance is less affected by the peripheral circuit, and the second mapping relationship between the imaginary impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, the influence of temperature change on the imaginary impedance is eliminated, thereby accurately realizing the joint estimation of the battery temperature and the battery health state.

[0075] By measuring the imaginary impedance at different temperatures, it can be found that the current temperature of the battery can be estimated by the imaginary impedance. For example, taking the current temperature as 45°C, Figure 3 The diagram of the imaginary impedance of the battery at different SOCs at 45°C shows that at different states of charge (SOC), 90%, 70%, 50%, 30% and 10%, in the frequency range of 0.2Hz to 1kHz, the imaginary impedance is basically unaffected by SOC. Based on this, the corresponding relationship between the imaginary impedance and the number of cycles at a certain SOC is measured, taking SOC of 50% as an example, Figure 4 The figure is a schematic diagram of the relationship between the imaginary impedance and the number of cycles when the SOC is 50%. It can be seen that the imaginary impedance can reflect the changes in the number of battery cycles. For example, at 0.2Hz~1kHz, when the number of cycles is 0, 40, 80 and 120, the imaginary impedance corresponding to the same frequency has obvious differences. Based on this, a joint estimation method of temperature and SOH based on imaginary impedance is proposed. Figure 5 A schematic diagram is selected for different temperature-frequency points. For example, at 100 Hz, 0°C, 15°C, 30°C, 45°C and 60°C correspond to different imaginary impedances, respectively. The first target frequency of 100 Hz can be selected to estimate the battery temperature of the lithium battery. The battery temperature of the lithium battery can be accurately estimated based on the first imaginary impedance at 100 Hz. Figure 6 This is a schematic diagram of frequency point selection at 0°C. It can be seen that at 0°C, the imaginary impedance corresponding to the second target frequency of 0.05Hz when the number of cycles is 0, 40, 80 and 120 has obvious differences. The second target frequency of 0.05Hz can be selected when the battery temperature of the lithium battery is 0°C, and the second imaginary impedance of the lithium battery at 0.05Hz can be measured, so as to accurately estimate the number of cycles and then accurately estimate the battery health status.

[0076] In one embodiment, before estimating the battery temperature of the lithium battery according to the preset first mapping relationship and the first imaginary impedance, the method further includes: acquiring the first mapping relationship and the second mapping relationship.

[0077] In this embodiment, the generation process of the first mapping relationship and the second mapping relationship includes: when the lithium battery is offline, cyclically charging and discharging the lithium battery; during the cyclic charging and discharging process, recording the maximum available capacity corresponding to each cycle number, and measuring the battery impedance spectrum at different temperatures at each cycle number; wherein the maximum available capacity is used to calculate the health state of the lithium battery at the current cycle number; according to the battery impedance spectrum at different temperatures for the same cycle number, fitting the first mapping relationship between the imaginary impedance and the battery temperature in the first frequency interval; wherein the first target frequency is within the first frequency interval; according to the battery impedance spectrum at the same target temperature for different cycle numbers, obtaining the third mapping relationship between the imaginary impedance and the health state in the second frequency interval at the target temperature; wherein the second target frequency is within the second frequency interval; according to the third mapping relationship at all different target temperatures within the target temperature interval, determining the second mapping relationship between the imaginary impedance and the health state.

[0078] In this embodiment, when the first mapping relationship and the second mapping relationship are obtained offline, the first mapping relationship between the imaginary impedance and the battery temperature in the first frequency range and the second mapping relationship between the imaginary impedance and the health state at all different target temperatures in the target temperature range can be obtained by fitting the battery impedance spectrum at different temperatures of the same number of cycles and the battery impedance spectrum at the same target temperature of different number of cycles obtained during the cyclic charge and discharge process of the lithium battery. Therefore, the battery temperature of the lithium battery can be estimated according to the first imaginary impedance of the lithium battery at the first target frequency and the first mapping relationship between the imaginary impedance and the battery temperature, and then the second target frequency for accurately measuring the battery health state can be determined according to the current battery temperature of the lithium battery. Therefore, the health state of the lithium battery can be estimated according to the second imaginary impedance measured at the second target frequency and the preset second mapping relationship between the imaginary impedance and the health state. Since the imaginary impedance is less affected by the peripheral circuit, and the second mapping relationship between the imaginary impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, the influence of temperature change on the imaginary impedance is eliminated, thereby accurately realizing the joint estimation of the battery temperature and the battery health state.

[0079] In a specific embodiment, a schematic diagram of a method for jointly estimating temperature and SOH based on imaginary impedance is shown in FIG. Figure 7 .

[0080] In this embodiment, during online measurement, the imaginary impedance at 100 Hz (i.e., the first imaginary impedance) can be measured, and the battery temperature can be estimated by combining the relationship between the imaginary impedance and the temperature measured offline (the first mapping relationship). Different SOH measurement frequencies (i.e., the second target frequency) are selected according to the estimated battery temperature, and the imaginary impedance at the second target frequency is measured (i.e., the second imaginary impedance), and the relationship between the imaginary impedance and the SOH measured offline (the second mapping relationship) can be combined to achieve a joint estimation of the temperature and SOH. Of course, the second mapping relationship can be derived through the relationship between the imaginary impedance and the number of cycles, and the relationship between the number of cycles and the SOH.

[0081] In this embodiment, before performing online measurement, the first mapping relationship between imaginary impedance and temperature and the second mapping relationship between imaginary impedance and health status can be obtained by offline measurement. The battery can be charged and discharged cyclically, and the maximum available capacity of the battery is recorded after each 10 cycles. The maximum available capacity is used to calculate the health status of the lithium battery in combination with the rated capacity of the battery. After each 10 cycles and discharge to SOC = 50%, the battery is placed in a thermostat at different temperatures for 1-1.5 hours, and the impedance spectra of the battery at different temperatures are measured using an electrochemical workstation. The battery impedance spectra at different temperatures for the same number of cycles and at the same temperature for different cycles are recorded. The imaginary impedance during temperature estimation can be called Z im1 , the imaginary impedance during SOH estimation is called Z im2 , a temperature-sensitive temperature characteristic frequency (such as 100 Hz) can be selected to establish the first mapping relationship between imaginary impedance and temperature, such as T = f1 (Z im1 ), and establish T at different temperatures x The second mapping relationship between the imaginary impedance and SOH. The establishment process of the second mapping relationship can be specifically as follows: selecting T at different temperatures x The imaginary impedance characterizes the most obvious characteristic frequency f of the number of cycles (i.e. the number of cycles) x , establish different T x 、f x The relationship between the lower imaginary impedance and the number of loops: n x =f(f x , Z im2，x ), establish different T x 、f x Relationship between the number of lower cycle and SOH: SOH x =f(n x ), establish different T x 、f x Relationship between lower imaginary impedance and SOH: SOH x =f(f x , Z im2，x ).

[0082] Taking a specific application scenario as an example, the imaginary impedance data of the lithium battery at a frequency of 100Hz can be measured, and T=f1(Z im1 ) can get the current battery temperature of the battery. If the current battery temperature is 0℃, the imaginary impedance data at f=0.05Hz can be selected. It is similar when the battery is at other temperatures. For example, when the battery temperature is 15℃, the imaginary impedance data at f=0.16Hz can be selected. When the current battery temperature is 30℃, the imaginary impedance data at f=0.3Hz can be selected. When the current battery temperature is 45℃, the imaginary impedance data at f=2Hz can be selected. When the current battery temperature is 60℃, the imaginary impedance data at f=5Hz can be selected. Then according to SOH x =f(f x , Z im2，x ) to obtain the current battery health status. It should be noted that the specific values ​​of the frequency points corresponding to the above different battery temperatures are only examples, and can actually be selected within a frequency range. The frequency points exemplified above do not represent restrictions on the second target frequency corresponding to the battery temperature.

[0083] In one embodiment, after obtaining a third mapping relationship between the imaginary impedance in the second frequency range at the target temperature and the health state based on the battery impedance spectrum of the same target temperature with different cycle numbers, the method further includes: determining the characteristic frequency at each target temperature from the second frequency range; wherein, at the characteristic frequency, the difference in the imaginary impedance between different cycle numbers at the same target temperature is greater than a preset threshold; and obtaining a fourth mapping relationship based on the characteristic frequency corresponding to each target temperature and each target temperature.

[0084] In this embodiment, in order to facilitate the determination of the second target frequency for measuring the battery health status at the current battery temperature according to the battery temperature, a fourth mapping relationship can be generated between the characteristic frequencies corresponding to each target temperature and each target temperature during offline testing. For example, the current battery temperature of 0°C corresponds to the characteristic frequency f=0.05Hz, and the current battery temperature of 60°C corresponds to the characteristic frequency f=5Hz. It should be noted again that the characteristic frequency can be a frequency range. The specific frequencies exemplified above do not represent restrictions on the frequency range at that temperature. At the characteristic frequency, the difference in imaginary impedance between different cycle numbers at the same target temperature is greater than a preset threshold, that is, at the characteristic frequency, the current cycle number can be distinguished according to the value of the imaginary impedance, and the characteristic frequencies corresponding to different temperatures may be different.

[0085] In one embodiment, determining a second target frequency for measuring the health state according to the battery temperature includes: determining a target characteristic frequency according to the battery temperature and a fourth mapping relationship; and using the target characteristic frequency as the second target frequency for measuring the health state at the battery temperature.

[0086] In this embodiment, after estimating the battery temperature of the lithium battery according to the preset first mapping relationship and the first imaginary impedance, the target characteristic frequency of the current battery temperature can be conveniently and quickly determined according to the battery temperature and the fourth mapping relationship, so that the second imaginary impedance of the lithium battery at the target characteristic frequency can be measured.

[0087] In one embodiment, according to the battery impedance spectrum of the same target temperature with different cycle numbers, a third mapping relationship between the imaginary impedance in the second frequency range at the target temperature and the health state is obtained, including: according to the battery impedance spectrum of the same target temperature with different cycle numbers, a first functional relationship between the imaginary impedance in the second frequency range at the target temperature and the number of cycles is obtained, and a second functional relationship between the number of cycles in the second frequency range at the target temperature and the health state is obtained; and the third mapping relationship is determined based on the first functional relationship and the second functional relationship.

[0088] In this embodiment, the mathematical model of the number of cycles related to the frequency and the imaginary impedance of the battery can be obtained according to the data fitting, and the battery temperature is 30° C. as an example. Figure 8 The relationship between the number of cycles, imaginary impedance and frequency at 30°C is shown in Figure 2. The predicted data points can be inferred based on the original data points, and the mathematical model n=F(f, Z im ), for example, the mathematical model is as follows:

[0089] n=-99.193+6.8864f-1307929.1429Z im -105010.8997Z im *f

[0090] Among them, Z im is the imaginary impedance, f is the frequency corresponding to the battery temperature, and n is the number of cycles. Based on this formula, the number of battery cycles corresponding to a certain temperature can be estimated online through the imaginary impedance.

[0091] Fig. 9 The figure is a schematic diagram of the relationship between the battery's imaginary impedance and the number of cycles. Further, a mathematical model of the battery's health status can be fitted based on the number of cycles. For example, taking the battery temperature at 30°C as an example, Fig.10 The figure is a schematic diagram of the relationship between the battery health status and the number of cycles. The fitted mathematical model SOH = F (n) can be as follows:

[0092] SOH=0.9993+(-0.0001n)

[0093] At a single temperature, n = F (f, Z im ) is combined with SOH=F(n) to obtain SOH=F(f,Z im ), taking the battery temperature of 30°C as an example, Fig.11Schematic diagram of the relationship between the number of cycles and the imaginary impedance at 30°C:

[0094] SOH=1.0283-0.0359Z im -8.6592f+0.0174Z im 2 +119.5602Z im f-527053.3

[0095] 534f 2

[0096] By fitting the battery health status and imaginary impedance at different temperatures, the general functional relationship between the battery health status and the imaginary impedance can be obtained as follows:

[0097] SOH=C1-C2f-C3Z im +C4f 2 +C5f im -C6Z im 2

[0098] Where f is the frequency, Z im is the imaginary impedance of the battery corresponding to the frequency, C1, C2, C3, C4, C5, and C6 are corresponding coefficients, and the specific value of each coefficient is not limited and can be obtained by fitting.

[0099] In one embodiment, during the cyclic charge and discharge process, the maximum available capacity corresponding to each cycle number is recorded, and the battery impedance spectrum at different temperatures is measured at each cycle number, including: during the cyclic charge and discharge process, the current maximum available capacity of the lithium battery is recorded after every ten cycles; and after every ten cycles and when the battery is discharged to a state of charge of 50%, the lithium battery is placed in a constant temperature box, and the battery impedance spectrum of the lithium battery is measured at different temperatures at the set temperature of the constant temperature box.

[0100] In this embodiment, in order to increase the speed of offline acquisition of mapping relationships, the amount of some data can be reduced. For example, during the cyclic charge and discharge process, the current maximum available capacity of the lithium battery is recorded every ten cycles, and when the lithium battery is discharged to 50% of the charge state after ten cycles, the lithium battery is placed in a constant temperature box to measure the battery impedance spectrum of the lithium battery at different temperatures at the set temperature of the constant temperature box. Specifically, the battery impedance spectrum at each temperature can be measured and placed in the constant temperature box for a period of time to keep the internal temperature of the battery consistent with the set temperature of the constant temperature box, thereby improving the accuracy of the data.

[0101] In the above embodiments of the present application, the health state of the battery can be estimated based on the imaginary impedance of the battery at the current temperature, thereby realizing the joint estimation of the battery temperature and the battery health state. In addition, the estimation method is not affected by the SOC and peripheral circuits, thereby improving the accuracy of the battery health state estimation.

[0102] Based on the same technical concept, the second embodiment of the present application provides a lithium battery health status estimation device, such as Fig.12 , the device comprises:

[0103] A first measuring module 1201 is used to measure a first imaginary impedance of a lithium battery at a first target frequency;

[0104] A first estimation module 1202, configured to estimate the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature;

[0105] A determination module 1203, configured to determine a second target frequency for measuring a health state according to the battery temperature;

[0106] A second measuring module 1204, configured to measure a second imaginary impedance of the lithium battery at the second target frequency;

[0107] The second estimation module 1205 is used to estimate the health state of the lithium battery according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

[0108] The device can estimate the battery temperature of the lithium battery according to the first imaginary impedance of the lithium battery at the first target frequency and the first mapping relationship between the imaginary impedance and the battery temperature, and then determine the second target frequency for accurately measuring the battery health state according to the current battery temperature of the lithium battery, so that the health state of the lithium battery can be estimated according to the second imaginary impedance measured at the second target frequency and the preset second mapping relationship between the imaginary impedance and the health state. Since the imaginary impedance is less affected by the peripheral circuit, and the second mapping relationship between the imaginary impedance and the health state corresponding to the current battery temperature of the lithium battery is selected for estimation, the influence of temperature change on the imaginary impedance is eliminated, thereby accurately realizing the joint estimation of the battery temperature and the battery health state.

[0109] like Fig.13 As shown, an embodiment of the present application provides an electronic device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0110] Memory 113, used for storing computer programs;

[0111] In one embodiment of the present application, the processor 111 is used to execute the program stored in the memory 113 to implement the lithium battery health state estimation method provided by any of the above method embodiments, including:

[0112] Measuring a first imaginary impedance of the lithium battery at a first target frequency;

[0113] estimating the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature;

[0114] determining a second target frequency for measuring a health state according to the battery temperature;

[0115] measuring a second imaginary impedance of the lithium battery at the second target frequency;

[0116] The health state of the lithium battery is estimated according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

[0117] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0118] The communication interface is used for communication between the above terminal and other devices.

[0119] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0120] The above-mentioned processor 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 gate or transistor logic devices, discrete hardware components.

[0121] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, a lithium battery health status estimation method as provided in any of the aforementioned method embodiments is implemented.

[0122] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] 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, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0124] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0125] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. In the description, the suffixes such as "module", "component" or "unit" used to represent the elements are only used to facilitate the description of the present application and have no specific meaning in themselves. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0126] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A method for estimating the health status of a lithium battery, characterized in that: The method comprises: Measuring a first imaginary impedance of the lithium battery at a first target frequency; estimating the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature; determining a second target frequency for measuring a health state according to the battery temperature; measuring a second imaginary impedance of the lithium battery at the second target frequency; The health state of the lithium battery is estimated according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

2. The method according to claim 1, characterized in that Before estimating the battery temperature of the lithium battery according to the preset first mapping relationship and the first imaginary impedance, the method further includes: Acquire the first mapping relationship and the second mapping relationship; The generation process of the first mapping relationship and the second mapping relationship includes: When the lithium battery is offline, the lithium battery is charged and discharged cyclically; During the cyclic charge and discharge process, the maximum available capacity corresponding to each cycle number is recorded, and the battery impedance spectrum at different temperatures is measured at each cycle number; wherein the maximum available capacity is used to calculate the health status of the lithium battery at the current cycle number; According to the battery impedance spectra of the same number of cycles at different temperatures, fitting a first mapping relationship between the imaginary impedance and the battery temperature in a first frequency interval; wherein the first target frequency is within the first frequency interval; According to the battery impedance spectra of the same target temperature with different cycle numbers, a third mapping relationship between the imaginary impedance and the health state in the second frequency interval at the target temperature is obtained; wherein the second target frequency is within the range of the second frequency interval; According to the third mapping relationship at all different target temperatures within the target temperature range, a second mapping relationship between the imaginary impedance and the health state is determined.

3. The method according to claim 2, characterized in that After obtaining a third mapping relationship between the imaginary impedance in the second frequency interval and the health state at the target temperature according to the battery impedance spectra of the battery at the same target temperature with different cycle numbers, the method further includes: Determine a characteristic frequency at each target temperature from the second frequency interval; wherein, at the characteristic frequency, the difference in imaginary impedance between different cycle times at the same target temperature is greater than a preset threshold; A fourth mapping relationship is obtained according to the characteristic frequencies corresponding to the respective target temperatures and the respective target temperatures.

4. The method according to claim 3, characterized in that Determining a second target frequency for measuring a health state according to the battery temperature includes: determining a target characteristic frequency according to the battery temperature and the fourth mapping relationship; The target characteristic frequency is used as the second target frequency for measuring the health state at the battery temperature.

5. The method according to claim 3, characterized in that: According to the battery impedance spectra of the same target temperature with different cycle numbers, a third mapping relationship between the imaginary impedance in the second frequency interval and the health state at the target temperature is obtained, including: According to the battery impedance spectra of the same target temperature with different cycle numbers, a first functional relationship between the imaginary impedance and the cycle number in the second frequency range at the target temperature and a second functional relationship between the cycle number and the health state in the second frequency range at the target temperature are obtained; The third mapping relationship is determined according to the first functional relationship and the second functional relationship.

6. The method according to claim 2, characterized in that During the cyclic charge and discharge process, the maximum available capacity corresponding to each cycle number is recorded, and the battery impedance spectrum at different temperatures is measured at each cycle number, including: During the cyclic charge and discharge process, recording the current maximum available capacity of the lithium battery after every ten cycles; and After every ten cycles and when the battery is discharged to a state of charge of 50%, the lithium battery is placed in a thermostat to measure the battery impedance spectrum of the lithium battery at different temperatures set by the thermostat.

7. The method according to claim 1, characterized in that The second frequency interval includes 0.2 Hz-1 kHz.

8. A lithium battery health status estimation device, characterized in that: The device comprises: A first measuring module, used to measure a first imaginary impedance of the lithium battery at a first target frequency; A first estimation module, used for estimating the battery temperature of the lithium battery according to a preset first mapping relationship and the first imaginary impedance; wherein the first mapping relationship is a mapping relationship between the imaginary impedance and the battery temperature; a determination module, configured to determine a second target frequency for measuring a health state according to the battery temperature; A second measuring module, used to measure a second imaginary impedance of the lithium battery at the second target frequency; The second estimation module is used to estimate the health state of the lithium battery according to a preset second mapping relationship and the second imaginary impedance; wherein the second mapping relationship is a mapping relationship between the imaginary impedance and the health state.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the lithium battery health status estimation method described in any one of claims 1-7 when executing the program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for estimating the health status of a lithium battery as described in any one of claims 1 to 7 is implemented.

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