Battery health determination method, device, equipment, medium and program product

Abstract

The present application provides a method, apparatus, device, medium and program product for determining battery health. The specific scheme includes: determining the production batch and usage level of the target battery; obtaining the available capacity gain thermal characteristic model corresponding to the matching sample battery according to the production batch and usage level of the target battery; inputting the standard temperature into the available capacity gain thermal characteristic model, and calculating the available capacity gain of the target battery; and determining the battery health of the target battery according to the available capacity gain of the target battery. By calibrating the actual available capacity gain of the sample battery in terms of temperature through the available capacity gain thermal characteristic model, the influence of temperature on the measured value of the current sensor and the maximum available capacity of the battery can be eliminated. The available capacity gain of the target battery at the standard temperature is determined as the battery health of the target battery, which can eliminate the influence of the accuracy of the current sensor on the battery health calculation result, thereby improving the accuracy of determining the battery health.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a method, device, equipment, medium, and program product for determining battery health. Background Art

[0002] Battery State of Health (SOH) is a quantitative indicator used to assess a battery's energy storage capacity. It expresses the battery's state from the beginning to the end of its life as a percentage, quantitatively describing the battery's current state of health. It can be determined by taking the ratio of the battery's maximum available capacity in its current state to its rated capacity. The battery's maximum available capacity decreases over time, and the accuracy of sensors in the battery system also changes over time, leading to measurement errors. Accurately assessing battery health and promptly retiring aging batteries are crucial for maintaining the proper functioning of equipment and recycling power batteries.

[0003] In the prior art, the maximum available capacity of a battery is obtained by current integration, and the battery health is determined by calculating the ratio of the maximum available capacity to the rated capacity of the battery.

[0004] The principle of current integration is to integrate the current value measured by the current sensor with time in real time during the battery's charge / discharge process. The integration result is the battery's maximum available capacity. Therefore, in the existing technology, the current sensor's measurement value is coupled with the integration result. Measurement errors of the current sensor directly lead to deviations in the integration result, and the accuracy of the current sensor affects the battery health determined based on the integration result. Moreover, under different temperature conditions, the current sensor's measurement value and the battery's maximum available capacity may vary.

[0005] In the prior art, the influence of the accuracy of the current sensor on the battery health calculation result is not eliminated, and the influence of temperature on the measured value of the current sensor and the maximum available capacity of the battery during current integration is not considered, resulting in poor accuracy in determining the battery health. Summary of the Invention

[0006] The present application provides a battery health determination method, apparatus, device, medium and program product to solve the problem that the accuracy of the current sensor and the battery temperature will affect the calculation results of the battery health, resulting in poor accuracy in determining the battery health.

[0007] In a first aspect, the present application provides a method for determining battery health, comprising:

[0008] Determine the production batch and usage level of the target battery;

[0009] Obtaining a thermal characteristic model of available capacity gain corresponding to a matching sample battery according to the production batch and usage level of the target battery, wherein the thermal characteristic model of available capacity gain is a model that calibrates the actual available capacity gain of the sample battery in terms of temperature;

[0010] Inputting the standard temperature into the available capacity gain thermal characteristic model and calculating the target battery available capacity gain;

[0011] The battery health of the target battery is determined according to the available capacity gain of the target battery.

[0012] In a second aspect, the present application provides a device for determining battery health, comprising:

[0013] A determination module, used to determine the production batch and usage level of the target battery;

[0014] an acquisition module, configured to acquire, based on the production batch and usage level of the target battery, an available capacity gain thermal characteristic model corresponding to a matching sample battery, wherein the available capacity gain thermal characteristic model is a model for calibrating the actual available capacity gain of the sample battery in terms of temperature;

[0015] a calculation module, configured to input a standard temperature into the available capacity gain thermal characteristic model and calculate a target battery available capacity gain;

[0016] The determination module is further configured to determine the battery health of the target battery according to the available capacity gain of the target battery.

[0017] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0018] The processor and the memory are interconnected by circuits;

[0019] The memory stores computer-executable instructions;

[0020] The processor executes the computer-executable instructions stored in the memory to implement the above-mentioned battery health determination method.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above-mentioned battery health determination method.

[0022] In a fifth aspect, the present application provides a computer program product, comprising computer-executable instructions, which, when executed by a processor, implement the above-mentioned data processing method based on printed circuit board film.

[0023] The battery health determination method, apparatus, device and storage medium provided in the present application determine the production batch and usage level of the target battery; obtain the available capacity gain thermal characteristic model corresponding to the matching sample battery based on the production batch and usage level of the target battery, and the available capacity gain thermal characteristic model is a model that calibrates the actual available capacity gain of the sample battery in terms of temperature; inputs the standard temperature into the available capacity gain thermal characteristic model, and calculates the available capacity gain of the target battery; and determines the battery health of the target battery based on the available capacity gain of the target battery. By calibrating the actual available capacity gain of the sample battery in terms of temperature through the available capacity gain thermal characteristic model, the influence of temperature on the measured value of the current sensor and the maximum available capacity of the battery can be eliminated. The available capacity gain of the target battery at the standard temperature is determined as the battery health of the target battery, which can eliminate the influence of the accuracy of the current sensor on the battery health calculation result, thereby improving the accuracy of the determination of the battery health. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] 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.

[0025] Figure 1 This is a schematic diagram of an application scenario of this application;

[0026] Figure 2 A flow chart of the method for determining battery health provided in Example 1 of the present application;

[0027] Figure 3 A flow chart of a method for determining battery health provided in Example 2 of this application;

[0028] Figure 4 A schematic diagram of the structure of a device for determining battery health provided in Example 4 of the present application;

[0029] Figure 5 This is a structural diagram of the electronic device provided in Example 5 of the present application.

[0030] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0031] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0032] The terms "first," "second," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. In the description of the following embodiments, "plurality" means more than two, unless otherwise specifically defined.

[0033] First, the prior art involved in the present invention is described and analyzed in detail.

[0034] Battery health (SOH) indicates a battery's ability to store energy relative to a new battery. SOH represents the battery's state from the beginning to the end of its life as a percentage, quantitatively describing the current state of health. Battery health is evaluated using a variety of metrics, primarily capacity, charge, internal resistance, cycle count, and peak power.

[0035] In the prior art, battery capacity is used as an evaluation indicator of battery health, and the battery health is determined by the ratio of the maximum available capacity of the battery in the current state to the rated capacity.

[0036] However, since the maximum available capacity of a battery gradually decreases over time, the accuracy of the sensors in the battery system will also change over time, resulting in measurement errors in the sensors. The measurement errors of the current sensor will directly lead to deviations in the current integration results. The accuracy of the current sensor will affect the battery health determined based on the current integration results. In addition, under different temperature conditions, the measurement value of the current sensor and the maximum available capacity of the battery may change. However, in the existing technology, the impact of the current sensor accuracy on the battery health calculation results is not eliminated, and the impact of temperature on the current sensor measurement value and the maximum available capacity of the battery during current integration is not considered, resulting in poor accuracy in determining the battery health.

[0037] In view of the problem in the prior art that the influence of the accuracy of the current sensor on the calculation result of the battery health is not eliminated, and the influence of the temperature on the measured value of the current sensor and the maximum available capacity of the battery during current integration is not considered, resulting in poor accuracy in determining the battery health. The inventors found in their research that the available capacity gain thermal characteristic model can be used to calibrate the actual available capacity gain of the battery in terms of temperature, and the available capacity gain at the calibrated standard temperature is the battery health. According to the charge and discharge data of the sample battery matching the target battery, the first fitting parameter in the available capacity gain thermal characteristic model is fitted to determine the available capacity gain thermal characteristic model corresponding to the sample battery matching the target battery.

[0038] Figure 1 This is a schematic diagram of an application scenario of this application, such as Figure 1 As shown, an application scenario of the present application includes: a sample battery 1, a battery health determination device 2, and a target battery 3. The battery health determination device 2 can obtain the charge and discharge data of the sample battery, and determine a thermal characteristic model of the available capacity gain of the sample battery that matches the sample battery based on the charge and discharge data of the sample battery 1; the battery health determination device 2 can also obtain the production batch and usage level of the target battery 3, and obtain a matching thermal characteristic model of the available capacity gain based on the obtained production batch and usage level of the target battery 3. The standard temperature is substituted into the matching thermal characteristic model of the available capacity gain to calculate the available capacity gain of the target battery at the standard temperature. The available capacity gain at the standard temperature is the health of the target battery.

[0039] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0040] Example 1

[0041] Figure 2This is a flow chart of a method for determining battery health provided in the first embodiment of the present application. This embodiment of the present application addresses the problem that the accuracy of the current sensor and the battery temperature will affect the calculation results of the battery health, resulting in poor accuracy in determining the battery health, and provides a method for determining battery health. The method in this embodiment is applied to a battery health determination device, and the battery health determination device can be located in an electronic device. The electronic device can be a digital computer representing various forms. Such as a laptop computer, a desktop computer, a workbench, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices.

[0042] like Figure 2 As shown, the specific steps of this method are as follows:

[0043] Step S101: Determine the production batch and usage level of the target battery.

[0044] The target battery refers to the battery whose health is to be determined. The usage level is at least one indicator that reflects the battery's usage level. For example, the usage level can be the total time from the first use of the battery after production to its determination as a target battery. For another example, if the target battery is a battery in a car, the usage level can also be the car's mileage.

[0045] For example, a request for obtaining information can be sent to a user system using the target battery to obtain the production batch and usage level of the target battery. A communication connection can also be established with the target battery system to read the production batch and usage level stored in the target battery system. The production batch stored in the target battery system can also be determined by inputting the label information of the target battery, and the production time of the target battery can be determined based on the production batch, thereby determining the usage level of the target battery. The embodiment of the present application does not specifically limit the specific method for determining the production batch and usage level of the target battery.

[0046] Step S102: Obtain an available capacity gain thermal characteristic model corresponding to a matching sample battery according to the production batch and usage level of the target battery.

[0047] The available capacity gain thermal characteristic model calibrates the actual available capacity gain of a sample battery over temperature. Available capacity gain refers to the deviation between the available capacity of a sample battery and its rated capacity at standard temperature. The available capacity gain of an unused, post-production battery at standard temperature is 100%.

[0048] Specifically, a local storage space of the electronic device stores the available capacity gain thermal characteristic model corresponding to the sample battery. The matching sample battery is determined according to the production batch and usage level of the target battery. By accessing the storage space, the available capacity gain thermal characteristic model corresponding to the matching sample battery is obtained.

[0049] In the embodiment of the present application, batteries whose production batches are within the same preset batch and whose usage levels are within the same preset range are considered to be a batch of sample batteries.

[0050] Specifically, it is determined whether the production batch of the target battery is within the preset batch and whether the usage level of the target battery is within the preset range; if the production batch of the target battery is within the preset batch and the usage level is within the preset range, the target battery is matched with the sample battery corresponding to the preset batch and the usage level.

[0051] For example, the production batch of the first sample battery is X or Z, and the usage period is one to two years; the production batch of the second sample battery is Y, and the usage period is one to two years; the production batch of the third sample battery is X or Z, and the usage period is two to three years; taking the production batch of the target battery as X and the usage period of three years as an example, the target battery is matched with the third sample battery, and the available capacity gain thermal characteristic model corresponding to the third sample battery is obtained.

[0052] Step S103: input the standard temperature into the available capacity gain thermal characteristic model, and calculate the target battery available capacity gain.

[0053] In the embodiment of the present application, the standard temperature may be the standard condition specified in thermodynamics, i.e., 298 Kelvin, i.e., 25 degrees Celsius. The standard temperature may also be the average operating environment temperature of other reaction target batteries.

[0054] Specifically, the standard temperature is input into the available capacity gain thermal characteristic model, and the calculation result of the available capacity gain thermal characteristic model is the target battery available capacity gain at the standard temperature.

[0055] For example, the available capacity gain thermal characteristic model for the matched sample battery is represented by K2(T0), where T0 is the standard temperature. The specific value of the standard temperature is then input into the available capacity gain thermal characteristic model. For example, if the standard temperature is 298K (Kelvin), K2(298K) is calculated.

[0056] Step S104: Determine the battery health of the target battery according to the available capacity gain of the target battery.

[0057] Specifically, the target battery's available capacity gain at the standard temperature is determined as the target battery's battery health. The target battery's available capacity gain at the standard temperature is the ratio of the target battery's maximum available capacity to its rated capacity at the standard temperature. Therefore, the target battery's available capacity gain at the standard temperature can be directly used as the target battery's battery health.

[0058] In an embodiment of the present application, the production batch and usage level of the target battery are determined; based on the production batch and usage level of the target battery, an available capacity gain thermal characteristic model corresponding to a matching sample battery is obtained, the available capacity gain thermal characteristic model being a model for calibrating the actual available capacity gain of the sample battery in terms of temperature; the standard temperature is input into the available capacity gain thermal characteristic model, and the available capacity gain of the target battery is calculated; and the battery health of the target battery is determined based on the available capacity gain of the target battery. By calibrating the actual available capacity gain of the sample battery in terms of temperature using the available capacity gain thermal characteristic model, the effect of temperature on the measured value of the current sensor and the maximum available capacity of the battery can be eliminated. By determining the available capacity gain of the target battery at the standard temperature as the battery health of the target battery, the effect of the accuracy of the current sensor on the battery health calculation result can be eliminated, thereby improving the accuracy of determining the battery health.

[0059] Example 2

[0060] Figure 3 The flowchart of the battery health determination method provided in the second embodiment of the present application is based on the above-mentioned first embodiment. This embodiment involves the specific process of determining the available capacity gain thermal characteristic model corresponding to the sample battery before obtaining the available capacity gain thermal characteristic model corresponding to the matching sample battery according to the production batch and usage level of the target battery in step S102.

[0061] like Figure 3 As shown, the specific steps of this method are as follows:

[0062] Step S201: Obtain a thermal characteristic model of the available capacity gain of an initial sample battery.

[0063] The thermal characteristic model of the available capacity gain of the initial sample battery includes at least one first fitting parameter.

[0064] Specifically, a preset public form is obtained, and a thermal characteristic model of the available capacity gain of the initial sample battery is determined based on the preset public form and initial parameter values. The preset public form is a public form that conforms to the law of how the available capacity gain of the battery changes with temperature, for example, a polynomial form or an Arrhenius formula form.

[0065] Step S202: Obtain charge and discharge data of at least one batch of sample batteries.

[0066] The usage level of each batch of sample batteries is within a preset range, and the health of the sample batteries does not change significantly within the preset range. For example, if the health of the sample batteries changes by less than 1% within 30,000 kilometers, the preset range can be 30,000 kilometers. Then, the charge and discharge data of the sample batteries with a mileage of 0 to 30,000 kilometers is a batch, the charge and discharge data of the sample batteries with a mileage of 30,000 to 60,000 kilometers is a batch, and the charge and discharge data of the sample batteries with a mileage of 60,000 to 90,000 kilometers is a batch.

[0067] In the embodiment of the present application, the charge and discharge data may include: discharge depth, ambient temperature, rated capacity of the sample battery at a standard temperature, and chargeable or dischargeable capacity.

[0068] Specifically, the following operations are performed for each batch of sample batteries: the rated capacity of the sample battery at the standard temperature is obtained; the discharge depth and ambient temperature of the sample battery are obtained; a charging operation or a discharging operation is performed on the sample battery to obtain a current value through a current sensor; current integration is performed over time according to the current value, and the current integration result is determined as the chargeable capacity or dischargeable capacity of the sample battery; the discharge depth, ambient temperature, the rated capacity of the sample battery at the standard temperature, and the chargeable capacity or dischargeable capacity are determined as the charge and discharge data.

[0069] For example, if the sample battery is charged, the chargeable amount of the sample battery can be determined based on the current integration result; if the sample battery is discharged, the dischargeable amount of the sample battery can be determined based on the current integration result.

[0070] In an embodiment of the present application, the charge and discharge data of at least one batch of sample batteries can be obtained online or offline. The online acquisition can include sending a request to obtain the charge and discharge data to a user system using the sample batteries and receiving the charge and discharge data sent by the user system of the sample batteries, thereby obtaining the charge and discharge data of at least one batch of sample batteries online. The offline acquisition can include obtaining at least one batch of sample batteries, performing a charging or discharging operation on the sample batteries, and performing a measurement operation on the sample batteries, thereby obtaining the charge and discharge data of at least one batch of sample batteries offline. Furthermore, the usage level of the sample batteries can also be obtained to process the sample batteries in batches.

[0071] Step S203 : For each batch of sample batteries, calculate the first fitting parameter in the thermal characteristic model of the available capacity gain of the initial sample batteries according to the charge and discharge data to obtain a thermal characteristic model of the available capacity gain of the sample batteries that matches the sample batteries.

[0072] Specifically, the thermal characteristic model of the available capacity gain of the initial sample battery is fitted and calculated based on the charging data of each batch of sample batteries, and the first fitting parameter in the thermal characteristic model is determined. The first fitting parameter is brought into the thermal characteristic model of the available capacity gain of the initial sample battery to obtain a thermal characteristic model of the available capacity gain of the sample battery that matches the sample battery.

[0073] In the embodiment of the present application, calculating the first fitting parameter in the thermal characteristic model of the available capacity gain of the initial sample battery according to the charge and discharge data specifically includes the following steps:

[0074] Step S2031: For each batch of sample batteries, obtain a relationship between the actual maximum available capacity and the measured available capacity of the sample batteries, and obtain a thermal characteristic model of the initial current sensor sampling accuracy gain.

[0075] In the embodiment of the present application, if the charge and discharge data obtained in step S202 includes the chargeable capacity, the relationship between the actual maximum available capacity of the sample battery obtained and the measured available capacity is expressed as: C1(T)=DOD test C2(T); If the charge and discharge data obtained in step S202 includes the dischargeable capacity, the relationship between the actual maximum available capacity of the sample battery obtained and the measured available capacity is expressed as: C1(T) = (1-DOD test )C2(T);C1(T)=K1(T)∫I r dt; C2(T)=K2(T)C nom .

[0076] Where C1(T) is the measured available capacity, C2(T) is the actual maximum available capacity of the sample battery, and DOD test is the depth of discharge, K1(T) is the thermal characteristic model of the initial sample battery available capacity gain, K2(T) is the thermal characteristic model of the initial current sensor sampling accuracy gain, ∫I r dt is the chargeable or dischargeable capacity, C nom is the rated capacity of the sample battery at standard temperature, and T is the ambient temperature.

[0077] In an embodiment of the present application, the thermal characteristic model of the initial current sensor sampling accuracy gain can be in the same formula form as the thermal characteristic model of the initial sample battery available capacity gain. For example, the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in polynomial form; or the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in the form of Arrhenius formula. The thermal characteristic model of the initial current sensor sampling accuracy gain can also be in a different formula form from the thermal characteristic model of the initial sample battery available capacity gain. For example, if the current sensor is a temperature-insensitive sensor (such as a power shunt), the thermal characteristic model of the initial current sensor sampling accuracy gain can be a constant, and the thermal characteristic model of the initial sample battery available capacity gain can be in the form of a polynomial or an Arrhenius formula.

[0078] Step S2032: Inputting the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain into the relational expression.

[0079] Among them, the actual maximum available capacity of the sample battery is represented by a thermal characteristic model of the initial sample battery available capacity gain, and the measured available capacity is represented by a thermal characteristic model of the chargeable capacity or the dischargeable capacity and the initial current sensor sampling accuracy gain; the thermal characteristic model of the initial current sensor sampling accuracy gain includes at least one second fitting parameter.

[0080] Step S2033: input the charge and discharge data of each batch of sample batteries into the relational expression, and perform fitting on the first fitting parameter to calculate the first fitting parameter.

[0081] Specifically, the first fitting parameter and the second fitting parameter in the thermal characteristic model of the initial current sensor sampling accuracy gain are fitted to calculate the first fitting parameter and the second fitting parameter. The thermal characteristic model of the current sensor sampling accuracy gain obtained to match the sample battery can be a constant. For example, if the current sensor of the sample battery is a power shunt, which is insensitive to temperature and has a small impact on its accuracy, the thermal characteristic model of the current sensor sampling accuracy gain obtained to match the sample battery is a constant.

[0082] For example, the first fitting parameter can be fitted using one of the least squares method, a traditional optimization algorithm, and an intelligent optimization algorithm to calculate the first fitting parameter. Other algorithms can also be used to fit the first fitting parameter, and the embodiments of the present application do not specifically limit this. Among them, the least squares method can be recursive least squares or least squares with a forgetting factor, the traditional optimization algorithm can be a gradient descent method, and the intelligent optimization algorithm can be a genetic algorithm, a neural network algorithm, or a deep learning algorithm.

[0083] In the embodiment of the present application, after calculating the first fitting parameter, the first fitting parameter is substituted into the thermal characteristic model of the available capacity gain of the initial sample battery to obtain the thermal characteristic model of the available capacity gain of the sample battery that matches the sample battery.

[0084] In the embodiment of the present application, the sampling accuracy of the current sensor is calibrated at temperature using a thermal characteristic model of the current sensor sampling accuracy gain, which can eliminate the influence of the current sensor accuracy on the battery health calculation result; the measured maximum available capacity after calibration is equal to the actual maximum available capacity of the battery, and the measured maximum available capacity can be obtained based on the discharge depth and the measured available capacity. The actual maximum available capacity of the battery is the battery rated capacity multiplied by the available capacity gain, and the relationship between the actual maximum available capacity of the battery and the measured available capacity can be constructed. Based on the relationship between the actual maximum available capacity of the battery and the measured available capacity, the available capacity gain thermal characteristic model can be determined, and the available capacity gain at the standard temperature after calibration can be further determined, and the battery health can be determined.

[0085] Optionally, based on any of the above embodiments, after determining the battery health of the target battery according to the target battery available capacity gain, the method further includes: if it is determined that the battery health is in an abnormal state, sending target battery aging prompt information to the user terminal.

[0086] In an embodiment of the present application, after determining the battery health of the target battery, a preset health threshold can be obtained to determine whether the battery health of the target battery is less than the preset health threshold. If the battery health of the target battery is less than the preset health threshold, a target battery aging prompt message is sent to the user terminal to scrap or retire the target battery system for recycling to maintain the normal operation of the equipment.

[0087] Example 3

[0088] The present invention provides a detailed description of the battery health determination method provided by the present invention with reference to a specific example. In the present invention, the standard temperature is 25 degrees Celsius, i.e., 298 Kelvin, and the current sensor is a Hall effect sensor. The Hall effect sensor is temperature sensitive. The specific steps of the method are as follows:

[0089] Step S301: Obtain a thermal characteristic model of the available capacity gain of an initial sample battery.

[0090] In the embodiment of the present application, the thermal characteristic model of the available capacity gain of the initial sample battery obtained is a quadratic polynomial, specifically expressed as: K2(T)=a2T 2 +b2T+c2.

[0091] Step S302: Obtain charge and discharge data of at least one batch of sample batteries.

[0092] In the embodiment of the present application, the method for obtaining the charge and discharge data of at least one batch of sample batteries is similar to that in step S202 and will not be described in detail here.

[0093] Step S303 : For each batch of sample batteries, calculate the first fitting parameter in the thermal characteristic model of the available capacity gain of the initial sample batteries according to the charge and discharge data to obtain a thermal characteristic model of the available capacity gain of the sample batteries that matches the sample batteries.

[0094] Specifically, the thermal characteristic model of the initial current sensor sampling accuracy gain is obtained and the relationship between the actual maximum available capacity and the measured available capacity of the sample battery is obtained. The thermal characteristic model of the initial current sensor sampling accuracy gain obtained is a quadratic polynomial, specifically expressed as: K1(T)=a1T 2 +b1T+c1. The relationship between the actual maximum available capacity of the sample battery and the measured available capacity is: C1(T)=DOD test C2(T).

[0095] Where C1(T) is the measured available capacity, C2(T) is the actual maximum available capacity of the sample battery, and C1(T) = ∫K1(T)I r dt=∫(a1T 2 +b1T+c1)I r dt, C2(T)=(a2T 2 +b2T+c2)C nom .

[0096] Optionally, by substituting C1(T) and C2(T) into the relationship between the actual maximum available capacity and the measured available capacity of the sample battery, we can further obtain:

[0097]

[0098] Among them, a1, b1, and c1 are the first fitting parameters, and a2, b2, and c2 are the second fitting parameters.

[0099] In the embodiment of the present application, based on the large amount of charge and discharge data of the sample battery under different temperature conditions obtained in step S302 and the relationship between the actual maximum available capacity and the measured available capacity of the sample battery after substituting C1(T) and C2(T), the first fitting parameter and the second fitting parameter can be solved using an algorithm such as the least squares method to calculate the first fitting parameter. The calculated first fitting parameter is substituted into the thermal characteristic model of the available capacity gain of the initial sample battery to obtain a thermal characteristic model of the available capacity gain of the sample battery that matches the sample battery.

[0100] Step S304: Determine the production batch and usage level of the target battery.

[0101] Step S305 : obtaining an available capacity gain thermal characteristic model corresponding to a matching sample battery according to the production batch and usage level of the target battery.

[0102] In the embodiment of the present application, the available capacity gain thermal characteristic model corresponding to the matched sample battery is substituted into the formula of the calculated first fitting parameter, specifically K2(T)=a2T 2 +b2T+c2. For example, taking the calculated first fitting parameters as a1=A, b1=B, c1=C as an example, the available capacity gain thermal characteristic model corresponding to the matched sample battery is K2(T)=AT 2 +BT+C.

[0103] Step S306: input the standard temperature into the available capacity gain thermal characteristic model, and calculate the target battery available capacity gain.

[0104] In the embodiment of the present application, the standard temperature T = 25 degrees Celsius or T = 298 Kelvin is substituted into the available capacity gain thermal characteristic model K2(T) = a2T 2 +b2T+c2, the target battery available capacity gain can be calculated. For example, the available capacity gain thermal characteristic model of the sample battery matching the target battery is K2(T)=AT 2 +BT+C, then substitute the standard temperature T = 25 degrees Celsius or T = 298 Kelvin into K2(T) = AT 2 +BT+C, the target battery available capacity gain at standard temperature is calculated as K2(25℃)=AT 2 +BT+C.

[0105] Step S307: Determine the battery health of the target battery according to the available capacity gain of the target battery.

[0106] For example, the target battery available capacity gain at standard temperature is K2(25°C)=AT 2 +BT+C, then K2(25°C)*100% can be determined as the battery health of the target battery. For example, if the target battery available capacity gain at standard temperature is K2(25°C)=0.9, then the battery health of the target battery can be determined as 90%.

[0107] In an embodiment of the present application, the actual available capacity gain of the sample battery is calibrated in temperature through the available capacity gain thermal characteristic model, which can eliminate the influence of temperature on the measurement value of the current sensor and the maximum available capacity of the battery. The target battery available capacity gain at the standard temperature is determined as the battery health of the target battery, which can eliminate the influence of the accuracy of the current sensor on the battery health calculation result, thereby improving the accuracy of the determination of the battery health.

[0108] Example 4

[0109] Figure 4 This is a structural diagram of the battery health determination device provided in the fourth embodiment of the present application. The battery health determination device provided in the embodiment of the present application can execute the processing flow provided in the embodiment of the battery health determination method. Figure 4 As shown, the battery health determination device 40 includes: a determination module 401 , an acquisition module 402 and a calculation module 403 .

[0110] Specifically, the determination module 401 is used to determine the production batch and usage level of the target battery.

[0111] An acquisition module 402 is configured to acquire a thermal characteristic model of available capacity gain corresponding to a matching sample battery based on the production batch and usage level of the target battery. The thermal characteristic model of available capacity gain is a model that calibrates the actual available capacity gain of the sample battery over temperature.

[0112] A calculation module 403 is used to input the standard temperature into the available capacity gain thermal characteristic model and calculate the target battery available capacity gain;

[0113] The determination module 401 is further configured to determine the battery health of the target battery according to the available capacity gain of the target battery.

[0114] The device provided in the embodiment of the present application can be specifically used to execute the method embodiment provided in the above-mentioned embodiment 1, and the specific functions will not be repeated here.

[0115] Optionally, before the acquisition module 402 acquires the thermal characteristic model of the available capacity gain corresponding to the matching sample battery according to the production batch and usage level of the target battery, the acquisition module 402 is further used to: acquire the thermal characteristic model of the available capacity gain of the initial sample battery; the thermal characteristic model of the available capacity gain of the initial sample battery includes at least one first fitting parameter; and acquire charge and discharge data of at least one batch of sample batteries, wherein the usage level of each batch of sample batteries is within a preset range.

[0116] The calculation module 403 is further configured to calculate, for each batch of sample batteries, a first fitting parameter in the thermal characteristic model of the available capacity gain of the initial sample batteries based on the charge and discharge data, so as to obtain a thermal characteristic model of the available capacity gain of the sample batteries that matches the sample batteries.

[0117] Optionally, the acquisition module 402 is specifically used to perform the following operations for each batch of sample batteries: obtain the rated capacity of the sample battery at a standard temperature; obtain the discharge depth and ambient temperature of the sample battery; perform a charging operation or a discharging operation on the sample battery to obtain a current value through a current sensor; integrate the current over time according to the current value, and determine the current integration result as the chargeable capacity or dischargeable capacity of the sample battery; determine the discharge depth, ambient temperature, the rated capacity of the sample battery at a standard temperature, and the chargeable capacity or dischargeable capacity as charge and discharge data.

[0118] Optionally, the calculation module 403 includes: an acquisition unit and a fitting unit. The acquisition unit is used to: for each batch of sample batteries, obtain a relationship between the actual maximum available capacity and the measured available capacity of the sample battery; and obtain a thermal characteristic model of the initial current sensor sampling accuracy gain.

[0119] The fitting unit is used to: input the thermal characteristic model of the available capacity gain of the initial sample battery and the thermal characteristic model of the initial current sensor sampling accuracy gain into the relationship formula, the actual maximum available capacity of the sample battery is represented by the thermal characteristic model of the available capacity gain of the initial sample battery, and the measured available capacity is represented by the thermal characteristic model of the chargeable capacity or the dischargeable capacity and the initial current sensor sampling accuracy gain; the thermal characteristic model of the initial current sensor sampling accuracy gain includes at least one second fitting parameter; the charging and discharging data of each batch of sample batteries are input into the relationship formula, and the first fitting parameter is fitted to calculate the fitting parameter.

[0120] Optionally, the relationship between the actual maximum available capacity and the measured available capacity of the sample battery is expressed as:

[0121] C1(T)=DOD test C2(T), C1(T)=K1(T)∫I r dt; C2(T)=K2(T)C nom ; Where C1(T) is the measured available capacity, C2(T) is the actual maximum available capacity of the sample battery, and DOD test is the depth of discharge, K1(T) is the thermal characteristic model of the initial sample battery available capacity gain, K2(T) is the thermal characteristic model of the initial current sensor sampling accuracy gain, ∫I r dt is the chargeable or dischargeable capacity, C nom is the rated capacity of the sample battery at standard temperature, and T is the ambient temperature.

[0122] Optionally, the fitting unit is specifically configured to fit the first fitting parameter using one of a least squares method, a traditional optimization algorithm, and an intelligent optimization algorithm to calculate the first fitting parameter.

[0123] Optionally, the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in polynomial form; or the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in Arrhenius formula form.

[0124] Optionally, the battery health determination device 40 also includes a sending module. After the determination module 401 determines the battery health of the target battery based on the target battery available capacity gain, the sending module is used to: if the battery health is determined to be in an abnormal state, send target battery aging prompt information to the user terminal.

[0125] The device provided in the embodiment of the present application can be specifically used to execute the above method embodiment, and the specific functions will not be repeated here.

[0126] Example 5

[0127] Figure 5 This is a schematic diagram of the structure of the electronic device provided in Example 5 of this application. Figure 5 As shown, the electronic device 50 includes: a processor 501 and a memory 502 communicatively connected to the processor 501.

[0128] Among them, the circuits between the processor 501 and the memory 502 are interconnected; the memory 502 stores computer-executable instructions; the processor 501 executes the computer-executable instructions stored in the memory to implement the battery health determination method provided in any of the above embodiments.

[0129] An embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the battery health determination method provided by any of the above method embodiments is implemented.

[0130] An embodiment of the present application also provides a computer program product, which includes: computer execution instructions, which are stored in a readable storage medium. At least one processor of the electronic device can read the computer execution instructions from the readable storage medium, and at least one processor executes the computer execution instructions so that the electronic device executes the battery health determination method provided by any of the above method embodiments.

[0131] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0132] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0133] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining battery health, characterized in that: include: Determine the production batch and usage level of the target battery; Obtaining a thermal characteristic model of available capacity gain corresponding to a matching sample battery according to the production batch and usage level of the target battery, wherein the thermal characteristic model of available capacity gain is a model that calibrates the actual available capacity gain of the sample battery in terms of temperature; Inputting the standard temperature into the available capacity gain thermal characteristic model and calculating the target battery available capacity gain; Determining a battery health of the target battery according to the available capacity gain of the target battery; Before obtaining the available capacity gain thermal characteristic model corresponding to the matched sample battery according to the production batch and usage level of the target battery, the method further includes: Obtaining a thermal characteristic model of an initial sample battery available capacity gain; wherein the thermal characteristic model of the initial sample battery available capacity gain includes at least one first fitting parameter; Obtaining charge and discharge data of at least one batch of sample batteries, wherein the usage level of each batch of sample batteries is within a preset range; For each batch of sample batteries, obtaining a relationship between the actual maximum available capacity and the measured available capacity of the sample batteries; Obtaining a thermal characteristic model of the initial current sensor sampling accuracy gain; Inputting a thermal characteristic model of the available capacity gain of the initial sample battery and a thermal characteristic model of the initial current sensor sampling accuracy gain into the relationship, the actual maximum available capacity of the sample battery is represented by the thermal characteristic model of the available capacity gain of the initial sample battery, and the measured available capacity is represented by the thermal characteristic model of the chargeable or dischargeable capacity and the initial current sensor sampling accuracy gain; the thermal characteristic model of the initial current sensor sampling accuracy gain includes at least one second fitting parameter; Inputting the charge and discharge data of each batch of sample batteries into the relationship equation, fitting the first fitting parameters to calculate the fitting parameters, and obtaining a thermal characteristic model of the available capacity gain of the sample batteries that matches the sample batteries; The relationship is expressed as: , ; ; in, The available capacity for said measurement, is the actual maximum available capacity of the sample battery, is the depth of discharge, The thermal characteristic model for the available capacity gain of the initial sample battery is: is the thermal characteristic model of the initial current sensor sampling accuracy gain, is the chargeable amount or the dischargeable amount, is the rated capacity of the sample battery at standard temperature, and T is the ambient temperature.

2. The method according to claim 1, characterized in that The obtaining of charge and discharge data of at least one batch of sample batteries includes: For each batch of sample batteries, perform the following: Obtaining the rated capacity of the sample battery at a standard temperature; Obtaining the discharge depth and ambient temperature of the sample battery; performing a charging operation or a discharging operation on the sample battery to obtain a current value through a current sensor; performing current integration over time according to the current value, and determining the current integration result as the chargeable capacity or dischargeable capacity of the sample battery; The depth of discharge, the ambient temperature, the rated capacity of the sample battery at the standard temperature, the chargeable amount of electricity or the dischargeable amount of electricity are determined as the charge and discharge data.

3. The method according to claim 1, characterized in that The fitting of the first fitting parameter to calculate the fitting parameter includes: The first fitting parameter is fitted by using one of a least squares method, a traditional optimization algorithm, and an intelligent optimization algorithm to calculate the first fitting parameter.

4. The method according to claim 1, wherein The thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in polynomial form; Alternatively, the thermal characteristic model of the initial sample battery available capacity gain and the thermal characteristic model of the initial current sensor sampling accuracy gain are in the form of Arrhenius formulas.

5. The method according to any one of claims 1 to 4, characterized in that After determining the battery health of the target battery according to the target battery available capacity gain, the method further includes: If it is determined that the battery health is in an abnormal state, target battery aging prompt information is sent to the user terminal.

6. A device for determining battery health, characterized in that: include: A determination module, used to determine the production batch and usage level of the target battery; an acquisition module, configured to acquire, based on the production batch and usage level of the target battery, an available capacity gain thermal characteristic model corresponding to a matching sample battery, wherein the available capacity gain thermal characteristic model is a model for calibrating the actual available capacity gain of the sample battery in terms of temperature; a calculation module, configured to input a standard temperature into the available capacity gain thermal characteristic model and calculate a target battery available capacity gain; a determination module, further configured to determine the battery health of the target battery according to the available capacity gain of the target battery; Before the acquisition module acquires the available capacity gain thermal characteristic model corresponding to the matched sample battery according to the production batch and usage level of the target battery, the acquisition module is further configured to: acquire the thermal characteristic model of the available capacity gain of the initial sample battery; the thermal characteristic model of the available capacity gain of the initial sample battery includes at least one first fitting parameter; Obtaining charge and discharge data of at least one batch of sample batteries, wherein the usage level of each batch of sample batteries is within a preset range; The calculation module includes: an acquisition unit and a fitting unit; The obtaining unit is used to obtain, for each batch of sample batteries, a relationship between the actual maximum available capacity and the measured available capacity of the sample batteries; Obtaining a thermal characteristic model of the initial current sensor sampling accuracy gain; The fitting unit is configured to input a thermal characteristic model of the available capacity gain of the initial sample battery and a thermal characteristic model of the sampling accuracy gain of the initial current sensor into the relationship, wherein the actual maximum available capacity of the sample battery is represented by the thermal characteristic model of the available capacity gain of the initial sample battery, and the measured available capacity is represented by the thermal characteristic model of the chargeable or dischargeable capacity and the sampling accuracy gain of the initial current sensor; the thermal characteristic model of the sampling accuracy gain of the initial current sensor includes at least one second fitting parameter; Inputting the charge and discharge data of each batch of sample batteries into the relationship equation, fitting the first fitting parameters to calculate the fitting parameters, and obtaining a thermal characteristic model of the available capacity gain of the sample batteries that matches the sample batteries; The relationship is expressed as: , ; ; in, The available capacity for said measurement, is the actual maximum available capacity of the sample battery, is the depth of discharge, The thermal characteristic model for the available capacity gain of the initial sample battery is: is the thermal characteristic model of the initial current sensor sampling accuracy gain, is the chargeable amount or the dischargeable amount, is the rated capacity of the sample battery at standard temperature, and T is the ambient temperature.

7. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The processor and the memory are interconnected by circuits; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 5 when executed by a processor.

9. A computer program product, characterized in that The method comprises computer-executable instructions, which implement the method according to any one of claims 1 to 5 when executed by a processor.

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