WO2024031261A1

WO2024031261A1 - Battery testing method, apparatus, device, storage medium and program product

Info

Publication number: WO2024031261A1
Application number: PCT/CN2022/110933
Authority: WO
Inventors: 左启琪; 李伟
Original assignee: 宁德时代新能源科技股份有限公司
Priority date: 2022-08-08
Filing date: 2022-08-08
Publication date: 2024-02-15

Abstract

The present application provides a battery testing method, an apparatus, a device, a storage medium and a program product. The battery testing method comprises: acquiring charging data of a tested battery during a formation process, the charging data comprises a voltage value and a corresponding power value; according to the charging data of the tested battery, determining a test voltage interval and the measured value of the tested battery; and according to the measured value and a standard value, judging whether the tested battery is normal. Therefore, by using the testing method, the performance of batteries can be tested by means of the charging data during the formation process before a standing process and a test process in battery manufacturing, so as to screen out unqualified batteries in advance, thus the batteries do not need to be placed for a period of time, helping to shorten the test time and the test cycles of the batteries.

Description

Battery testing methods, devices, equipment, storage media and program products

Technical field

The present application relates to the field of battery technology, and in particular to a battery detection method, device, equipment, storage medium and program product.

Background technique

Energy conservation and emission reduction are the key to the sustainable development of the automobile industry. Electric vehicles have become an important part of the sustainable development of the automobile industry due to their advantages in energy conservation and environmental protection. For electric vehicles, battery technology is an important factor related to their development.

The manufactured batteries must be tested before leaving the factory to screen out unqualified batteries. In the related art, the manufactured battery is usually left aside for a period of time, and then the battery's power or K value and other parameters are monitored to test whether the battery is normal. However, it takes a long time to test whether the battery is qualified in this way, and the test cycle is long.

Contents of the invention

This application aims to solve at least one of the technical problems existing in the prior art. To this end, one purpose of this application is to propose a battery detection method, device, equipment, storage medium and program product to solve the problem that it takes a long time to test whether the battery is qualified and the test cycle is long.

An embodiment of the first aspect of the present application provides a battery detection method, which includes: obtaining charging data of the battery under test in the formation process; wherein the charging data includes a voltage value and a corresponding power value; according to the charging data of the battery under test, Determine the test voltage range and measured value of the battery under test; judge whether the battery under test is normal based on the measured value and standard value.

In the technical solution of the embodiment of the present application, this detection method can be used to test the performance of the battery with the help of the charging data of the formation process before the resting process and testing process of battery manufacturing, so as to screen out unqualified batteries in advance. In this way, no need Putting the battery aside for a period of time will help shorten the test time and test cycle of the battery, improve the test efficiency, and in turn help relieve the pressure on the battery manufacturer's storage space and cash flow.

Moreover, since the formation process is a necessary processing step for every battery, using this detection method to test the performance of the battery can make full use of the data from the formation process and improve the utilization of the charging data from the formation process. In addition, the method of testing the performance of the battery by shelving it is often only a random inspection of the battery. Using the detection method of this embodiment, each battery can be tested for performance using its charging data in the formation process, thereby achieving full battery performance. The effect of inspection is that each battery can be tested for performance, which is helpful to avoid unqualified batteries from leaving the factory.

In some embodiments, the measured value is the test power difference, and the test power difference is the difference in power value when the battery under test is charged from the first endpoint voltage value of the test voltage interval to the second endpoint voltage value of the test voltage interval, The standard value is the standard deviation value of the power value of the reference battery when it is charged from the first endpoint voltage value of the test voltage interval to the second endpoint voltage value of the test voltage interval. The detection method of this embodiment can use the charging data of the battery under test in the formation process to calculate the test power difference of the battery under test, and then based on the test power difference and the standard power difference, it can be identified whether the battery under test is different from the reference battery, and then Unqualified batteries under test can be screened out.

In some embodiments, the measured value is the total charging current of the battery under test, and the standard value is the total charging current of the reference battery. Use the charging data of the battery under test in the formation process to calculate the total charging current of the battery under test, and then based on the total charging current of the battery under test and the total charging current of the reference battery, you can identify whether the battery under test is different from the reference battery, and then Unqualified batteries under test can be screened out. Compared with using the power difference to detect whether the battery is qualified, the total charging current of the battery under test can better reflect the short circuit condition inside the battery under test, and the detection effect is better.

In some embodiments, judging whether the battery under test is normal based on the measured value and the standard value includes: calculating the self-discharge current of the battery under test based on the measured value and the standard value; summing the self-discharge current of the battery under test and The comparison result is obtained by comparing the self-discharge current threshold, and based on the comparison result, it is judged whether the battery under test is normal. By calculating the self-discharge current of the battery under test and screening out unqualified batteries accordingly, the self-discharge current of the battery under test can be intuitively understood.

In some embodiments, before comparing the self-discharge current of the tested battery with the self-discharge current threshold to obtain a comparison result, and before determining whether the tested battery is normal based on the comparison result, the method further includes: obtaining the self-discharge currents of multiple tested batteries; The self-discharge current threshold is determined based on the distribution of self-discharge currents of multiple tested batteries. The self-discharge current threshold is determined based on the distribution of the self-discharge current of the battery under test. The value of the self-discharge current used to evaluate battery performance is a range, not a single value, which is beneficial to improving the accuracy and rationality of battery screening. .

In some embodiments, after comparing the self-discharge current of the battery under test with the self-discharge current threshold to obtain a comparison result, and determining whether the battery under test is normal based on the comparison result, the method further includes: based on the self-discharge current of the reference battery, evaluating the self-discharge The current threshold is corrected. With this design, the self-discharge current threshold is designed not only by considering the distribution of the self-discharge current of the battery under test, but also by considering the self-discharge current of the reference battery, in order to improve the accuracy of the self-discharge current threshold.

In some embodiments, before determining whether the battery under test is normal based on the measured value and the standard value, it also includes: obtaining the charging data of the reference battery in the formation process; calculating the standard value based on the test voltage interval and the charging data of the reference battery. . The standard value is calculated based on the actual charging data of the reference battery in the formation process. In this way, the standard value is not prone to errors and the design is reasonable.

In some embodiments, determining the test voltage range of the battery under test according to the charging data of the battery under test includes: fitting according to the charging data of the battery under test to generate a formation curve of the battery under test; wherein the formation curve includes the formation curve of the battery under test. The voltage value of the battery under test and the corresponding power value; determine the test voltage range based on the slope of each point on the formation curve of the battery under test. A formation curve is established based on the charging data of the battery under test, and the test voltage range is determined based on the changes in the slope of each point on the formation curve. This fully takes into account the changing characteristics of the formation curve, which is beneficial to improving test accuracy.

A second embodiment of the present application provides a battery detection device. The battery detection device includes: a data acquisition module, a determination module and a judgment module. Among them, the data acquisition module is used to obtain the charging data of the battery under test in the formation process; the charging data includes the voltage value and the corresponding power value; the determination module is used to determine the test voltage of the battery under test based on the charging data of the battery under test. interval and measured value; the judgment module is used to judge whether the battery under test is normal based on the measured value and the standard value.

In some embodiments, the measured value is the test power difference, and the test power difference is the difference in power value when the battery under test is charged from the first endpoint voltage value of the test voltage interval to the second endpoint voltage value of the test voltage interval, The standard value is the standard deviation value of the power value of the reference battery when it is charged from the first endpoint voltage value of the test voltage interval to the second endpoint voltage value of the test voltage interval.

In some embodiments, the measured value is the total charging current of the battery under test, and the standard value is the total charging current of the reference battery.

In some embodiments, the judgment module is further configured to calculate the self-discharge current of the battery under test based on the measured value and the standard value; compare the self-discharge current of the battery under test with the self-discharge current threshold to obtain a comparison result. The result determines whether the battery under test is normal.

In some embodiments, the data acquisition module is further configured to obtain the comparison results of the self-discharge current of the battery under test and the self-discharge current threshold, and determine whether the battery under test is normal based on the comparison result. Self-discharge current; the determining module is further configured to determine the self-discharge current threshold according to the distribution of self-discharge currents of the plurality of tested batteries.

In some embodiments, the battery detection device also includes a correction module. The correction module is used to compare the self-discharge current of the tested battery with the self-discharge current threshold to obtain a comparison result, and then determine whether the tested battery is normal based on the comparison result. The self-discharge current threshold is corrected based on the self-discharge current of the reference battery.

In some embodiments, the data acquisition module is further configured to obtain the charging data of the reference battery in the formation process before determining whether the battery under test is normal based on the measured value and the standard value; the determination module is further configured to obtain charging data based on the test voltage interval. And the charging data of the reference battery to calculate the standard value.

In some embodiments, the determination module is further configured to perform fitting according to the charging data of the battery under test and generate a formation curve of the battery under test; wherein the formation curve includes the voltage value and the corresponding power value of the battery under test; according to the Measure the slope of each point on the battery's formation curve to determine the test voltage range.

The embodiment of the third aspect of the present application provides an electronic device, including a memory and a processor. The memory stores a computer program; the processor executes the computer program stored in the memory, so that the electronic device executes the battery detection method described in the first aspect. .

The embodiment of the fourth aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when executed by the processor, the computer program is used to implement the detection of the battery as described in the first aspect. method.

The embodiment of the fifth aspect of the present application provides a computer program product, wherein the computer program product is a computer program. When the computer program is executed by a processor, it is used to implement the battery detection method described in the first aspect.

The above description is only an overview of the technical solutions of the present application. In order to have a clearer understanding of the technical means of the present application, they can be implemented according to the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and understandable. , the specific implementation methods of the present application are specifically listed below.

Description of drawings

In the drawings, unless otherwise specified, the same reference numbers refer to the same or similar parts or elements throughout the several figures. The drawings are not necessarily to scale. It should be understood that these drawings depict only some embodiments disclosed in accordance with the present application and should not be considered as limiting the scope of the present application.

Figure 1 is a schematic flow chart of a battery detection method according to some embodiments of the present application;

Figure 2 is a schematic diagram of battery formation according to an embodiment of the present application;

Figure 3 is a schematic circuit diagram of the battery during charging according to some embodiments of the present application;

Figure 4a is a schematic diagram of the charging principle of a normal battery;

Figure 4b is a schematic diagram of the charging principle of an abnormal battery with internal short circuit;

Figure 5 is a schematic diagram of the voltage-electricity relationship curve of a normal battery and an abnormal battery;

Figure 6 is a schematic flowchart of a modified example of the method shown in Figure 1;

Figure 7 is a scatter diagram of the self-discharge current of the battery under test in the battery detection method according to some embodiments of the present application;

Figure 8 shows the normal distribution diagram of the self-discharge current of the reference battery.

Figure 9 is a schematic diagram of the formation curve of the tested battery according to some embodiments of the present application;

Figure 10 is a schematic diagram of the voltage charging time relationship curve of a normal battery and an abnormal battery;

Figure 11 is a schematic flow chart of a battery detection method according to other embodiments of the present application;

Figure 12 is a schematic flowchart of a modified example of the method shown in Figure 11;

Figure 13 is a schematic diagram of a first relationship curve of a battery according to some embodiments of the present application;

Figure 14 is a schematic flowchart of a battery detection method according to some embodiments of the present application;

Figure 15 is a schematic structural diagram of a battery detection device according to some embodiments of the present application;

Figure 16 is a schematic structural diagram of an electronic device according to some embodiments of the present application.

Detailed ways

The embodiments of the technical solution of the present application will be described in detail below with reference to the accompanying drawings. The following examples are only used to illustrate the technical solution of the present application more clearly, and are therefore only used as examples and cannot be used to limit the protection scope of the present application.

Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the technical field belonging to this application; the terms used herein are for the purpose of describing specific embodiments only and are not intended to be used in Limitation of this application; the terms "including" and "having" and any variations thereof in the description and claims of this application and the above description of the drawings are intended to cover non-exclusive inclusion.

In the description of the embodiments of this application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying the relative importance or implicitly indicating the quantity or specificity of the indicated technical features. Sequence or priority relationship. In the description of the embodiments of this application, "plurality" means two or more, unless otherwise explicitly and specifically limited.

Reference herein to "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.

In the description of the embodiments of this application, the term "and/or" is only an association relationship describing associated objects, indicating that there can be three relationships, such as A and/or B, which can mean: A exists alone, and A exists simultaneously and B, there are three cases of B alone. In addition, the character "/" in this article generally indicates that the related objects are an "or" relationship.

In the description of the embodiments of this application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to two or more groups (including two groups), and "multiple pieces" refers to It is more than two pieces (including two pieces).

In the description of the embodiments of this application, the technical terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "back" , "Left", "Right", "Vertical", "Horizontal", "Top", "Bottom", "Inside", "Outside", "Clockwise", "Counterclockwise", "Axis", " The orientations or positional relationships indicated by "radial", "circumferential", etc. are based on the orientations or positional relationships shown in the drawings. They are only for the convenience of describing the embodiments of the present application and simplifying the description, and are not intended to indicate or imply the devices or devices referred to. Elements must have a specific orientation, be constructed and operate in a specific orientation, and therefore are not to be construed as limitations on the embodiments of the present application.

In the description of the embodiments of this application, unless otherwise explicitly stated and limited, technical terms such as "installation", "connection", "connection", and "fixing" should be understood in a broad sense. For example, it can be a fixed connection or a fixed connection. It can be detachably connected or integrated; it can also be mechanically connected or electrically connected; it can be directly connected or indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction between two elements. . For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of this application can be understood according to specific circumstances.

Power batteries are widely used in fields such as mobile devices and electric vehicles. Power batteries need to be tested before leaving the factory to screen out batteries that fail in self-discharge, thereby ensuring that all batteries leaving the factory have excellent performance.

Referring to Figures 4a and 4b below, the cell of the battery includes a positive electrode piece 210, a negative electrode piece 220, a separator 230 and an electrolyte 240. During the cell manufacturing process, impurities are mixed into the interior of the cell, and some of the impurities can conduct electricity. The positive electrode piece 210 and the negative electrode piece 220 will cause a short circuit inside the battery cell. In this way, even if the battery is not connected to a load, the short circuit will consume the battery's power, causing the battery's power to decrease. In other words, if a power battery in an open circuit state is left at a certain temperature for a period of time, its power will decrease. This phenomenon is called the self-discharge phenomenon of the battery. Based on this, although there are many methods used to characterize the self-discharge performance of batteries in related technologies, the general idea is to leave the manufactured battery aside for a period of time and monitor the parameter changes during the battery placement process.

For example, taking the K value to characterize the self-discharge performance of a battery as an example, in the related art, the test steps of the method of detecting the K value of the battery are usually: charging the battery to a fixed capacity C, completing the formation process; Leave it for a period of time to age the battery and achieve depolarization; the voltage of the tested battery after t1 is U1, and the voltage of the tested battery after t2 is U2, where t1＜t2, U1＜U2; calculate the K value, K Value = (U1-U2)/(t2-t1); and then detect the self-discharge performance of the battery according to the K value to screen out unqualified batteries with serious self-discharge.

The researchers of this application found that when testing the performance of the battery, it is usually necessary to put the battery aside for a long period of time to test the parameter changes when the battery is discharged during the standing process, resulting in a longer battery performance test time, a long test cycle, and test low efficiency. This further poses greater challenges to battery manufacturers’ storage space and cash flow.

In response to the above problems, the researchers of this application thought that there are also differences in the parameters of normal batteries and abnormal batteries during the charging process. By detecting the parameters of the battery charging process, the performance of the battery can also be tested to detect whether the battery is qualified. Inspired by this technical concept, the researchers of this application finally designed a battery detection method and detection device. This method relies on the charging data of the battery during the formation process to determine whether the battery is normal. Since the formation process is Each battery must go through a processing process, so this can make full use of the data during formation, saving storage time, which in turn helps shorten the test time.

The battery detection method and device disclosed in the embodiments of the present application can be applied to the battery manufacturing process, and specifically can be applied to the later processes of battery manufacturing. The battery here is not limited to lithium-ion batteries, but can also refer to other types of batteries such as lead-acid batteries and nickel-cadmium batteries. It should be noted that the battery can be used as a power source for the electrical device to provide power to the electrical device. Among them, the electrical devices can be but are not limited to mobile phones, tablets, laptops, electric toys, power tools, battery cars, electric vehicles, ships, spacecraft, etc. Electric toys can include fixed or mobile electric toys, such as game consoles, electric car toys, electric ship toys, electric airplane toys, etc. Spacecraft can include airplanes, rockets, space shuttles, spaceships, etc.

The execution subject of the battery detection method provided by the embodiment of the present application may be a battery detection device, or may be an electronic device capable of controlling the battery detection device, such as a server or terminal equipment. The following embodiments take a battery detection device as an example for schematic description.

The embodiment of the present application provides a battery detection method. The method is used to test whether the battery is normal. According to the detection results of the method, batteries with unqualified performance can be screened out. The battery detection method obtains the charging data of the battery under test during the formation process, and determines whether the battery under test is normal based on the charging data of the battery under test. Among them, the battery under test refers to the battery that is newly manufactured and to be tested. The model and type of the battery under test are not limited.

It is worth noting that since the battery detection method in this embodiment uses the charging data of the battery under test during the formation process, the detection method can be implemented after the formation process of the battery manufacturing process.

The battery detection method provided by some embodiments of the present application is described below with reference to the accompanying drawings.

Figure 1 is a schematic flowchart of a battery detection method according to some embodiments of the present application. In the example shown in Figure 1, the method includes the following steps S101 to S103.

Step S101: Obtain the charging data of the battery under test in the formation process; the charging data includes voltage values and corresponding power values.

Step S102: Determine the test voltage range and measured value of the battery under test based on the charging data of the battery under test.

Step S103: Determine whether the battery under test is normal based on the measured value and the standard value.

The formation process is also called activation. It is the process of charging a newly produced and packaged battery for the first time to activate the active materials inside the battery. The battery can be used normally only after the active materials inside the battery are activated. Therefore, the formation process is an indispensable link in the production and manufacturing process of each battery.

FIG. 2 is a schematic diagram of the formation of a battery 200 according to some embodiments of the present application. Referring to FIG. 2 , the specific implementation method of the formation process may be: using the power supply 110 to charge the battery 200 so that the power of the battery 200 reaches a preset power. Specifically, for example, as shown in FIG. 3 , the battery 200 is equivalent to a capacitor. Both ends of the capacitor are connected to the positive and negative poles of the power supply 110 respectively. A charging circuit 120 is connected between the power supply 110 and the capacitor. The charging circuit 120 can regulate and control the power supply. 110 supplies the voltage to the capacitor. When the circuit between the capacitor and the power supply 110 is turned on, current flows through the circuit between the capacitor and the power supply 110, causing the capacitor's power to continuously increase. That is to say, the voltage value of the battery 200 continues to increase, and accordingly, the power value of the battery 200 also continues to increase, until the voltage value of the battery 200 increases to the same voltage value as the voltage value of the power supply 110 . Among them, FIG. 3 is a schematic circuit diagram of the battery 200 during charging according to some embodiments of the present application. It should be noted that during the formation process, the power supply 110 can specifically provide a constant current to charge the battery 200 with a constant current.

Furthermore, as shown in FIG. 2 , a detection circuit 130 may also be connected between the power supply 110 and the battery 200 . In this way, step S101 can obtain charging data by obtaining the data detected by the detection circuit 130 . In this example, the charging data may include the voltage value U (unit: V) of the battery 200 and the power value Q (unit: mA·h) of the battery 200. As shown in FIG. 3 , the detection circuit 130 at this time may include a voltmeter. 131 and the power detector 132. The voltmeter 131 is connected in parallel with the capacitor to detect the voltage value of the capacitor. The power detector 132 uses the Coulomb detection method to detect the power value of the battery 200, in which the resistor R1 is the internal resistance of the power detector 132. Of course, in other embodiments, the voltmeter 131 can also be replaced by other voltage sensors.

It can be understood that the voltage value U of the battery 200 and the power value Q of the battery 200 are in one-to-one correspondence. Because the voltage value and power value of the battery 200 increase with the charging time, the detection circuit 130 can Multiple sets of charging data detected. In this way, multiple sets of charging data of the battery 200 under test can be obtained in step S101, and each set of charging data can be (U, Q). For example, if the voltage value of power supply 110 is 4.2V, the obtained charging data of the battery under test may include (2V, 6734.3mA·h), (3.2V, 20038.4mA·h), (4V, 35205.1mA·h). h) etc.

On the basis of step S101, step S102 is to select the first endpoint voltage value U _C1 and the second endpoint voltage value U _C2 from the charging data of the battery under test as the endpoints of the test voltage interval, where, U _C1 < _UC2 , Then the test voltage interval is ( _UC1 , U _C2 ). For example, if the voltage value of the power supply 110 is 4.2V, the test voltage range of a battery under test may be (1.8V, 3V), (2V, 3.2V) or (2.5V, 4V). Moreover, while determining the test voltage interval, the measured value can also be determined based on the voltage value U of the battery 200 and the electric quantity value Q of the battery 200 .

The standard value in step S103 can be understood as the value corresponding to the measured value of the reference battery. Here, the reference battery refers to a battery that has passed the test and is determined to be a normal battery, and the model and type are consistent with the battery under test. The reference battery is formed The charging parameters of the process (such as charging current or charging voltage) are still the same as the charging parameters of the battery under test in the formation process. Designed in this way, the purpose of step S103 is to compare the measured value of the battery under test with the measured value of the reference battery to determine whether the battery under test is normal.

In summary, by detecting the battery under test according to the detection method provided in this embodiment, it can be determined whether the battery under test is normal, and then abnormal batteries can be screened out.

In the related art, the process flow of the battery 200 is the sealing process, the formation process, the resting process, the testing process, and the capacity dividing process. That is, the battery 200 is first put aside and then the discharge parameters of the battery 200 are detected to test the performance of the battery 200. This embodiment uses the charging data of the battery 200 during the formation process to determine the performance of the battery 200 . Therefore, the detection method provided by this embodiment can be executed after the formation process and before the resting process. Designed in this way, the detection method can be used to test the performance of the battery 200 using the charging data of the formation process before the resting process and the testing process, so as to screen out unqualified batteries 200 in advance. In this way, there is no need to leave the battery 200 aside for a period of time. It is conducive to shortening the test time and test cycle of the battery 200 and improving the test efficiency, which is conducive to easing the pressure on the storage space and cash flow of the battery 200 manufacturer.

Moreover, since the formation process is a necessary processing step for each battery 200, using this detection method to test the performance of the battery 200 can fully utilize the data of the formation process and improve the utilization rate of the charging data of the formation process. In addition, the method of testing the performance of the battery 200 by leaving it aside often only involves random inspection of the battery 200. Using the detection method of this embodiment, each battery 200 can be tested for performance using its charging data in the formation process, and thus can The effect of full battery inspection is achieved, that is, each battery 200 can be tested for performance, which is helpful to avoid unqualified batteries 200 from leaving the factory.

In an implementable manner, the measured value can be the test power difference ΔQ _C ; where the test power difference ΔQ _C is the charge of the battery under test from the first endpoint voltage value U _C1 of the test voltage interval to the second endpoint voltage. The difference between the electric quantity value Q at the value U _C2 .

Figure 4a is a schematic diagram of the charging principle of a normal battery, and Figure 4b is a schematic diagram of the charging principle of an abnormal battery with an internal short circuit. Referring to Figure 4a, if the battery 200 is normal, when the battery 200 is charging, the lithium ions Li ⁺ in the positive electrode of the battery move to the negative electrode of the battery through the separator 230. At the same time, the electrons e ^- in the positive electrode of the battery migrate to the negative electrode of the battery along the charging circuit 120. In this way, the electrons e ^- at the positive electrode of the battery decrease and the electrons e ^- at the negative electrode increase. A potential difference is formed between the positive electrode and the negative electrode of the battery. As the electrons e ^- move, the voltage of the battery 200 increases. Referring to Figure 4b, on the basis of the normal battery charging principle, if the battery 200 is internally short-circuited, the positive electrode and the negative electrode of the battery 200 will be slightly conductive and form a conductive loop 140. The conductive loop 140 is connected in parallel with the charging circuit 120. The electrons e ^- from the positive electrode of the battery migrate to the negative electrode of the battery along the charging circuit 120 , and part of the electrons e ^- from the negative electrode of the battery migrate to the positive electrode of the battery along the conduction loop 140 . Some of the lithium ions Li ⁺ embedded in the negative electrode of the battery are deintercalated and move to the battery through the separator 230 positive electrode. It can be seen that when an abnormal battery is internally short-circuited, there is a self-discharge phenomenon. When the battery 200 is being charged, a greater amount of electricity is charged into the battery 200 to compensate for the energy loss of the battery 200 due to self-discharge. Therefore, when the normal battery and the abnormal battery are charged to the same voltage value, the capacity value of the abnormal battery is higher than that of the normal battery.

Figure 5 is a schematic diagram of the voltage-electricity relationship curve of a normal battery and an abnormal battery. The charging data of the battery 200 is fitted to obtain a voltage-electricity relationship curve. The voltage-electricity relationship curve is used to represent the relationship between the electric quantity value of the battery 200 and the voltage change. It should be noted that the voltage-electricity relationship curve of a normal battery can be shown as the solid line in Figure 5, and the voltage-electricity relationship curve of an abnormal battery can be shown as the dotted line in Figure 5. Referring to Figure 5, it can be seen that when the voltage value of the normal battery is consistent with the voltage value of the abnormal battery, the power value of the normal battery is smaller than the power value of the abnormal battery; conversely, when the power value of the normal battery is consistent with the power value of the abnormal battery, the power value of the normal battery is The voltage value is greater than the voltage value of the abnormal battery.

Based on this difference, the voltage value of the battery under test is designed to be quantitative, and the measured value and the standard value are designed to be related to the power value. By comparing the measured value and the standard value, it can be judged whether the battery under test is normal.

It can be seen from Figure 5 that when charged to the same voltage value, the capacity values of normal batteries and abnormal batteries are different. Therefore, in some embodiments, the measured value may specifically be the electric quantity value corresponding to when the battery under test is charged to the target voltage value in the test voltage range. In this example, the standard value is the corresponding power value when the reference battery is charged to the target voltage value. If the measured value is different from the standard value, the battery under test can be considered abnormal. If the measured value is the same as the standard value, the battery under test can be considered normal.

Specifically, the target voltage value may be the first endpoint voltage value, the second endpoint voltage value, or any voltage value between the first endpoint voltage value and the second endpoint voltage value. When the charging data of the battery under test includes (2V, 6734.3mA·h), (3.2V, 20038.4mA·h), (4V, 35205.1mA·h), and the test voltage range is (2V, 3.2V), if the target If the voltage value can be the first endpoint voltage value, then the measured value can be determined to be 6734.3mA·h. If the target voltage value can be the second endpoint voltage value, then the measured value can be determined to be 20038.4mA·h.

Here, the standard value can be designed based on the charging data in the formation process of the benchmark battery that has been tested and determined. Moreover, the average value of the electric quantity values corresponding to multiple reference batteries charged to the target voltage value can be taken as the standard value. In this way, the standard value is designed with reference to the charging data of multiple reference batteries to improve the accuracy of the test.

It can be seen from Figure 5 that when charging from U _C1 to U _C2 , the power difference ΔQ of the normal battery is _different _from the power difference ΔQ of the abnormal battery. Therefore, in some embodiments, the measured value may be the test power difference ΔQ _C , and the test power difference ΔQ _C is when the battery under test is charged from the first endpoint voltage value U _C1 of the test voltage interval to the second endpoint voltage value U _C2 The difference in electric quantity value Q at that time, that is to say, the test electric quantity difference ΔQ _C is equal to the electric quantity value Q _C2 corresponding to the battery under test being charged to U _C2 minus the electric quantity value Q _C1 corresponding to charging to U _C1 . In this example, the standard value is the standard power difference ΔQ _B , and the standard power difference ΔQ _B is the standard deviation value of the power value Q when the reference battery is charged from _UC1 to _UC2 . Designed in this way, the battery detection method in this embodiment is by comparing the power difference ΔQ _C and the standard power difference ΔQ _B when the tested battery is charged from the first endpoint voltage value U _C1 to the second endpoint voltage value U _C2 . to determine whether the battery under test is normal. When ΔQ _C = ΔQ _B , the battery under test can be considered normal; when ΔQ _C ≠ ΔQ _B , the battery under test can be considered abnormal.

For example, when the charging data of the battery under test includes (2V, 6734.3mA·h), (3.2V, 20038.4mA·h), (4V, 35205.1mA·h), if the test voltage range is determined to be (2V, 3.2V ), then the test power difference ΔQ _C =20038.4mA·h-6734.3mA·h=13304.1mA·h.

Among them, the standard power difference ΔQ _B can be designed based on experience and actual working conditions. For example, when the test voltage range is (2V, 3.2V), the standard power difference ΔQ _B can be designed as 13304.1mA·h, 13600mA·h, 14000mA· h, etc., this embodiment does not limit this.

Since the positive and negative electrodes of the abnormal battery with internal short circuit are connected, the abnormal battery has self-discharge phenomenon. Therefore, the amount of electricity charged into the abnormal battery is greater than the amount of electricity charged into the normal battery to compensate for part of the self-discharge of the abnormal battery. Therefore, this implementation The detection method in this example uses the charging data of the battery under test in the formation process to calculate the test power difference of the battery under test. Based on the test power difference and the standard power difference, it can be identified whether the battery under test is different from the reference battery, and then it can be screened Unqualified batteries under test are produced.

Moreover, the difference in power between the normal battery charged from U _C1 to U _C2 and the difference in power between the abnormal battery charged from U _C1 to U _C2 are relatively large. In this embodiment, the measured value is designed to be the test power difference, which is different from the direct design. The measured value is compared with the corresponding power value when the battery under test is charged to the target voltage value, which helps avoid misjudgments and improves the accuracy of battery testing.

In another implementable manner, the measured value may be the total charging current I of the battery under _test . The total charging current refers to the total current on the circuit between the battery and the power supply 110 during the charging process.

It can be understood that, continuing to refer to Figure 4a, when the battery is charged normally, the lithium ions Li ⁺ on the positive electrode of the battery move to the negative electrode of the battery through the separator 230, converting the electrical energy into chemical energy. At the same time, the electrons ^e- on the positive electrode of the battery move along the The charging circuit 120 moves to the negative electrode of the battery, so that the circuit between the battery and the power source 110 forms a chemical current _Ichem . At this time, _Ichemistry is the total charging current _Itotal of the normal battery. Continuing to refer to Figure 4b, when an abnormal battery is charged, a short circuit is formed inside the battery, and the positive and negative electrodes of the battery are slightly connected to form a conductive loop 140. The conductive loop 140 is connected in parallel with the charging circuit 120, and the positive electrode plate 210 and the negative electrode plate are 220 and the electrolyte 240 have internal resistance, so the conduction loop 140 can be regarded as having a resistor R2 connected in series, and the electrons ^e at the positive electrode of the battery migrate from the positive electrode of the battery along the charging circuit 120 to the negative electrode of the battery to form a chemical current I _chemistry , the part of the negative electrode of the battery. The electrons e ^- migrate to the positive electrode of the battery along the conductive loop 140, and a self-discharge current I is _formed on the conductive loop 140. Since the conductive loop 140 is connected in parallel with the charging circuit 120, the total charging current I of the abnormal battery is _always equal to I _chemical and The sum of I _{self-discharge} . The self-discharge current I _{self-discharge} can be understood as the current input by the power supply 110 to compensate for the power consumed by the battery's self-discharge.

That is to say, on the basis of the same model, category, etc., the total charging current I of a normal battery _is _always different from the total charging current I of an abnormal battery. Based on this difference, in this embodiment, by designing the measured value to _be the total charging current I of the battery under test, and comparing the measured value with the standard value, it can also be determined whether the battery under test is normal. It should be understood that in this example, the standard value may be _the total charging current I of the reference battery.

According to I=Q/t, the method for determining the measured value (i.e., the total charging current I of the battery under _test ) in this embodiment is: _Itest =ΔQ _C / _ΔTC , where ΔQ _C can refer to the previous description The calculation is performed in a manner that will not be described in detail in this embodiment. _ΔTC refers to the charging time required for the battery under test to charge from the first endpoint voltage value U _C1 to the second endpoint voltage value U _C2 .

After _determining the measured value I, compare the _measured value I with the standard _value I. If the _measured value I is consistent with the standard _value I, the battery under test is judged to be normal. If the _measured value I is _inconsistent with the standard value I, the battery under test is judged to be abnormal.

The detection method in this embodiment is to use the charging data of the battery under test in the formation process to calculate the total charging current of the battery under test, and then based on the total charging current of the battery under test and the total charging current of the reference battery, the battery under test can be identified Whether it is different from the reference battery, and then the unqualified tested batteries can be screened out. Compared with using the power difference to detect whether the battery is qualified, the total charging current of the battery under test can better reflect the short circuit condition inside the battery under test, and the detection effect is better.

FIG. 6 is a schematic flowchart of a modified example of the method shown in FIG. 1 . Based on the above embodiment, as shown in Figure 6, when the measured value is the total charging current I of the battery under _test , step S103 may include the following implementation steps:

S1031. Calculate the self-discharge current of the battery under test based on the measured value and the standard value.

S1032: Compare the self-discharge current of the battery under test and the self-discharge current threshold to obtain a comparison result, and determine whether the battery under test is normal based on the comparison result.

Based on the above, it can be seen that on the basis of the same model, category, etc., the total charging current I of a normal battery is _always different _from the total charging current I of an abnormal battery. Moreover, when the model and type of the normal battery and the abnormal cell are the same, the chemical _current I formed by converting electrical energy into chemical energy when charging the normal battery is equal to the chemical current I formed by converting electrical energy into _chemical energy when charging the abnormal battery. Therefore, the difference between the total charging current _Itotal of the normal battery and the total charging current _Itoto of the abnormal battery is the self-discharge current _{Iself-discharge} . Therefore, this embodiment can also determine whether the battery under test is normal by calculating the self-discharge current _IC self-discharge of the battery under test and comparing the self-discharge current _{IC self-discharge} of the battery under test with the self-discharge current threshold.

In step S1031, the standard value is the total charging current I of the reference battery. _As a normal battery, the self-discharge current of the reference battery can be regarded as 0 mA. Then the total charging current I of the reference battery is _equal to the chemical current of the reference battery. Since the model and type of the reference battery and the battery under test are the same, the chemical current of the battery under test is equal to the chemical current of the reference battery. In general, the standard value = the total charging current of the reference battery I _standard = the chemical current of the reference battery = the chemical current of the tested battery. According to the total charging current I _total equal to the sum of I _chemical and I _{self-discharge} , the self-discharge current I _{C self-} _discharge of the battery under test is calculated as follows: I _{C self-discharge} = I _{measured total} - I _{standard total} .

The self-discharge current threshold in step S1032 can be understood as the self-discharge current I _{B self-discharge} of the reference battery. When the comparison result is that the self-discharge current of the battery under test I _{C self-discharge} is equal to the self-discharge current threshold I _{B self-discharge} , the battery under test can be judged to be normal. When the comparison result is that the self-discharge current of the battery under test I _{C self-discharge} is not equal to If the self-discharge current threshold I _{B self-discharges} , it can be judged that the battery under test is abnormal.

For example, in some embodiments, the reference battery can be regarded as having a self-discharge current of 0 mA, and the self-discharge current threshold can be designed to be 0 mA. In this embodiment, if the self-discharge current I _{C self-discharge} of the battery under test is calculated to be equal to 0 mA, then the battery under test can be judged to be normal. If the self-discharge current I _{C self-discharge of the battery under test is calculated not to be 0 mA, then it can be determined that the battery under test} is normal. Determine whether the battery under test is abnormal.

The detection method of this embodiment can be used to detect whether the performance of the battery under test is qualified, and is particularly suitable for detecting whether the self-discharge performance of the battery under test is qualified. Moreover, this detection method is to screen out unqualified batteries by calculating the self-discharge current I _C of the battery under test. In this way, you can intuitively understand whether there is self-discharge in the battery under test to detect the self-discharge phenomenon. Check whether the battery's self-discharge is serious. In addition, after calculating the self-discharge current I _{C of the battery under _test} , combined with the formula Q = I Discharge rate, the self-discharge rate of the battery under test can be used to define the specifications of the battery under test.

In addition to designing the self-discharge current threshold equal to 0mA, the self-discharge current threshold can also be determined in other ways. In some embodiments, continuing to refer to FIG. 6 , after step S1031 and before step S1032, the battery detection method of this embodiment may further include:

Step S104: Obtain the self-discharge currents of multiple batteries under test.

Step S105: Determine a self-discharge current threshold based on the distribution of self-discharge currents of multiple batteries under test.

Based on step S1031, step S104 can obtain the self-discharge current _{IC self- _discharge} of multiple batteries under test. It should be pointed out that due to the inevitable presence of some impurities in the battery manufacturing process, general normal batteries have slight self-discharge. In the detection method of this embodiment, because the self-discharge current _I of the battery under test is not measured directly using a detection instrument, it is measured based on the difference between the total charging current I of the battery under _test and the _standard value I. Calculated, in which the standard _value I is only used as a reference value. The actual calculated total charging _current I of the battery under test may be higher than the standard _value I, or may be lower than or equal to the standard _value I. Therefore, the calculated self-discharge current I _C of the battery under test may be greater than 0 mA, or may be less than or equal to 0 mA.

In step S105, the self-discharge current I _{C self-discharge} and battery number of multiple batteries under test can be counted, and a distribution diagram of the self-discharge current of the battery under test can be drawn. For example, see Figure 7, which shows some diagrams of the present application. Scatter plot of the self-discharge current of the battery under test in the battery detection method of the embodiment. The self-discharge current of the reference battery can be regarded as 0mA. Based on Figure 7, it can be seen that the self-discharge current _IC of most tested batteries is scattered around 0mA, and the self- _{discharge current IC} of a small number of tested batteries is much greater than 0mA. . In Figure 7, it can be determined that the point where the _{self-discharge current IC} exceeds 1A is a discrete point, and the battery under test whose _self -discharge current IC exceeds 1A is an abnormal battery.

In other embodiments of the present application, the normal distribution curve of the self-discharge current can be drawn according to the value and frequency of _{self-discharge} of the battery under test. Combined with the 3σ principle, the battery under test can be determined to be a normal battery. The self-discharge current I _{C self-discharge} is basically distributed between [0-3σ, 0+3σ], σ refers to the standard deviation. In this way, when the self-discharge current I _C of the battery under test is in the range of 0-3σ ≤ I _{C self-discharge} ≤ 0 + 3σ, the battery under test can be judged to be a normal battery _. When the range of _{self-discharge} is I _{C self-discharge} <0-3σ or I _{C self-discharge} >0+3σ, the battery under test can be judged to be an abnormal battery.

To determine whether the self-discharge current I _C of the battery under test is between [0-3σ, 0+3σ], you can refer to the following example:

In a possible example, the self-discharge current threshold can be designed to be 0mA. In this example, the specific implementation method of step S1032 is: compare the self-discharge current I _{C self-discharge} of the battery under test with 0mA. The comparison result obtained at this time is I _{C self-discharge} , and then whether the absolute value of I _{C self-discharge} is Less than or equal to 3σ to determine whether the battery under test is normal.

In another possible example, the self-discharge current threshold may include a first critical value and a second critical value, where the first critical value is -3σ (unit: mA) and the second critical value is 3σ (unit: mA). ). In this example, step S1032 can be implemented by using the following steps:

Step 1: Compare the self-discharge current I _{C self-discharge} of the battery under test with the first critical value -3σ, and obtain the first comparison result as the difference Δd1 = I _{C self-discharge} + 3σ;

Step 2: Compare the self-discharge current I _{C self-discharge} of the battery under test with the second critical value +3σ, and obtain the second comparison result as the difference Δd2 = I _{C self-discharge} -3σ;

Step 3: When the first comparison result Δd1 is greater than 0 and the second comparison result Δd2 is less than 0, determine that the battery under test is a normal battery.

Due to the influence of the battery production process, the performance of each battery is different. Therefore, even if each battery is a normal battery, the self-discharge current of each battery may not be completely consistent. This embodiment determines the self-discharge current threshold based on the distribution of the self-discharge current of the battery under test. In this way, by comparing the self-discharge current of the battery under test and the self-discharge current threshold, it can be determined whether the self-discharge performance of the battery under test is normal. Based on the above, it can be seen that the value of self-discharge current used to evaluate battery performance can be a range instead of a single value, which will help improve the accuracy and rationality of battery screening.

Illustratively, continuing to refer to FIG. 6 , after step S1032, the battery detection method of this embodiment may further include:

Step S106: Modify the self-discharge current threshold according to the self-discharge current of the reference battery.

Figure 8 is a normal distribution diagram of the self-discharge current of the reference battery. Step S106 can be implemented by: obtaining the self-discharge currents of multiple reference batteries, counting the intervals in which the self-discharge currents of the reference batteries are located and the frequency of each interval, and establishing a normal distribution diagram (for example, as shown in Figure 8). The horizontal axis of the distribution chart is the interval of the self-discharge current of the reference battery, and the vertical axis of the normal distribution chart is the frequency of each interval. The self-discharge current threshold is designed based on the distribution of the self-discharge current of the reference battery. For example, the self-discharge current threshold can be designed to be the self-discharge current of the reference battery with the highest frequency.

The specific implementation method of obtaining the self-discharge currents of multiple reference batteries may refer to the above-mentioned step S1031. It should be understood that before obtaining the self-discharge currents of multiple reference batteries, the reference battery needs to be determined first. The reference battery refers to the battery that has passed the test and is determined to be a normal battery, and the model and type are consistent with the battery under test. Here, it is worth pointing out that the reference battery can be determined by testing the K value or self-discharge rate of the battery using methods in the related art. Taking the K value of the test battery to determine the benchmark battery as an example, first test the K value of the battery, screen out the normal batteries based on the K value, and use some of the selected normal batteries with the same model and type as the battery under test as the benchmark battery. Then, the self-discharge current of the reference battery is calculated based on the charging data of the reference battery in the formation process, and the self-discharge current threshold is corrected accordingly.

Since the K value test or self-discharge rate test method is relatively mature, and the battery needs to be left aside for a period of time before the K value or self-discharge rate can be tested, the accuracy of using this method to screen normal batteries is relatively high. In other words, the purpose of step S106 can be understood as using a known and highly accurate method to screen out the reference battery, then using the detection method of this embodiment to calculate the self-discharge current of the reference battery, and correcting the self-discharge current based on the self-discharge current of the reference battery. discharge current threshold. In this way, the accuracy of screening the reference battery is high, which is conducive to reducing the impact of the design error of the self-discharge current threshold on the test results of the battery under test, and improving the test accuracy of the battery under test.

Designed in this way, the self-discharge current threshold is designed not only considering the distribution of the self-discharge current of the battery under test, but also considering the self-discharge current of the reference battery, so as to improve the accuracy of the self-discharge current threshold, so that according to the comparison The results can accurately determine whether the tested battery is a normal battery or an abnormal battery, reducing battery screening errors.

When the measured value is the total charging current I of the battery under _test and the standard value is the total charging current I of the reference _battery , as shown in Figure 6, before executing step S1031, the battery detection method can also be performed as follows: Described steps:

Step 1: Obtain the charging data of the reference battery during the formation process.

Step 2: Calculate the standard value based on the test voltage range and the charging data of the reference battery.

In this embodiment, according to I=Q/t, the calculation formula of the standard value is I _{standard total} =ΔQ _B /ΔT _B .

The above standard power difference ΔQ _B is the standard deviation value of the power value Q when the battery is charged from U _C1 to U _C2 . In a better example, the reference battery is a normal battery, so the difference in power value Q when the reference battery is charged from U _C1 to U _C2 can be regarded as the standard power difference, that is, the standard power difference ΔQ _B can be designed to be equal to The electric quantity value Q _B1 corresponding to when the reference battery is charged to the second endpoint voltage value U _C2 is subtracted from the electric quantity value Q _B2 corresponding to the first end point voltage value U _C1 of the reference battery, then ΔQ _B = Q _B2 - Q _B1 . The power value of the reference battery can be obtained in step 1, and its specific acquisition method is similar to that of the battery under test, and can also be detected by the detection circuit 130. In this way, multiple sets of charging data of the reference battery can be obtained in step 1, and each set of charging data is (U, Q).

Among them, ΔT _B refers to the standard charging time required for a normal battery to be charged from the first endpoint voltage value U _C1 of the test voltage range to the second endpoint voltage value U _C2 . ΔT _B can be designed based on experience and actual working conditions. For example, when the test voltage range is (2V, 3.2V), ΔT _B can be designed as 0.8h, 0.82h, 0.85h, 1h, etc. This embodiment does not do this limit.

In some embodiments, since the reference battery is a normal battery, the difference in charging time when the reference battery is charged from U _C1 to U _C2 can be regarded as the standard charging time ΔT _B . In this example, in addition to the voltage value and the corresponding power value, the detection circuit 130 is also configured to detect the charging time T (unit: h) required for charging the battery to a certain voltage value. At this time, the obtained charging data of the battery under test and the charging data of the reference battery are both (T, U, Q). In this way, the standard charging time ΔT _B can be determined based on the charging data of the reference battery in the formation process. The detection circuit 130 may include a clock chip, and the clock chip is used to measure the charging time of the battery.

For example, the charging data of the reference battery are obtained as shown in Table 1.

Table 1

Table 1 shows the charging data of battery A and battery B. The following takes the test voltage range as (2V, 3.2V) as an example. The charging time required for battery A to charge from 2V to 3.2V is 1.82h. -1h=0.82h, then ΔT _B can be designed as 0.82h. For example, when battery A is used as the reference battery, the standard power difference ΔQ _B = 20038.4mA·h-6734.3mA·h = 13304.1mA·h can be calculated. In this way, the total charging current of the reference battery _IStandard = ΔQ _B ÷ΔT _B = 13304.1mA·h÷0.82h = 16.224mA, then the standard value is 16.224mA. For another example, when battery B is used as the reference battery, the standard power difference ΔQ _B = 20318.5mA·h-7073.4mA·h = 13245.1mA·h can be calculated. In this way, the total charging current of the reference battery _IStandard = ΔQ _B ÷ ΔT _B =13245.1mA·h÷0.82h=16.152mA.

It can be understood that the standard value can also be an average of the total charging current of multiple reference batteries. For example, both A battery and B battery can be used as the reference battery. In this case, the standard value can be the average of the total charging current of battery A and the total charging current of battery B, then the standard value is (16.224mA+16.152mA)/2 =16.188mA. Compared with taking the total charging current of a reference battery as the standard value, in this embodiment, taking the average of the total charging current of multiple reference batteries as the standard value is beneficial to reducing the error of the referenced reference battery's total charging current. The impact brought by the test will help improve the accuracy of the test.

Compared with designing the standard value as a fixed value based on past experience, the detection method of this embodiment calculates the standard value based on the actual charging data of the reference battery in the formation process. In this way, the standard value is less prone to errors and the design is reasonable.

It is worth noting that when the detection circuit 130 can detect the charging time of the battery and the charging data includes the charging time, ΔT _c can be calculated based on the charging data of the battery under test obtained in step S101 . At this time, ΔT _c can be The charging time T2 required for the battery under test to charge to the second endpoint voltage value is minus the charging time T1 required for the battery under test to charge to the first endpoint voltage value.

Or, in other feasible embodiments, _ΔTC can be equal to _ΔTB , then the measured value is the total charging current of the battery under test _Itest , _Itest = _ΔQC / _ΔTC = _ΔQC / _ΔTB . Designed in this way, the total charging current of the battery under test is calculated based on the standard time required for a normal battery to charge from the first endpoint voltage value to the second endpoint voltage value. In this way, there is no need to charge the tested battery from the first endpoint voltage value. The charging time required to reach the second endpoint voltage value is calculated, which saves calculation time.

If it is assumed that the average of the total charging current of battery A and battery B shown in Table 1 is the standard value, that is, the standard value is 16.188mA·h, the test voltage range is (2V, 3.2V), ΔT _c is 0.82h, when When the test power difference of the battery under test is as shown in Table 2, according to the content described above, the total charging current and self-discharge current of the battery under test can be measured.

Table 2

Taking the self-discharge current threshold as 0mA as an example, at this time, the self-discharge current _IC of battery 1 under test in Table 2 is not equal to the self-discharge current threshold, then the battery under test is judged to be abnormal and is unqualified. Battery; Similarly, if the self-discharge current I _C of battery 2 under test in Table 2 is not equal to the self-discharge current threshold, the battery under test is judged to be abnormal and is also an unqualified battery.

Among them, in step S102, the implementation method of determining the test voltage interval of the battery under test based on the charging data of the battery under test specifically includes the following execution steps:

Step 1021: Perform fitting according to the charging data of the battery under test to generate a formation curve of the battery under test; the formation curve includes the voltage value and the corresponding power value of the battery under test.

Step 1022: Determine the test voltage interval based on the slope of each point on the formation curve of the battery under test.

Step S101 can obtain multiple sets of charging data of the battery under test, and each set of charging data is (U, Q). Step S1021 can obtain the formation curve of the battery under test by fitting multiple sets of charging data. For example, according to the charging data of the battery under test, the formation curve shown in Figure 9 can be obtained by fitting. The vertical axis of the formation curve represents the voltage value of the battery under test, and the horizontal axis of the formation curve represents the power value of the battery under test. Among them, FIG. 9 is a schematic diagram of the formation curve of the tested battery according to some embodiments of the present application. It can be seen from the formation curve that during the charging process of the battery under test, the voltage value of the battery under test is positively correlated with the power value. Moreover, when the voltage value of the measured voltage is in the range of 2V ~ 3.2V, the tangent slope of each point on the curve segment ab is greater than or equal to k1; when the voltage value of the measured voltage is in the range of 3.6V ~ 4V, the tangent slope of each point on the curve segment cd is The tangent slope of the point is greater than or equal to k2; when the voltage value of the measured voltage is in the range of 3.2V to 3.6V, the tangent slope of each point on the curve bc segment is greater than or equal to 0 and less than k1 and k2. This means that when the voltage value of the measured voltage is in the range of 2V to 3.2V and in the range of 3.6V to 4V, the voltage value increases rapidly, and when the voltage value of the measured voltage is in the range of 3.2V to 3.6V, the voltage value increases slowly. In this way, the curve segment ab can be regarded as the first non-platform area transformed into a curve, the curve segment bc can be regarded as the platform area transformed into a curve, and the curve segment cd can be regarded as the second non-platform area transformed into a curve.

In this way, the specific implementation of step S1022 can be to divide the formation curve into a platform area and a non-platform area according to the slope of each point on the formation curve of the battery under test, determine the voltage range corresponding to the platform area as the test voltage interval, or determine the non-platform area. The corresponding voltage range is the test voltage interval. The above-mentioned division of the formation curve into platform areas and non-platform areas based on the slope of each point on the formation curve includes but is not limited to the following possible implementation methods:

In one example, the transformation function U=f(Q) is constructed based on the transformation curve. The transformation function is used to characterize the transformation curve. The transformation function is first-order differentiated to obtain the first-order derivative function U=f'(Q). The transformation function is The charging data corresponding to each point in the curve is substituted into the first-order derivative function U=f'(Q) to obtain the first-order derivative of each point. In this way, it is confirmed that the point where the first-order derivative is greater than or equal to k1 and the voltage value is the smallest is the starting end point of the first non-platform area, and the point where the first-order derivative is greater than or equal to k1 and the voltage value is the largest is the end end point of the first non-platform area. Then the first non-platform area can be determined. Confirm that the point with the first-order derivative greater than or equal to k2 and the smallest voltage value is the starting endpoint of the second non-platform area, and confirm that the point with the first-order derivative greater than or equal to k2 and the largest voltage value is the end endpoint of the second non-platform area, then the The second non-platform area can be determined. Among them, the end endpoint of the first non-platform area is the start endpoint of the platform area, and the start endpoint of the second non-platform area is the end endpoint of the platform area, then the platform area can be determined.

Or, in another example, the transformation function U=f(Q) is constructed based on the transformation curve, the transformation function is used to characterize the transformation curve, and the first-order derivative is performed on the transformation function to obtain the first-order derivative function U=f'(Q) , arrange the charging data of the battery under test in order from small to large voltage values and substitute it into the first-order derivative function U=f'(Q), and then the first-order derivative sequence can be obtained, and the first-order derivative can be determined to change from greater than or equal to k1 The point that is greater than 0 but less than k1 and k2 is the starting end point of the platform area. It is determined that the point where the first derivative changes from greater than 0 but less than k1 and k2 to greater than or equal to k2 is the end end point of the platform area. Then the platform area can be determined, and then A first non-platform area and a second non-platform area may be determined.

The first-order derivative of each point in the formation curve represents the tangent slope of the point. In this way, the detection method can divide the platform area and the non-platform area by calculating the first-order derivative.

In the first example, the voltage range corresponding to the non-platform area can be determined as the test voltage interval. When the formation curve of the battery under test is as shown in Figure 9, the test voltage range of the battery under test at this time can be (2V, 3.2V) or (3.6V, 4V). Moreover, it can be understood that in some embodiments, the test voltage range of the battery under test can be further designed to be included in the voltage range corresponding to the non-platform area. For example, the test voltage range of the battery under test can be (2.2V, 3V), (3.8V, 4V), etc.

In the second example, the voltage range corresponding to the platform area can be determined as the test voltage interval. When the formation curve of the battery under test is as shown in Figure 9, the test voltage range of the battery under test at this time can be (3.2V, 3.6V). Moreover, it can be understood that in some embodiments, the test voltage range of the battery under test can be further designed to be included in the voltage range corresponding to the platform area. For example, the test voltage range of the battery under test can be (3.3V, 3.5V V).

Compared with designing the voltage range corresponding to the platform area as the test voltage interval, in the first example, the voltage range corresponding to the non-platform area is designed as the test voltage interval. When the power difference is the same, the voltage difference corresponding to the non-platform area If the value is larger, the difference between the first endpoint voltage value and the second endpoint voltage value of the test voltage interval can be larger to facilitate calculation.

It should be pointed out that for the tested batteries of the same model, after the test voltage interval is obtained according to the charging data of one of the tested batteries using step S102, this test can be referred to when using the method of this embodiment to detect other tested batteries. voltage range, step S102 can be omitted at this time.

The battery detection method of this embodiment establishes a formation curve based on the charging data of the battery under test, and determines the test voltage range based on the changes in the slope of each point on the formation curve. This fully takes into account the changing characteristics of the formation curve, which is beneficial to improving test accuracy. sex.

Of course, in other embodiments of the present application, two voltage values in the charging data of the battery under test can also be arbitrarily selected as the endpoint voltage values of the test voltage interval, thereby determining the test voltage interval of the battery under test.

It is worth noting that, referring to the detection method of this embodiment, using the charging data of the formation process to test the self-discharge current of the battery, and then detecting whether the battery is normal has been verified by a large number of experiments. Specifically, since the self-discharge caused by the internal short circuit of the battery is equivalent to the discharge caused by the series resistance of the battery, the experimental plan is to use the detection method of this embodiment to charge the unformed battery and record the charging data, and detect the battery without series resistance. The self-discharge current of the battery and the self-discharge current when a resistor is connected in series. Based on the difference between the self-discharge current when the battery is not connected in series with a resistor and the self-discharge current when a resistor is connected in series, it is proved that the self-discharge current when the battery is connected in series with a resistor is different from that of the battery. The self-discharge current when no resistor is connected in series, so whether the battery is normal can be judged based on the self-discharge current of the battery.

For details, please refer to Table 3, which shows the charging data of three experimental batteries. None of the three experimental batteries have been formed. Among the three experimental batteries, the S1 battery has no series resistor, the S2 battery has a series resistor and the resistance value is 100K. The S3 battery is connected in series with a resistor and the resistor value is 1M. Charge the S1 battery, S2 battery and S3 battery for formation. The test voltage range is (2V, 3.2V), and the charging time required for the three experimental batteries to charge from 2V to 3.2V is 0.87167h. Calculate three The self-discharge current of each experimental battery is shown in Table 3.

table 3

电池序号Battery serial number	电池串联电阻状态Battery series resistance status	测试电量差ΔQTest power difference ΔQ	充电总电流I _总 Total charging current I _total	自放电电流I _自放电 Self-discharge current ISelf _-discharge
S1电池S1 battery	未串联电阻No resistor in series	200.38200.38	229.88229.88	00
S2电池S2 battery	串联阻值为100K的电阻A resistor with a value of 100K in series	200.77200.77	230.33230.33	0.450.45
S3电池S3 battery	串联阻值为1M的电阻A resistor with a value of 1M in series	200.5200.5	230.02230.02	0.140.14

It can be seen from Table 3 that the S1 battery has no series resistor, which is equivalent to a normal battery with no internal short circuit. Therefore, the S1 battery can be used as the reference battery, and then the self-discharge current of the S2 battery can be calculated. I _{self-discharge} = 230.33-229.88 = 0.45, it can be seen that the self-discharge current of the S2 battery with a resistor with a resistance of 100K in series is not equal to the self-discharge current of the S1 battery. Similarly, the self-discharge current of the S3 battery with a resistor with a resistance of 1M in series is not equal to that of the S1 battery. Self-discharge current.

The following describes battery detection methods provided by other embodiments of the present application with reference to the accompanying drawings.

Figure 10 is a schematic diagram of the voltage charging time relationship curve of a normal battery and an abnormal battery. It can be seen from Figure 4a and Figure 4b that the abnormal battery has an internal short circuit, and the positive and negative electrodes of the abnormal battery are connected to form a conductive loop 140. The electrons e ^- in the negative electrode of the battery will migrate to the positive electrode along the conductive loop 140, causing self-discharge. Affected by self-discharge, abnormal batteries charge slower than normal batteries at the same current, and the charging time required to reach a certain voltage value is longer. Therefore, the voltage charging time relationship during normal battery charging is shown as the solid line in Figure 10, and the voltage charging time relationship during abnormal battery charging is shown as the dotted line in Figure 10. And it can be seen from Figure 10 that no matter whether it is a normal battery or an abnormal battery, during the formation stage, as the charging time increases, the voltage value of the battery gradually increases until the voltage value of the battery reaches the maximum. Based on this difference, this embodiment determines whether the battery under test is normal by comparing the relationship between the voltage value of the battery under test and the charging time and the relationship between the voltage value of the reference battery and the charging time. This embodiment is described in detail below with reference to the accompanying drawings.

Figure 11 is a schematic flowchart of a battery detection method according to other embodiments of the present application. In the example shown in Figure 11, the method includes the following steps S201 to S203.

Step S201, obtain the charging data of the battery under test in the formation process; the charging data includes reference parameters and parameters to be measured, where one of the reference parameters and the parameters to be measured is the voltage value, and the other is the voltage value charged to the corresponding voltage. The required charging time.

Step S202: Based on the charging data of the battery under test, determine the parameter value of the parameter to be measured when the reference parameter is in the interval to be estimated.

Step S203: Determine whether the battery under test is normal based on the comparison result between the parameter value of the battery under test and the base reference value when the reference parameter is in the range to be estimated.

Similar to step S101 in the detection method shown in FIG. 1 , the detection method of this embodiment also detects whether the battery under test is normal based on the charging data of the battery under test in the formation process. Specifically, the charging data obtained in step S201 in this example may include the voltage value U (unit: V) of the battery and the charging time T (unit: h) required for charging the battery to a certain voltage value. At this time, the detection circuit 130 may include a voltmeter 131 and a clock chip. The voltmeter 131 is connected in parallel with the battery to detect the voltage value of the battery, and the clock chip is used for timing.

It can be understood that the voltage value U of the battery and the corresponding charging time T are in one-to-one correspondence. Because the voltage value of the battery increases with the charging time, the detection circuit 130 can detect multiple sets of charging data during the battery charging process. In this way, multiple sets of charging data of the battery under test can be obtained in step S201, and each set of charging data can be (T, U). For example, if the voltage value of the power supply 110 is 4.2V, the charging data that may be obtained for a battery under test are (1h, 1.8V), (1.6h, 2.8V), (2h, 3.2V).

After obtaining the charging data, use one of the voltage value and charging time as the reference parameter and the other as the parameter to be measured, determine the value of the parameter to be measured when the reference parameter is in the interval to be measured, and then use the parameter of the parameter to be measured to The value is compared with the baseline reference value. Here, the baseline reference value can be understood as the value of the parameter to be measured when the reference parameter of the reference battery is in the interval to be measured. Among them, the model and type of the reference battery are consistent with the battery under test, the reference battery is a normal battery, and the charging parameters (such as charging current or charging voltage) of the reference battery in the formation process are consistent with the charging parameters of the battery under test in the formation process. In this way, by comparing the parameter value of the parameter to be tested with the benchmark reference value, it can be determined whether the parameter value of the parameter to be tested is different from that of the benchmark battery. If the parameter value of the parameter to be tested is different from the benchmark battery, Then you can determine whether the battery under test is normal.

In summary, by detecting the battery under test according to the detection method provided in this embodiment, it can be determined whether the battery under test is normal, and then abnormal batteries can be screened out. Moreover, because the charging time required for an abnormal battery with self-discharge phenomenon to be charged to a certain voltage value is longer than the charging time required for a normal battery to be charged to a certain voltage value, the detection method provided in this embodiment is by Comparing the relationship between the voltage value of the battery under test and the charging time and the voltage value of the reference battery and the charging time can be used to detect whether the self-discharge performance of the battery under test is qualified.

In the related art, the battery process flow includes a sealing process, a formation process, a resting process, a testing process, and a capacity dividing process. That is, the battery is first put aside and then the discharge parameters of the battery are detected to test the performance of the battery. This embodiment uses the charging data of the battery during the formation process to determine the performance of the battery. Therefore, the detection method provided by this embodiment can be executed after the formation process and before the resting process. Designed in this way, the detection method can be used to test the performance of the battery with the help of the charging data of the formation process before the resting process and the testing process, so as to screen out unqualified batteries in advance. In this way, there is no need to put the battery aside for a period of time, which is beneficial to shortening the battery life. Battery testing time and testing cycles improve testing efficiency, which in turn helps alleviate the pressure on battery manufacturers’ storage space and cash flow.

In a feasible embodiment, the reference parameter can be the voltage value of the interval to be estimated, and the parameter to be measured is the charging time required to charge to the corresponding voltage value. The reference reference value at this time is the charging time of the reference battery to The charging time required for the corresponding voltage value. The meaning of this embodiment is to compare the charging time required for the tested battery and the reference battery to charge to the same voltage value under the same charging parameters. Among them, the interval to be estimated can be (U _d1 , U _d2 ), and U _d1 is smaller than U _d2 . In this way, the method of this embodiment uses the charging data of the battery under test in the constant current charging stage for testing, and has high detection accuracy.

For example, the reference parameter can be U _d1 , and the parameter to be measured is the charging time T _d1 required for the battery under test to be charged to U _d1 . Here, the base reference value can be designed based on experience and actual working conditions. Preferably, the base reference value can be the charging time T _J1 required for the base battery to be charged to U _d1 . Based on the comparison results between T _d1 and T _J1 , the target battery is judged to be charged. Check whether the battery is normal. Among them, according to the comparison result of T _d1 and T _J1 , the following possible situations exist to determine whether the battery under test is normal: In the first situation, if the comparison result is T _d1 = T _J1 , then the battery under test is judged to be normal. If If the comparison result is T _d1 ≠ T _J1 , the battery under test is judged to be abnormal. In the second case, if the comparison result is that the difference between T _d1 and T _J1 is within the preset range, the battery under test is judged to be normal. If the comparison result If the difference between T _d1 and T _J1 exceeds the preset range, the battery under test is judged to be abnormal. Designed in this way, the essence of the second situation is that the charging time T _d1 required for the battery to be tested to be charged to U _d1 is within a time range, which is a qualified battery. Compared with comparing T _d1 with a numerical value, it is helpful to reduce the detection deviation. This results in inaccurate testing.

For another example, the reference parameter can be U _d2 , and the parameter to be measured is the charging time T _d2 required to charge the battery under test to U _d2 ; or the reference parameter can also be any voltage value within the interval to be estimated. Of course, in some embodiments, there can be multiple reference parameters. In this way, multiple sets of parameters to be measured of the battery under test need to be compared with multiple sets of parameters to be measured of the reference battery to avoid errors in one set of parameters that may cause the test to fail. The results are inaccurate, which in turn helps improve the accuracy of the test.

In another possible embodiment, the reference parameter is the charging time, and the parameter to be measured is the corresponding voltage value. The base reference value at this time is the voltage value reached when the charging time of the reference battery is the reference parameter. The meaning of this embodiment is to compare the voltage values reached when the tested battery and the reference battery are charged under the same charging parameters and for the same length of time. Here, the interval to be estimated can be (T _d1 , T _d2 ), and T _d1 is smaller than T _d2 .

Here, the specific implementation of step S203 may be as follows:

Step 1: Compare the voltage value corresponding to the battery under test when the charging time is the first preset value with the first reference value to obtain the first comparison result.

Step 2: Compare the voltage value corresponding to the battery under test when the charging time is the second preset value with the first reference value to obtain a second comparison result.

Step 3: Determine whether the battery under test is normal based on the first comparison result and the second comparison result.

The first preset value and the second preset value may be any value within the interval to be evaluated. For example, the first preset value may be T _d1 . At this time, the corresponding voltage value is the voltage value U _d1 reached by the battery under test when the charging time reaches T _d1 . Here, the first reference value can be designed based on experience and actual working conditions. Preferably, the base reference value can be the voltage value reached by the base battery when the charging time is T _d1 . The second preset value may be T _d2 . At this time, the corresponding voltage value is the voltage value U _d2 reached by the battery under test when the charging time reaches T _d2 .

Table 4

For example, Table 4 shows the charging data for battery C, battery D, and the two batteries under test. Taking the interval to be estimated as (48s, 3000s) and C battery as the benchmark battery as an example, the first preset value can be 48s and the second preset value can be 3000s. One of the reference values is when the charging time reaches 48s, the corresponding first reference value is the corresponding voltage value 2.004V when the C battery charging time reaches 48s, the other reference value is when the charging time reaches 3000s, the corresponding second reference value That is, the corresponding voltage value is 3.164V when the C battery charging time reaches 3000s.

The voltage value of the tested battery 3 when the charging time reaches 48s is 1.948V. Compare it with the first reference value 2.004V. The first comparison result is that the voltage value of the tested battery 3 when the charging time reaches 48s is less than the first reference value. Reference. Compare it with the second reference value 3.164V, and obtain the second comparison result that the voltage value of the tested battery 3 when the charging time reaches 48 seconds is less than the second reference value. Both the first comparison result and the second comparison result are that when the charging time of the battery 3 under test reaches the preset value, the corresponding voltage value is less than the base reference value, and then it can be determined that the battery 3 under test is abnormal.

Similarly, the voltage value reached by the tested battery 4 when the charging time reaches 48s is smaller than the corresponding first reference value, and the voltage value reached by the tested battery 4 when the charging time reaches 3000s is also smaller than the corresponding second reference value. , then the battery under test 4 is also different from the reference battery, and the battery under test 4 can be determined to be abnormal.

In this design, multiple reference parameters need to be taken, and multiple sets of parameters to be tested can be obtained for the battery under test. By comparing multiple sets of parameters to be tested and multiple sets of benchmark reference values, the battery under test can be tested. In this way, the number of sets of reference parameters is large, which is beneficial to improving the accuracy of the test.

According to some embodiments of the present application, the difference between the voltage value corresponding to the battery under test when the charging time is the first preset value and the voltage value corresponding to the battery under test when the charging time is the second preset value is greater than 0.5. V.

For example, the first preset value is T _d1 , and the corresponding voltage value of the battery under test is U _d1 when the charging time is the first preset value. The second preset value is T _d2 , and the battery under test is charged for the third time. The corresponding voltage value at the second preset value is U _d2 . Among them, ΔU _d =U _d2 -U _d1 , ΔU _d >0.5V.

In this way, the difference between the two groups of measured parameters of the battery under test is obtained to be relatively large, which makes it easy to calculate and obtain accurate comparison results, which in turn helps improve the accuracy of the detection.

FIG. 12 is a schematic flowchart of a modified example of the method shown in FIG. 11 . It is worth noting that, referring to Figure 12, before step S203, the detection method of this embodiment may also include the following steps:

Step S204: Obtain the charging data of the reference battery.

Step S205: According to the charging data of the reference battery, determine the parameter value of the parameter to be measured of the reference battery when the reference parameter is in the interval to be estimated.

Step S206: Determine the base reference value based on the parameter value of the parameter to be measured of the base battery when the reference parameter is in the interval to be estimated.

The specific method of obtaining the charging data of the reference battery in step S204 may refer to step S201. This embodiment will not be repeated here. In step S204, multiple sets of charging data of the reference battery may be obtained. The purpose of step S206 is to design the benchmark reference value to be the parameter value of the parameter to be measured when the reference parameter of the benchmark battery is in the interval to be estimated. For example, in Table 4, C battery is used as the benchmark battery, and the reference parameter is that the charging time reaches 48 seconds, then the benchmark reference The value is the voltage value 2.004V reached by the reference battery after charging for 48 seconds.

Compared with designing the base reference value as a fixed value based on past experience, in the detection method of this embodiment, the base reference value is designed based on the actual charging data of the base battery in the formation process. In this way, the base reference value is less prone to errors and design errors. Reasonable.

Based on the embodiment shown in Figure 12, step S206 can be implemented in the following manner:

The base reference value is determined based on the average value of the parameter values to be measured of multiple reference batteries when the reference parameter is in the interval to be estimated.

That is to say, when the reference parameter is the voltage value, the parameter to be measured is the average of the charging time corresponding to the voltage value of multiple reference batteries; when the reference parameter is the charging time, the parameter to be measured is the average of the charging time corresponding to the voltage value. The battery is charged to the average voltage value corresponding to the charging time.

Specifically, taking the C battery and D battery shown in Table 4 as the reference battery, if the reference parameter is that the charging time of the battery reaches 48s, then the parameters to be measured are the voltage value reached by the C battery when the charging time is 48s and the D battery. The average voltage value reached when the charging time is 48s, that is, the parameter to be measured = 2.004V + 2.007V = 2.0055V.

In this embodiment, by taking the average value of the parameters to be measured of multiple benchmark batteries as the benchmark reference value, it is helpful to reduce the impact of the error of a single value on the test, and to improve the accuracy of the test.

The above step S203 can also be implemented by using the following steps:

Step 1: Establish the first relationship curve of the battery under test based on the charging data of the battery under test;

Step 2: Establish the second relationship curve of the reference battery based on the charging data of the reference battery

Step 3: Determine whether the battery under test is normal based on the comparison result between the section to be estimated of the first relationship curve and the section to be estimated of the second relationship curve; wherein, the section to be estimated of the first relationship curve is the reference parameter in the first relationship curve. The curve segment in the interval to be estimated, the segment to be estimated in the second relationship curve is the curve segment in the second relationship curve in which the reference parameter is in the interval to be estimated.

The charging data of the battery under test in step 1 includes the voltage value of the battery under test and the corresponding charging time. Then the first relationship curve may include the voltage value and the charging time. The voltage value is the vertical axis of the first relationship curve, and the charging time is the third. The horizontal axis of a relationship curve. Step 1: Matlab can be used to fit multiple sets of charging data obtained in step S201 to form a first relationship curve.

In step 2, the horizontal axis of the second relationship curve is the charging time of the reference battery, and the vertical axis is the voltage value of the reference battery. The second relationship curve is formed by fitting multiple sets of charging data obtained in step S204 using Matlab. .

The section to be estimated of the first relationship curve in step 3 is the curve section where the reference parameter is in the interval to be estimated. For example, the first relationship curve of the battery under test can be as shown in Figure 13. The reference parameter is the charging time and the interval to be estimated is Taking (48s, 3000s) as an example, at this time, the section to be estimated of the first relationship curve is the cs section. In the same way, the section to be estimated of the second relationship curve in step 3 is the curve section in the relationship curve of the reference battery in which the reference parameter is in the range to be estimated. Among them, FIG. 13 is a schematic diagram of the first relationship curve of the battery according to some embodiments of the present application.

The purpose of step 3 can be understood as comparing the section to be estimated of the battery under test with the section to be estimated of the reference battery. If the section to be estimated of the battery under test overlaps or is highly similar to the section to be estimated of the benchmark battery, it can be determined that the section under test is The battery is normal. If the section to be evaluated of the battery under test does not coincide with the section to be evaluated of the reference battery or the similarity is low, it can be determined that the battery under test is abnormal.

With this arrangement, the relationship curve obtained by fitting the charging data of the battery under test is compared with the relationship curve obtained by fitting the charging data of the reference battery to determine whether there is an abnormality in the battery under test.

Based on the above description, the detection circuit 130 can be configured to detect the voltage value, power value and charging time of the battery. Then the charging data of the battery 200 can include the voltage value U, the power value Q and the charging time T. In this way, not only can the detection methods shown in Figures 1 and 6 be used to determine whether the battery under test is qualified based on the detected voltage value U and power value Q of the battery under test, but also the testing methods shown in Figures 11 and 12 can be used. The detection method determines whether the battery under test is qualified based on the detected voltage value U and charging time T of the battery under test. In general, by obtaining the charging data of the battery in the formation process, the charging data includes the voltage value U, the electric quantity value Q and the charging time T. Based on the charging data, multiple detection methods can be selected to test the battery under test.

Based on the above embodiments, the charging data may also include the electric quantity value Q when charging to the corresponding voltage value. That is to say, the charging data of the battery under test obtained in step S201 in this embodiment is (T, U, Q).

In this example, after performing step S201, the method may also include the following steps:

Step S207: Determine the resistance value of the battery under test based on the charging data of the battery under test.

Step S208: Determine whether the battery under test is normal based on the comparison result between the resistance value of the battery under test and the reference resistance value.

Since the charging data (T, U, Q) of the battery under test is known, the corresponding current value when the battery under test is charged to a certain length of time can be calculated using the formula I=Q/T, and then the formula R=U/I can be used to calculate Calculate the resistance value of the battery under test. In this example, the charging data (T, U, Q) of the reference battery can also be obtained by referring to step S201. Based on this, the resistance value of the reference battery can also be calculated, and the resistance value of the reference battery can be the reference resistance value. Compare the resistance value of the battery under test with the reference resistance value. When the resistance value of the battery under test is equal to the reference resistance value, it can be determined that the battery under test is normal. When the resistance value of the battery under test is not equal to the reference resistance value, it can be determined that the battery under test is normal. The battery under test is abnormal.

With this arrangement, the detection method of this embodiment can also detect the resistance value of the battery under test. By comparing the resistance value of the battery under test with the reference resistance value, it can be determined whether the internal resistance of the battery under test is normal. That is to say, the detection method of this embodiment is suitable for detecting the internal resistance performance of the battery.

Figure 14 is a schematic flowchart of a battery detection method according to some further embodiments of the present application. Referring to FIG. 14 , in a specific embodiment, the battery detection method may include steps S301 to S313.

Step S301: Obtain the charging data of the battery under test in the formation process; the charging data includes the voltage value U and the corresponding electric quantity value Q.

Step S302: Perform fitting according to the charging data of the battery under test to generate a formation curve of the battery under test; wherein the formation curve data of the battery under test includes a voltage value of the battery under test and a corresponding power value.

Step S303: According to the slope of each point on the formation curve of the battery under test, the formation curve is divided into a platform area and a non-platform area, and the voltage range corresponding to the platform area is determined as the test voltage interval ( _UC1 , U _C2 ).

Step S304: Calculate the test power difference ΔQ _C according to the charging data of the battery under test and the test voltage interval ( _UC1 , U _C2 ). The test power difference ΔQ _C is equal to the power value Q _C2 corresponding to the battery under test charged to U _C2 minus the power value Q _C1 corresponding to the charge to U _C1 .

Step S305: Obtain the charging data of the reference battery in the formation process; the charging data includes the voltage value U, the corresponding power value Q and the charging time.

Step S306: Calculate the standard power difference ΔQ _B and the standard charging time ΔT _B according to the charging data of the reference battery and the test voltage interval ( _UC1 , _UC2 ). Among them, the standard power difference ΔQ _B is equal to the power value Q _C2 corresponding to the reference battery charged to U _C2 minus the power value Q _C1 corresponding to the charge to U _C1 . The standard charging time ΔT _B is equal to the charging time required for the reference battery to be charged to U _C2 Subtract the charging time required to charge to U _C1 .

Step S307: Calculate the total charging current I of the battery under test and the total charging current I of the reference battery _based on the test power difference ΔQ _C , the standard power difference ΔQ _B and the standard charging _time ΔT _B . Among them, I _{measured total} = ΔQ _C ÷ ΔT _B , I _standard _total = ΔQ _B ÷ ΔT _B .

Step S308: _Calculate the self-discharge current I of the battery under test based on the total charging current I of the battery _{under test and} the total charging current _I of the reference battery. Among them, I _{C self-discharge} = I _{measured total} - I _{standard total} .

Step S309: Repeat steps S301 to step S308 to obtain the self-discharge current _{IC self-discharge} of multiple batteries under test.

Step S310: Determine a self-discharge current threshold based on the distribution of self-discharge currents of multiple batteries under test.

Step S311: Compare the self-discharge current of each tested battery with the self-discharge current threshold, and determine whether the tested battery is normal based on the comparison result.

Step S312: Obtain the charging data of the normal battery in the formation process based on the test results of the voltage drop method.

Step S313: Calculate the self-discharge current of each normal battery based on the charging data of the normal battery in S312, and adjust the self-discharge current threshold based on the distribution of the self-discharge current of the normal battery.

The order of step S301 and step S305 is not specifically limited.

Figure 15 is a schematic structural diagram of a battery detection device 300 according to some embodiments of the present application. Referring to FIG. 15 , an embodiment of the present application provides a battery detection device 300 . The battery detection device 300 includes: a data acquisition module 310 , a determination module 320 and a judgment module 330 . Among them, the data acquisition module 310 is used to obtain the charging data of the battery under test in the formation process; the charging data includes the voltage value and the corresponding power value; the determination module 320 is used to determine the battery under test based on the charging data of the battery under test. Test the voltage range and the measured value; the judgment module 330 is used to judge whether the battery under test is normal based on the measured value and the standard value.

In some embodiments, the judgment module 330 is further configured to calculate the self-discharge current of the battery under test based on the measured value and the standard value; compare the self-discharge current of the battery under test with the self-discharge current threshold to obtain a comparison result, based on Compare the results to determine whether the battery under test is normal.

In some embodiments, the data acquisition module 310 is further configured to acquire multiple batteries under test before comparing the self-discharge current and the self-discharge current threshold of the battery under test to obtain a comparison result, and determining whether the battery under test is normal based on the comparison result. The self-discharge current; the determination module 320 is further configured to determine the self-discharge current threshold according to the distribution of self-discharge currents of the plurality of batteries under test.

In some embodiments, the battery detection device 300 also includes a correction module. The correction module is used to compare the self-discharge current of the battery under test with the self-discharge current threshold to obtain a comparison result, and determine whether the battery under test is normal based on the comparison result. , the self-discharge current threshold is corrected based on the self-discharge current of the reference battery.

In some embodiments, the data acquisition module 310 is further configured to obtain the charging data of the reference battery in the formation process before determining whether the battery under test is normal based on the measured value and the standard value; the determination module 320 is further configured to obtain charging data based on the test The voltage range and the charging data of the reference battery are used to calculate the standard value.

In some embodiments, the determination module 320 is further configured to perform fitting according to the charging data of the battery under test and generate a formation curve of the battery under test; wherein the formation curve includes the voltage value and the corresponding power value of the battery under test; according to The slope of each point on the formation curve of the battery under test determines the test voltage range.

Continuing to refer to FIG. 15 , an embodiment of the present application also provides a battery detection device 300 . The battery detection device 300 includes: a data acquisition module 310 , a determination module 320 and a judgment module 330 . Among them, the data acquisition module 310 is used to obtain the charging data of the battery under test in the formation process; the charging data includes reference parameters and parameters to be measured, where one of the reference parameters and the parameters to be measured is the voltage value, and the other is the charging value. The charging time required to reach the corresponding voltage value; the determination module 320 is used to determine the parameter value of the parameter to be tested when the reference parameter is in the interval to be estimated according to the charging data of the battery to be tested; the judgment module 330 is used to determine the parameter value according to the charging data of the battery to be tested. The parameter value of the battery under test is compared with the baseline reference value when the reference parameter is in the range to be estimated to determine whether the battery under test is normal.

In some embodiments, the reference parameter is the charging time and the parameter to be measured is the voltage value. The judgment module 330 is further configured to compare the voltage value corresponding to the battery under test when the charging time is the first preset value with the first reference value. Obtain the first comparison result; compare the voltage value corresponding to the tested battery when the charging time is the second preset value with the second reference value to obtain the second comparison result; judge the tested battery based on the first comparison result and the second comparison result. Is the battery normal?

In some embodiments, the difference between the voltage value corresponding to the battery under test when the charging time is the first preset value and the voltage value corresponding to the battery under test when the charging time is the second preset value is greater than 0.5V.

In some embodiments, the data acquisition module 310 is further configured to determine whether the battery under test is normal based on the comparison result of the parameter value of the battery under test when the reference parameter is in the interval to be estimated and the baseline reference value, Obtain the charging data of the reference battery; the determination module 320 is further configured to determine, based on the charging data of the reference battery, the parameter value of the parameter to be measured of the reference battery when the reference parameter is in the interval to be estimated; the determination module 330 is further configured to determine the parameter value of the reference battery based on the charging data of the reference battery. The parameter value of the parameter to be measured when the reference parameter is in the interval to be estimated determines the base reference value.

In some embodiments, the determination module 320 is further configured to determine the base reference value based on an average of the parameter values of the parameters to be measured of the plurality of reference batteries when the reference parameters are in the interval to be evaluated.

In some embodiments, the judgment module 330 is further configured to establish a first relationship curve of the tested battery based on the charging data of the tested battery; establish a second relationship curve of the reference battery based on the charging data of the reference battery; based on the first The comparison result between the to-be-evaluated section of the relationship curve and the to-be-evaluated section of the second relationship curve is used to determine whether the battery under test is normal; wherein, the to-be-evaluated section of the first relationship curve is the curve in which the reference parameter in the first relationship curve is in the to-be-evaluated interval. segment, the segment to be estimated of the second relationship curve is the curve segment in the second relationship curve in which the reference parameter is in the interval to be estimated.

In some embodiments, the charging data also includes the electric quantity value when charging to the corresponding voltage value; the determination module 320 is further configured to, after the data acquisition module 310 obtains the charging data of the battery under test in the formation process, according to the battery under test. The charging data is used to determine the resistance value of the battery under test; the determination module 330 is further configured to determine whether the battery under test is normal based on the comparison result between the resistance value of the battery under test and the reference resistance value.

Figure 16 is a schematic structural diagram of an electronic device according to some embodiments of the present application. Referring to Figure 16, an embodiment of the present application also provides an electronic device, including: a memory 401 and at least one processor 402. Memory 401 is used to store program instructions. The processor 402 is configured to implement the battery detection method in this embodiment when the program instructions are executed. For specific implementation principles, please refer to the above embodiments, and this embodiment will not be described again here. The electronic device may also include an input/output interface 403. The input/output interface 403 may include an independent output interface and an input interface, or may be an integrated interface integrating input and output. Among them, the output interface is used to output data, and the input interface is used to obtain input data.

One embodiment of the present application provides a computer-readable storage medium. Execution instructions are stored in the readable storage medium. When at least one processor 402 of the electronic device executes the execution instructions, when the computer execution instructions are executed by the processor 402, Implement the battery detection method in the above embodiment. Among them, the computer-readable storage medium can be ROM, random access memory 401 (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

The present application provides a computer program product, including a computer program. The computer program is executed by the processor 402 to implement the battery detection method provided in any one of the embodiments corresponding to FIG. 1 and FIG. 14 of the present application.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features can be equivalently replaced; and these modifications or substitutions do not deviate from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present application. The scope shall be covered by the claims and description of this application. In particular, as long as there is no structural conflict, the technical features mentioned in the various embodiments can be combined in any way. The application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

A battery detection method, including:

Obtain the charging data of the tested battery in the formation process; wherein the charging data includes the voltage value and the corresponding power value;

According to the charging data of the battery under test, determine the test voltage range and measured value of the battery under test;

According to the measured value and the standard value, it is judged whether the battery under test is normal.
The detection method according to claim 1, wherein the measured value is a test power difference, and the test power difference is when the tested battery is charged from the first endpoint voltage value of the test voltage interval to the The difference between the electric capacity value at the second endpoint voltage value of the test voltage interval, and the standard value is when the reference battery is charged from the first endpoint voltage value of the test voltage interval to the second endpoint voltage value of the test voltage interval. The standard deviation value of the power value.
The detection method according to claim 1, wherein the measured value is the total charging current of the battery under test, and the standard value is the total charging current of the reference battery.
The detection method according to claim 3, wherein determining whether the tested battery is normal based on the measured value and the standard value includes:

Calculate the self-discharge current of the battery under test based on the measured value and the standard value;

The self-discharge current of the battery under test is compared with the self-discharge current threshold to obtain a comparison result, and whether the battery under test is normal is determined based on the comparison result.
The detection method according to claim 4, wherein in the step of comparing the self-discharge current of the battery under test with the self-discharge current threshold to obtain a comparison result, it is determined whether the battery under test is normal based on the comparison result. Previously, this also included:

Obtain the self-discharge currents of multiple batteries under test;

The self-discharge current threshold is determined according to the distribution of the self-discharge currents of a plurality of batteries under test.
The detection method according to claim 4 or 5, wherein in the step of comparing the self-discharge current and the self-discharge current threshold of the battery under test to obtain a comparison result, the battery under test is judged according to the comparison result. After whether it is normal, it also includes:

The self-discharge current threshold is corrected according to the self-discharge current of the reference battery.
The detection method according to any one of claims 3 to 6, wherein before determining whether the battery under test is normal based on the measured value and the standard value, it further includes:

Obtain the charging data of the reference battery in the formation process;

The standard value is calculated based on the test voltage interval and the charging data of the reference battery.
The detection method according to any one of claims 1 to 7, wherein determining the test voltage interval of the battery under test based on the charging data of the battery under test includes:

Fitting is performed according to the charging data of the battery under test to generate a formation curve of the battery under test; wherein the formation curve includes the voltage value of the battery under test and the corresponding power value;

The test voltage interval is determined based on the slope of each point on the formation curve of the battery under test.
A battery testing device, including:

The data acquisition module is used to acquire the charging data of the tested battery during the formation process; wherein the charging data includes the voltage value and the corresponding electric quantity value;

A determination module, configured to determine the test voltage range and measured value of the battery under test based on the charging data of the battery under test;

A judgment module is used to judge whether the battery under test is normal based on the measured value and the standard value.
An electronic device, wherein the electronic device includes a memory and a processor,

The memory stores a computer program;

The processor executes the computer program stored in the memory, so that the electronic device executes the detection method according to any one of claims 1 to 8.
A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and the computer program is used to implement the detection method according to any one of claims 1 to 8 when executed by a processor.
A computer program product, wherein the computer program product includes a computer program, which when executed by a processor is used to implement the detection method according to any one of claims 1 to 8.