Battery health detection method, apparatus, device, and system

Abstract

The application provides a battery health detection method, device, equipment and system, the method comprises the following steps: obtaining the voltage value of the battery to be detected at a preset time after each charging / discharging operation ends before the current time; based on the voltage value at the preset time, the polarization voltage value of the battery to be detected after each charging / discharging operation ends is determined; based on all the polarization voltage values before the current time, the voltage deviation value of the battery to be detected at the current time is determined; based on the voltage deviation value, the battery health state of the battery to be detected is determined. Through the above manner, the efficiency and accuracy of battery health detection can be improved.

Description

Technical Field

[0001] This invention relates to the field of lithium battery technology, and in particular to battery health testing methods, apparatus, equipment and systems. Background Technology

[0002] During use, as the number of charge / discharge cycles increases, the capacity of lithium batteries will decrease to a certain extent, and may even lead to serious deterioration such as short circuit and lithium plating, causing significant safety hazards. Therefore, the health status testing of lithium batteries is of great significance and has substantial market demand.

[0003] However, most current lithium battery health testing methods suffer from low efficiency and accuracy. Summary of the Invention

[0004] In view of this, the present invention provides a battery health detection method, apparatus, device and system that can improve the efficiency and accuracy of battery health detection.

[0005] To address the aforementioned technical problems, the present invention provides a battery health detection method, comprising: acquiring the voltage value of the battery under test at a preset time after each charging / discharging operation prior to the current time; determining the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time; determining the voltage deviation value of the battery under test at the current time based on all polarization voltage values ​​prior to the current time; and determining the battery health status of the battery under test based on the voltage deviation value.

[0006] According to some embodiments of the present invention, the step of determining the voltage deviation value of the battery under test at the current moment based on all polarization voltage values ​​prior to the current moment includes: determining multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the initial charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation; and determining the voltage deviation value based on all Mahalanobis distance parameters.

[0007] According to some embodiments of the present invention, when the preset time includes a preset millisecond-level time and a preset second-level time, and the polarization voltage value includes an ohmic polarization voltage value and an electrochemical transfer polarization voltage value, the step of determining the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time includes: determining the voltage value at the preset millisecond-level time as the ohmic polarization voltage value; and determining the difference between the voltage value at the preset second-level time and the voltage value at the preset millisecond-level time as the electrochemical transfer polarization voltage value.

[0008] According to some embodiments of the present invention, the step of determining multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the initial charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation includes: determining the Mahalanobis distance parameters corresponding to the battery under test after each subsequent charge / discharge operation using the following formula (1):

[0009]

[0010] Wherein, D(x) is the Mahalanobis distance parameter of the battery under test after the x-th charge / discharge operation, V(ax) is the ohmic polarization voltage of the battery under test after the x-th charge / discharge operation, V(a0) is the ohmic polarization voltage of the battery under test after the first charge / discharge operation, V(bx) is the electrochemical transfer polarization voltage of the battery under test after the x-th charge / discharge operation, and V(bx) is the electrochemical transfer polarization voltage of the battery under test after the first charge / discharge operation.

[0011] According to some embodiments of the present invention, when the preset time includes a preset millisecond-level time, a preset second-level time, and a preset long time, and the polarization voltage value includes an ohmic polarization voltage value, an electrochemical transfer polarization voltage value, and a diffusion polarization voltage value, the step of determining the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time includes: determining the voltage value at the preset millisecond-level time as the ohmic polarization voltage value; determining the difference between the voltage value at the preset second-level time and the voltage value at the preset millisecond-level time as the electrochemical transfer polarization voltage value; and determining the difference between the voltage value at the preset long time and the voltage value at the preset second-level time as the diffusion polarization voltage value.

[0012] According to some embodiments of the present invention, the step of determining multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the initial charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation includes: determining the Mahalanobis distance parameters corresponding to the battery under test after each subsequent charge / discharge operation using the following formula (2):

[0013]

[0014] Wherein, V(cx) is the diffusion polarization voltage of the battery under test after the xth charge / discharge operation, and V(c0) is the diffusion polarization voltage of the battery under test after the first charge / discharge operation.

[0015] According to some embodiments of the present invention, the step of determining the voltage deviation value based on all Mahalanobis distance parameters includes: determining the voltage deviation value using the following formula (3):

[0016]

[0017] Where N is the voltage deviation value, and Y is the total number of charging / discharging operations of the battery under test before the current moment.

[0018] According to some embodiments of the present invention, the step of determining the battery health status of a battery under test based on a voltage deviation value includes: determining that the battery under test has a health problem when the voltage deviation value is greater than a deviation threshold.

[0019] Secondly, embodiments of the present invention provide a battery health detection device, including an acquisition module, a polarization voltage determination module, a deviation determination module, and a health status determination module.

[0020] The acquisition module is used to acquire the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time; the polarization voltage determination module is used to determine the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time; the deviation determination module is used to determine the voltage deviation value of the battery under test at the current time based on all polarization voltage values ​​before the current time; and the health status determination module is used to determine the battery health status of the battery under test based on the voltage deviation value.

[0021] Thirdly, embodiments of the present invention provide a battery health detection device, comprising: a processor; and a memory, wherein computer program instructions are stored in the memory.

[0022] When the computer program instructions are executed by the processor, the processor performs the battery health detection method as described in the above embodiments.

[0023] Fourthly, embodiments of the present invention provide a battery health detection system, including a voltage detection device and a battery health detection device.

[0024] The voltage detection device is connected to the battery under test to detect the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time; the battery health detection device is connected to the voltage detection device to perform health detection on the battery under test based on the voltage value, wherein the battery health detection device is the battery health detection device in the above embodiment.

[0025] According to some embodiments of the present invention, the battery health detection system further includes: an alarm device connected to the battery health detection device, used to receive an alarm signal fed back by the battery health detection device and perform an alarm operation when the battery health detection device determines that the health of the battery under test has a problem.

[0026] The above-described technical solution of the present invention has at least one of the following beneficial effects:

[0027] This method leverages the correlation between voltage response time and different types of polarization voltage during lithium battery relaxation. By collecting voltage values ​​at different preset times after the charging / discharging operation of the battery under test, it obtains the corresponding polarization voltages of different types. Then, by utilizing all polarization voltage values ​​prior to the current time, it determines the voltage deviation, thereby enabling the detection of the battery's health status. This embodiment only requires segmented voltage detection at a few preset times to differentiate polarization voltages, enabling the detection of battery health status. While maintaining accuracy, it offers the advantages of simplicity and speed, avoiding complex data analysis and making battery health detection faster and more efficient, significantly improving both efficiency and accuracy. Furthermore, it eliminates the need to apply multiple high-frequency or low-frequency currents to the battery under test, preventing damage and ensuring safety.

[0028] Furthermore, based on the voltage changes at three different times, the three polarization voltages are distinguished. By calculating the Mahalanobis distance parameter between the three polarization voltage values ​​and the reference polarization voltage value, and judging the voltage deviation based on the Mahalanobis distance parameter, effective information can be extracted from macroscopic feature parameters using the Mahalanobis distance method. This enables accurate battery health detection through simple means, simplifies data analysis, and improves the efficiency and accuracy of battery health detection.

[0029] Furthermore, by not using the SEI film polarization voltage as a reference data, the problem of the SEI film polarization voltage being too small and having too large a deviation can be avoided, which would affect the battery health detection effect. This improves the accuracy and efficiency of battery health detection. At the same time, considering the measurement time and data processing capabilities, it can also improve the general applicability of the battery health detection method.

[0030] Furthermore, it can select any two polarization voltage values ​​as the basis for health detection based on the actual data processing requirements, which provides a certain degree of flexibility and further improves the universal applicability of battery health detection methods. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of the equivalent circuit of a lithium battery according to an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of a battery health detection system according to an embodiment of the present invention;

[0033] Figure 3 This is a flowchart of a battery health detection method according to an embodiment of the present invention;

[0034] Figure 4This is a flowchart of the step in the battery health detection method of the present invention, which determines the voltage deviation value of the battery under test at the current moment based on all polarization voltage values ​​before the current moment.

[0035] Figure 5 This is a line graph showing the number of charging cycles versus the Mahalanobis distance parameter obtained in an actual test scenario according to an embodiment of the present invention.

[0036] Figure 6 This is a dot plot of the charging cycle count versus voltage deviation obtained in an actual test scenario according to an embodiment of the present invention.

[0037] Figure 7 This is a schematic diagram of a battery health detection device according to an embodiment of the present invention;

[0038] Figure 8 This is a schematic diagram of a battery health detection device according to an embodiment of the present invention. Detailed Implementation

[0039] The development of power lithium batteries has gone through three generations of management technologies, centered on threshold protection, state estimation, and safety and lifespan. It is now moving towards full lifecycle and intelligent management using big data. Lithium battery health is a crucial parameter in power lithium battery management technology, serving as a necessary input for determining the driving range of electric vehicles and for state estimation and lifespan prediction at the battery system level. During use, lithium battery capacity decreases to some extent with the increase in charge-discharge cycles, and may even experience severe degradation such as short-circuit lithium plating, posing significant safety hazards. Therefore, lithium battery health status detection is of great significance and has substantial market demand.

[0040] Currently, the most direct and accurate method for obtaining lithium battery health parameters is the direct measurement method, which refers to calculating the amount of charge transferred during the process of a lithium battery going from a "fully charged" state to a "discharged" state. However, in practical applications, due to the uncertainty and incompleteness of the charging and discharging process of lithium batteries, charging is completed by an external charging station, and discharging is dynamically determined by the complexity of driver behavior and the environment, making the direct measurement method unsuitable for engineering applications.

[0041] Lithium-ion battery health testing methods suitable for engineering applications are mainly divided into dynamic and static methods. Dynamic methods are primarily applicable to real-time monitoring scenarios during vehicle operation, while static methods are mainly applicable to after-sales 4S battery maintenance scenarios. The dynamic method involves injecting multiple broadband excitation signals ranging from low frequencies (a few µHz) to high frequencies (a few MHz) into the lithium-ion battery, detecting multiple sets of voltage and current parameters, and generating an EIS (electrochemical impedance spectroscopy) using the change in the ratio of excitation voltage to response current. This EIS analysis is then used to achieve battery health testing. However, this dynamic method is relatively complex and has low efficiency in battery health testing.

[0042] The static method refers to calculating the internal resistance of a lithium battery using open-circuit and heavy-circuit voltages, and then detecting the battery's health based on changes in internal resistance. While simple, the static method lacks sufficient accuracy. For example... Figure 1 As shown, Figure 1 The equivalent circuit of a lithium battery can be assumed, where the electrochemical model of a lithium battery is assumed to be an ohmic resistance and a polarization impedance connected in series, with the polarization impedance appearing as a continuous series RC parallel circuit. Specifically, for lithium batteries, the internal resistance can be divided into ohmic internal resistance Rb, SEI (solid electrolyte interphase) film resistance, electrochemical transfer internal resistance Rct, and diffusion internal resistance W. The values ​​of these four internal resistances vary greatly. Even if the rate of change of the smaller type of internal resistance is large, the rate of change of the total internal resistance may still be relatively small. Therefore, the static method of detecting the health of a lithium battery by measuring its internal resistance has low accuracy.

[0043] As can be seen from the above, current methods for testing the health of lithium batteries suffer from low efficiency and accuracy.

[0044] To address the aforementioned technical problems, this application proposes a battery health detection method, apparatus, device, and system that can improve the efficiency and accuracy of battery health detection.

[0045] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0046] like Figure 2 As shown, the battery health detection system 1000 of this embodiment includes a voltage detection device 1001 and a battery health detection device 1002.

[0047] Voltage detection device 1001 is used to connect to the battery under test to detect the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time. The battery under test may be a lithium battery. Battery health detection device 1002 is connected to voltage detection device 1001 to perform health detection on the battery under test based on the voltage value. Battery health detection device 1002 may be described in the following embodiments and will not be detailed here.

[0048] In one embodiment, the voltage detection device 1001 can be connected to both ends of the battery under test to collect the open-circuit voltage value at a preset time after the charging or discharging operation of the battery under test is completed. Understandably, the voltage value collected after the charging operation or the voltage value collected after the discharging operation is completed can be selected according to the actual application requirements. The preset time can also be selected according to the application requirements and is not limited here.

[0049] In one embodiment, the lithium battery can be charged with a constant current to a preset charging threshold, and then the charging operation can be stopped before its voltage value is collected. The preset charging threshold can be set according to actual conditions, including but not limited to 20% SOC, 50% SOC, or 100% SOC, etc., and is not limited here. For example, in the application scenario of lithium battery health testing before shipment, in order to reduce losses and costs, lithium batteries are generally not fully charged before shipment. In this case, charging to 50% SOC can be selected to complete the battery health test. The constant current used for charging the lithium battery can also be selected according to actual conditions, including but not limited to 1C, 2C, or 3C.

[0050] In one embodiment, the battery health monitoring system 1000 may further include an alarm device ( Figure 2 (Not shown), which is connected to the battery health detection device 1002, is used to receive an alarm signal fed back by the battery health detection device 1002 when the battery health detection device 1002 determines that the battery under test has a health problem, and to perform an alarm operation to provide timely warning before a safety problem occurs in the lithium battery. It is understood that the alarm device may be a speaker, indicator light, or audible and visual alarm, etc., and is not limited here.

[0051] The battery health detection system in this embodiment can achieve fast and convenient battery health detection, solving the problems of low efficiency and accuracy in battery health detection. The battery health detection method implemented by the battery health detection device in the battery health detection system will be described in detail below.

[0052] like Figure 3 As shown, the battery health detection method of this invention includes:

[0053] Step 110: Obtain the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time.

[0054] The system acquires the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time. In other words, it acquires the historical charging / discharging voltage detection data of the battery under test. This historical charging / discharging voltage detection data is used to detect the current (i.e., current) battery health status of the battery under test without the need for multiple applications of external broadband excitation signals, thus providing a basis for accurate and rapid detection of battery health status.

[0055] Step 120: Based on the voltage value at a preset time, determine the polarization voltage value of the battery under test after each charging / discharging operation.

[0056] In one embodiment, based on the correspondence between voltage response time and different types of polarization voltages during the relaxation process of a lithium battery, different types of polarization voltages, such as ohmic polarization voltage, SEI film polarization voltage, electrochemical transfer polarization voltage, or diffusion polarization voltage, can be obtained by collecting voltage values ​​at different preset times. Specifically, the relaxation process of a lithium battery can reflect the degradation mechanism of the lithium battery. The resting voltage of the lithium battery after the current is cut off can be used as a characteristic parameter. The characteristic parameters at different relaxation times can characterize the internal resistance and capacitance of the lithium battery. That is, by collecting characteristic parameters at different relaxation times, various polarization voltage values ​​can be obtained, and it is not limited by the lithium battery charging strategy.

[0057] Specifically, the specific value of the preset time can be selected according to the actual situation and is not limited here. The preset time can be set according to the relaxation time corresponding to the polarization voltage. The relaxation time can be related to factors such as the material, ratio or process of the battery to be tested.

[0058] Step 130: Based on all polarization voltage values ​​prior to the current moment, determine the voltage deviation of the battery under test at the current moment.

[0059] Based on all polarization voltage values ​​determined after each charge / discharge operation prior to the current moment, the voltage deviation of the battery under test at the current moment is determined. The voltage deviation can be used to characterize the degree of loss of the battery under test; the larger the voltage deviation, the more severe the loss.

[0060] Step 140: Determine the battery health status of the battery under test based on the voltage deviation value.

[0061] The battery health status of the battery under test is determined based on the voltage deviation value. In one embodiment, a health problem of the battery under test can be determined when the voltage deviation value is greater than a deviation threshold. The deviation threshold can be set according to the actual application scenario and the hardware conditions of the battery under test. For example, when the hardware conditions of the battery under test are good or the safety requirements of the application scenario are low, a higher deviation threshold can be set, generally between 3 and 5.

[0062] This embodiment can obtain the corresponding polarization voltages based on the correspondence between voltage response time and different types of polarization voltages during the relaxation process of a lithium battery. By collecting voltage values ​​at different preset times after the charging / discharging operation of the battery under test, it can determine the voltage deviation value using all polarization voltage values ​​before the current time, thereby realizing the detection of the battery health status. This embodiment only requires segmented voltage detection at a few preset times to distinguish polarization voltages, enabling the detection of battery health status. While ensuring the accuracy of battery health detection, it has the advantages of simplicity and speed, avoiding complex data analysis, making battery health detection faster and more efficient, and greatly improving the efficiency and accuracy of battery health detection. Moreover, it can perform health status detection without applying multiple high-frequency or low-frequency currents to the battery under test, without causing damage to the battery, achieving non-destructive testing and having the advantage of safety.

[0063] The following is a further explanation of the embodiment of step 120, which describes the step of determining the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at a preset time.

[0064] From the above Figure 1 It is known that the internal resistance of a lithium battery can be divided into ohmic internal resistance, SEI film resistance, electrochemical transfer internal resistance, and diffusion internal resistance. Correspondingly, the polarization voltage can be divided into ohmic polarization voltage, SEI film polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage. This embodiment does not use the SEI film polarization voltage as reference data, but only selects to collect ohmic polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage as the basis for battery health detection. This avoids the problem of the SEI film polarization voltage being too small and having too large a deviation, which would affect the battery health detection effect, thereby improving the accuracy and efficiency of battery health detection. Furthermore, considering measurement time and data processing capabilities, it also improves the general applicability of the battery health detection method.

[0065] In one embodiment, the preset time may include a preset millisecond time, a preset second time, and a preset long time. Correspondingly, the polarization voltage value may include an ohmic polarization voltage value, an electrochemical transfer polarization voltage value, and a diffusion polarization voltage value. In this case, step 120 may specifically include: determining the voltage value at the preset millisecond time as the ohmic polarization voltage value; determining the difference between the voltage value at the preset second time and the voltage value at the preset millisecond time as the electrochemical transfer polarization voltage value; and determining the difference between the voltage value at the preset long time and the voltage value at the preset second time as the diffusion polarization voltage value.

[0066] In other words, the ohmic polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage can be calculated using the following formulas (4)-(6):

[0067] V(ax)=V1 (4)

[0068] V(bx)=V2-V1 (5)

[0069] V(cx)=V3-V2 (6)

[0070] In equations (4)-(6) above, V(ax) is the ohmic polarization voltage of the battery to be tested after the xth charge / discharge operation, V1 is the voltage value at a preset millisecond time, V(bx) is the electrochemical transfer polarization voltage of the battery to be tested after the xth charge / discharge operation, V2 is the voltage value at a preset second time, V(cx) is the diffusion polarization voltage of the battery to be tested after the xth charge / discharge operation, and V3 is the voltage value at a preset long time.

[0071] Based on the elimination rate of polarization in lithium batteries, ohmic polarization disappears instantaneously, and its corresponding preset time can be in the millisecond range, such as 1 millisecond; electrochemical transfer polarization disappears approximately in the second range, and its corresponding preset time can be in the second range, such as 1 second; diffusion polarization disappears over tens of seconds or even several hours, and its corresponding preset time can be a long preset time, such as 10 seconds. Understandably, the specific values ​​of each preset time can be selected according to actual conditions. The value range for preset millisecond-level times can be 0.1 milliseconds to 10 milliseconds, the value range for preset second-level times can be 0.1 seconds to 10 seconds, and the value range for preset long preset times can be 10 seconds to 100 seconds, without any limitation here.

[0072] In one embodiment, the preset time may include a preset millisecond-level time and a preset second-level time. Correspondingly, the polarization voltage value may include an ohmic polarization voltage value and an electrochemical transfer polarization voltage value. Step 120 may specifically include: determining the voltage value at the preset millisecond-level time as the ohmic polarization voltage value, corresponding to equation (4) above; and determining the difference between the voltage value at the preset second-level time and the voltage value at the preset millisecond-level time as the electrochemical transfer polarization voltage value, corresponding to equation (5) above. In other words, only the ohmic polarization voltage value and the electrochemical transfer polarization voltage value can be collected as the basis for battery health detection to further improve the efficiency of battery health detection. Whether two or three polarization voltages are used as the detection basis can be selected according to actual needs and is not limited here.

[0073] The following description further explains the step 130 in the above embodiment, which involves determining the voltage deviation of the battery under test at the current moment based on all polarization voltage values ​​prior to the current moment. Figure 4 As shown, step 130 may specifically include:

[0074] Step 131: Based on the polarization voltage value of the battery under test after the first charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation, determine multiple Mahalanobis distance parameters.

[0075] Based on the polarization voltage value of the battery under test after the first charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation, multiple Mahalanobis distance parameters are determined. These Mahalanobis distance parameters can be used to characterize the voltage change of each charge / discharge operation compared to the first charge / discharge operation from the perspective of multiple polarization voltages.

[0076] In one embodiment, when the polarization voltage value includes an ohmic polarization voltage value and an electrochemical transfer polarization voltage value, step 131 may include: determining the Mahalanobis distance parameter corresponding to the battery to be tested after each subsequent charge / discharge operation using the following formula (1):

[0077]

[0078] Wherein, D(x) is the Mahalanobis distance parameter of the battery under test after the xth charge / discharge operation, V(ax) is the ohmic polarization voltage of the battery under test after the xth charge / discharge operation, V(a0) is the ohmic polarization voltage of the battery under test after the first charge / discharge operation, V(bx) is the electrochemical transfer polarization voltage of the battery under test after the xth charge / discharge operation, and V(bx) is the electrochemical transfer polarization voltage of the battery under test after the first charge / discharge operation.

[0079] In one embodiment, when the polarization voltage value includes an ohmic polarization voltage value, an electrochemical transfer polarization voltage value, and a diffusion polarization voltage value, step 131 may include: determining the Mahalanobis distance parameter corresponding to the battery to be tested after each subsequent charge / discharge operation using the following formula (2):

[0080]

[0081] Wherein, V(cx) is the diffusion polarization voltage of the battery under test after the xth charge / discharge operation, and V(c0) is the diffusion polarization voltage of the battery under test after the first charge / discharge operation.

[0082] In one embodiment, when the polarization voltage value includes an ohmic polarization voltage value, an electrochemical transfer polarization voltage value, and a diffusion polarization voltage value, that is, in step 120 above, the three polarization voltage values ​​of the ohmic polarization voltage value, the electrochemical transfer polarization voltage value, and the diffusion polarization voltage value are collected and determined. Any two polarization voltage values ​​can also be selected from the three polarization voltage values ​​to determine the Mahalanobis distance parameter, which can be selected according to the actual situation. In other words, step 131 may include: using formula (1) above, formula (7) below, or formula (8) below to determine the Mahalanobis distance parameter corresponding to the battery to be tested after each subsequent charge / discharge operation.

[0083]

[0084]

[0085] Step 132: Determine the voltage deviation based on all Mahalanobis distance parameters.

[0086] In one embodiment, step 132 may include: determining the voltage deviation value using the following formula (3):

[0087]

[0088] Where N is the voltage deviation value, and Y is the total number of charging / discharging operations of the battery under test before the current moment.

[0089] The following section uses lithium battery testing data obtained in actual test scenarios to illustrate the effectiveness of the battery health testing method described in the above embodiments. The testing data refers to the data obtained by testing the battery health status of lithium batteries using the battery health testing method described in the above embodiments.

[0090] First, as shown in Table 1 below, Table 1 contains the test data obtained after the lithium battery has undergone 1000 1C charging cycles. The test data in Table 1 includes the ohmic polarization voltage value Va, the electrochemical transfer polarization voltage value Vb, the diffusion polarization voltage value Vc, and the Mahalanobis distance parameter Dx.

[0091] Table 1. Test data of lithium batteries after 1000 1C charging cycles.

[0092]

[0093]

[0094] From the data in Table 1 above, we can further analyze and obtain the following: Figure 5 The line graph shown is a graph of the number of charging cycles versus the Mahalanobis distance parameter (Dx), and as shown... Figure 6The graph shows the number of charging cycles versus voltage deviation (N). Among them, [the graph is composed of...]. Figure 5 It can be seen that the Mahalanobis distance parameter of a lithium battery increases sharply after 700 charging cycles. Figure 6 It can be seen that after 700 charging cycles, the voltage deviation of the lithium battery exceeds the deviation threshold of 3, indicating that the lithium battery health has significant problems after 700 charging cycles. To further verify the accuracy of the data on the Mahalanobis distance parameter and voltage deviation, lithium batteries of the same model were disassembled after 700 charging cycles under the same conditions. It was found that the lithium batteries did indeed exhibit significant lithium plating, which demonstrates that the battery health detection method described in the above embodiments has a good detection effect on lithium batteries.

[0095] This embodiment distinguishes three polarization voltages based on voltage changes at three different times. It calculates the Mahalanobis distance between the three polarization voltage values ​​and a reference polarization voltage value, and determines voltage deviations based on this distance. By extracting effective information from macroscopic feature parameters using the Mahalanobis distance method, it achieves accurate battery health detection through simple means, simplifying data analysis and improving the efficiency and accuracy of battery health detection. Furthermore, by not using the SEI film polarization voltage as reference data, it avoids the problem of excessively small or large deviations in the SEI film polarization voltage affecting the battery health detection effect, thereby improving the accuracy and efficiency of battery health detection. Considering measurement time and data processing capabilities, it also improves the universality of the battery health detection method. In addition, it allows selection of any two polarization voltage values ​​as the basis for health detection based on actual data processing requirements, providing flexibility and further enhancing the universality of the battery health detection method.

[0096] like Figure 7 As shown, the battery health detection device 700 of this embodiment includes an acquisition module 701, a polarization voltage determination module 702, a deviation determination module 703, and a health status determination module 704.

[0097] The acquisition module 701 is used to acquire the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time; the polarization voltage determination module 702 is used to determine the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time; the deviation determination module 703 is used to determine the voltage deviation value of the battery under test at the current time based on all polarization voltage values ​​before the current time; and the health status determination module 704 is used to determine the battery health status of the battery under test based on the voltage deviation value.

[0098] Specifically, the battery health detection device 700 may be a device that integrates a processor and memory (i.e., a subsequent battery health detection device).

[0099] It should be noted that the battery health detection device 700 provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and the corresponding method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the corresponding method embodiments, which will not be repeated here.

[0100] One embodiment of the present invention also provides a battery health detection device, which includes a processor and a memory. The memory stores at least one instruction or at least one program, which is loaded and executed by the processor to implement the battery health detection method provided in the above method embodiments.

[0101] Memory is used to store software programs and modules. The processor executes these stored software programs and modules to perform various functional applications and data processing. Memory can primarily consist of a program storage area and a data storage area. The program storage area stores the operating system, application programs required for functionality, etc.; the data storage area stores data created based on device usage, etc. Furthermore, memory can include high-speed random access memory (RAM) and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory can also include a memory controller to provide the processor with access to the memory.

[0102] In one specific embodiment Figure 8 A schematic diagram of the structure for implementing the battery health detection device provided in the embodiments of the present invention is shown. The battery health detection device can be a computer terminal, a mobile terminal or other devices. The battery health detection device can also participate in or include the battery health detection device 700 provided in the embodiments of the present invention.

[0103] like Figure 8 As shown, this embodiment of the invention provides a battery health detection device 800, including a processor 801 and a memory 802. The memory 802 stores computer program instructions, wherein when the computer program instructions are executed by the processor, the processor 801 executes the battery health detection method as described in the above embodiment.

[0104] Furthermore, such as Figure 8As shown, the battery health monitoring device 800 also includes a network interface 803, an input device 804, a hard disk 805, and a display device 806.

[0105] The various interfaces and devices described above can be interconnected via a bus architecture. The bus architecture can include any number of interconnecting buses and bridges. Specifically, various circuits representing one or more central processing units (CPUs), represented by processor 801, and one or more memories, represented by memory 802, are connected together. The bus architecture can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits. It is understood that the bus architecture is used to implement communication between these components. In addition to the data bus, the bus architecture also includes a power bus, a control bus, and a status signal bus, which are well known in the art and will not be described in detail herein.

[0106] The network interface 803 can be connected to a network (such as the Internet, a local area network, etc.), obtain relevant data from the network, and save it to the hard disk 805.

[0107] The input device 804 can receive various instructions input by the operator and send them to the processor 801 for execution. The input device 804 may include a keyboard or a clicking device, such as a mouse, trackball, touchpad, or touch screen.

[0108] The display device 806 can display the results obtained by the processor 801 executing instructions.

[0109] The memory 802 is used to store programs and data necessary for the operation of the operating system, as well as intermediate results and other data during the calculation process of the processor 801.

[0110] It is understood that the memory 802 in the embodiments of the present invention may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. The memory 802 of the apparatus and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0111] In some implementations, memory 802 stores elements such as executable modules or data structures, or subsets thereof, or extended sets thereof: operating system 8021 and application programs 8022.

[0112] The operating system 8021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 8022 includes various applications, such as a browser, used to implement various application functions. The program implementing the method of this embodiment can be included in the application program 8022.

[0113] When the processor 801 calls and executes the application program and data stored in the memory 802, specifically the program or instructions stored in the application program 8022, it executes the battery health detection method as described in the above embodiments.

[0114] The methods disclosed in the above embodiments of the present invention can be applied to processor 801, or implemented by processor 801. Processor 801 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 801 or by instructions in software form. The processor 801 may be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), off-the-shelf programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, and can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 802, and processor 801 reads the information in memory 802 and completes the steps of the above method in combination with its hardware.

[0115] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0116] For software implementation, the techniques described herein can be achieved through modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented within the processor or externally.

[0117] In addition, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the battery health detection method as described in the above embodiments.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0119] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can be physically comprised separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware or in the form of hardware plus software functional units.

[0120] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute some steps of the transmission and reception methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0121] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A battery health detection method, characterized in that, Includes the following steps: Obtain the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time; Based on the voltage value at the preset time, the polarization voltage value of the battery under test is determined after each charging / discharging operation, wherein the polarization voltage value includes at least two of the following: ohmic polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage. Based on all polarization voltage values ​​prior to the current moment, determine the voltage deviation of the battery under test at the current moment; Based on the voltage deviation value, the battery health status of the battery to be tested is determined; The step of determining the voltage deviation of the battery under test at the current moment based on all polarization voltage values ​​prior to the current moment includes: Based on the polarization voltage value of the battery under test after the first charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation, multiple Mahalanobis distance parameters are determined. The voltage deviation value is determined based on all Mahalanobis distance parameters.

2. The battery health detection method according to claim 1, characterized in that, When the preset time includes a preset millisecond-level time and a preset second-level time, and the polarization voltage value includes an ohmic polarization voltage value and an electrochemical transfer polarization voltage value, the step of determining the polarization voltage value of the battery under test after each charge / discharge operation based on the voltage value at the preset time includes: The voltage value at the preset millisecond time is determined as the ohmic polarization voltage value; The difference between the voltage value at the preset second-level time and the voltage value at the preset millisecond-level time is determined as the electrochemical transfer polarization voltage value.

3. The battery health detection method according to claim 2, characterized in that, The step of determining multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the initial charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation includes: The Mahalanobis distance parameter corresponding to the battery under test after each subsequent charge / discharge operation is determined using the following formula (1): （1） Wherein, D(x) is the Mahalanobis distance parameter of the battery under test after the xth charge / discharge operation, V(ax) is the ohmic polarization voltage of the battery under test after the xth charge / discharge operation, V(a0) is the ohmic polarization voltage of the battery under test after the first charge / discharge operation, V(bx) is the electrochemical transfer polarization voltage of the battery under test after the xth charge / discharge operation, and V(b0) is the electrochemical transfer polarization voltage of the battery under test after the first charge / discharge operation.

4. The battery health detection method according to claim 1, characterized in that, When the preset time includes a preset millisecond-level time, a preset second-level time, and a preset long time, and the polarization voltage value includes an ohmic polarization voltage value, an electrochemical transfer polarization voltage value, and a diffusion polarization voltage value, the step of determining the polarization voltage value of the battery under test after each charge / discharge operation based on the voltage value at the preset time includes: The voltage value at the preset millisecond time is determined as the ohmic polarization voltage value; The difference between the voltage value at the preset second-level time and the voltage value at the preset millisecond-level time is determined as the electrochemical transfer polarization voltage value; The difference between the voltage value at the preset long time and the voltage value at the preset second time is determined as the diffusion polarization voltage value.

5. The battery health detection method according to claim 4, characterized in that, The step of determining multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the initial charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation includes: The Mahalanobis distance parameter corresponding to the battery under test after each subsequent charge / discharge operation is determined using the following formula (2): （2） Wherein, D(x) is the Mahalanobis distance parameter of the battery under test after the x-th charge / discharge operation, V(ax) is the ohmic polarization voltage of the battery under test after the x-th charge / discharge operation, V(a0) is the ohmic polarization voltage of the battery under test after the first charge / discharge operation, V(bx) is the electrochemical transfer polarization voltage of the battery under test after the x-th charge / discharge operation, V(b0) is the electrochemical transfer polarization voltage of the battery under test after the first charge / discharge operation, V(cx) is the diffusion polarization voltage of the battery under test after the x-th charge / discharge operation, and V(c0) is the diffusion polarization voltage of the battery under test after the first charge / discharge operation.

6. The battery health detection method according to claim 3 or 5, characterized in that, The step of determining the voltage deviation value based on all Mahalanobis distance parameters includes: The voltage deviation value is determined using the following formula (3): （3） Wherein, N is the voltage deviation value, and Y is the total number of charging / discharging operations of the battery under test before the current moment.

7. The battery health detection method according to claim 1, characterized in that, The step of determining the battery health status of the battery under test based on the voltage deviation value includes: When the voltage deviation exceeds the deviation threshold, it is determined that the health of the battery under test has a problem.

8. A battery health detection device, characterized in that, include: The acquisition module is used to acquire the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time. The polarization voltage determination module is used to determine the polarization voltage value of the battery under test after each charging / discharging operation based on the voltage value at the preset time. The polarization voltage value includes at least two of the following: ohmic polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage. The deviation determination module is used to determine the voltage deviation value of the battery under test at the current moment based on all polarization voltage values ​​before the current moment; The deviation determination module is used to determine multiple Mahalanobis distance parameters based on the polarization voltage value of the battery under test after the first charge / discharge operation and the polarization voltage value after each subsequent charge / discharge operation. The voltage deviation value is determined based on all Mahalanobis distance parameters; A health status determination module is used to determine the battery health status of the battery under test based on the voltage deviation value.

9. A battery health testing device, characterized in that, include: processor; and a memory, in which computer program instructions are stored. When the computer program instructions are executed by the processor, the processor performs the battery health detection method as described in any one of claims 1-7.

10. A battery health detection system, characterized in that, include: A voltage detection device is used to connect to the battery under test to detect the voltage value of the battery under test at a preset time after each charging / discharging operation before the current time. A battery health testing device is connected to the voltage testing device to perform health testing on the battery to be tested based on the voltage value, wherein the battery health testing device is the battery health testing device according to claim 9.

11. The battery health detection system according to claim 10, characterized in that, Also includes: An alarm device, connected to the battery health detection device, is used to receive an alarm signal from the battery health detection device and perform an alarm operation when the battery health detection device determines that the battery under test has a health problem.

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