Battery health state detection method and system

Abstract

The invention relates to a battery health state detection method and system, and relates to the technical field of battery management analysis, and the method comprises the steps: carrying out the fitting compensation according to real-time discharge state data and historical discharge state data in the discharge process of a target battery, and obtaining a target discharge state curve, performing curve change analysis by using the target discharge state curve and the initial state curve to obtain an attenuation change key point, and performing attenuation calculation according to the attenuation change key point to obtain a health state detection result of the target battery; in the charging process of a target battery, charging state fitting is performed by using real-time charging state data and historical charging state data to obtain a target charging state curve in different charging stages, and comparison analysis is performed according to the target charging state curve and an initial state curve to obtain a health state detection result. According to the invention, the health state of the battery can be accurately detected when the battery is in the charging / discharging state, and the detection efficiency and accuracy are improved.

Description

Technical Field

[0001] The present application relates to the technical field of battery management analysis, and in particular to a battery health status detection method and system. Background Art

[0002] At present, with the rapid development of science and technology, large-capacity batteries are widely used. However, the safety of large-capacity batteries has received continuous attention, which involves personal and property safety. With the increase of usage time, large-capacity batteries will age and decay. When the battery decays severely, it may cause dangers such as overcharge and explosion. Therefore, it is extremely important to pay attention to the health status of the battery in time.

[0003] Existing battery health status detection methods usually use the complete charge and discharge cycle data stored in the BMS to evaluate and determine the battery health status. However, in actual use, users do not perform a complete charge and discharge cycle most of the time. For example, when charging, users may only charge to 90% and then stop charging. At this time, the charging cycle data is incomplete. Using incomplete data to directly evaluate the battery health will result in large errors and cannot accurately detect the actual battery health status. Summary of the invention

[0004] The present application provides a battery health status detection method and system, which utilizes historical charge / discharge data, real-time data, and initial charge / discharge data for fitting, and can accurately detect the actual health status of the battery when the battery is in a charging state or a discharging state, thereby improving the detection efficiency and accuracy of the battery health status, and solving the problem that the existing battery health status detection method is limited by incomplete historical charge / discharge data and cannot accurately detect the actual health status of the battery.

[0005] In a first aspect, the present application provides a battery health status detection method, comprising:

[0006] Acquire an initial state curve of a target battery, and periodically collect historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data;

[0007] During the discharge process of the target battery, fitting compensation is performed according to the real-time discharge state data of the target battery and the historical discharge state data to obtain a target discharge state curve;

[0008] Performing curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points;

[0009] Perform attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery;

[0010] During the charging process of the target battery, charging state fitting is performed according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage, and a constant voltage stage;

[0011] For each of the charging stages, a comparison analysis is performed based on the target charging state curve and the initial charging state curve to obtain a health status detection result of the target battery.

[0012] Optionally, performing fitting compensation according to the real-time discharge state data of the target battery and the historical discharge state data to obtain a target discharge state curve includes:

[0013] Analyze the real-time discharge state data and the historical discharge state data respectively to obtain the characteristic points and missing points of the power change;

[0014] According to the electric quantity change characteristic point and the missing point, the real-time discharge state data and the historical discharge state data are fitted and compensated to obtain a target discharge state curve.

[0015] Optionally, performing curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points includes:

[0016] Performing an offset analysis based on the initial discharge state curve and the target discharge state curve to obtain curve offset information;

[0017] Performing trend analysis according to the curve offset information to obtain a curve change trend, wherein the curve change trend is used to characterize an attenuation change of the target discharge state curve relative to the initial discharge state curve;

[0018] According to the curve change trend, key point change analysis is performed to obtain attenuation change key points.

[0019] Optionally, performing key point change analysis according to the curve change trend to obtain attenuation change key points includes:

[0020] Determining key change segments in the initial discharge state curve and the target discharge state curve according to the curve change trend;

[0021] A voltage difference analysis is performed on each change point in the key change section to obtain a voltage difference change point, and the voltage difference change point is used as the attenuation change key point.

[0022] Optionally, performing attenuation calculation according to the attenuation change key point to obtain the health status detection result of the target battery includes:

[0023] Obtaining a complete aging curve of the target battery during a discharge cycle;

[0024] Performing difference calculation based on the initial discharge state curve and the complete aging curve to obtain a complete aging difference;

[0025] Performing difference calculation based on the key points of attenuation change to obtain a real-time aging difference, wherein the real-time aging difference is used to characterize the voltage attenuation of the target battery during this discharge process;

[0026] An aging comparison is performed based on the real-time aging difference and the complete aging difference to obtain a health status detection result of the target battery.

[0027] Optionally, performing difference calculation based on the attenuation change key points to obtain the real-time aging difference includes:

[0028] For each of the attenuation change key points, a difference calculation is performed using the initial discharge state curve and the real-time discharge state curve to obtain an attenuation difference corresponding to each of the attenuation change key points;

[0029] The real-time aging difference is obtained by performing calculation based on the attenuation difference.

[0030] Optionally, performing charging state fitting according to the real-time charging state data and the historical charging state data of the target battery to obtain a target charging state curve of the target battery in at least one charging stage includes:

[0031] Performing current and voltage analysis according to the real-time charging state data to obtain at least one charging stage, and performing fitting compensation using the real-time charging state data and the historical charging state data to obtain a complete charging state curve;

[0032] The charging stage is matched in the complete charging state curve to obtain a target charging state curve of the target battery in the charging stage.

[0033] Optionally, for each of the charging stages, comparing and analyzing the target charging state curve and the initial charging state curve to obtain a health state detection result of the target battery includes:

[0034] Performing charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage;

[0035] An aging analysis is performed based on the attenuation change to obtain a health status detection result of the target battery.

[0036] Optionally, performing charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage includes:

[0037] For each of the charging stages, using the target state of charge curve and the initial state of charge curve to perform decay point analysis to obtain slope key points;

[0038] Analyze and calculate the slope key points to obtain slope information corresponding to the charging stage;

[0039] An attenuation comparison is performed according to the slope information to obtain the attenuation change of the target battery.

[0040] In a second aspect, the present application provides a battery health status detection system, comprising:

[0041] A state curve and state data acquisition module, used to acquire an initial state curve of a target battery, and periodically collect historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data;

[0042] A fitting compensation module, used for performing fitting compensation according to the real-time discharge state data and the historical discharge state data of the target battery during the discharge process of the target battery to obtain a target discharge state curve;

[0043] A curve change analysis module, used to perform curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points;

[0044] An attenuation calculation module, used to perform attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery;

[0045] a charging state fitting module, used for performing charging state fitting according to the real-time charging state data and the historical charging state data of the target battery during the charging process of the target battery, so as to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage and a constant voltage stage;

[0046] The comparison and analysis module is used to compare and analyze the target charging state curve and the initial charging state curve for each charging stage to obtain a health state detection result of the target battery.

[0047] In summary, the embodiment of the present application utilizes the acquired initial charge / discharge state curve and historical charge / discharge state data of the target battery, and during the discharge process of the target battery, performs fitting compensation according to the real-time discharge data and the historical discharge data to obtain the target discharge state curve, and then performs curve change analysis according to the initial discharge state curve and the target discharge state curve to obtain the attenuation change key points, performs attenuation calculation according to the attenuation change key points, and obtains the health status detection result; during the charging process, performs charging state fitting according to the real-time charging state data and the historical charging state data to obtain the target charging state curve under at least one charging stage, and then for each charging stage, performs comparison and analysis according to the target charging state curve and the initial charging state curve to obtain the health status detection result of the target battery. It can be seen that the embodiments of the present application reasonably fit the historical charging data, real-time data and initial data, and use the real-time charging and discharging data to accurately evaluate the actual health status. The real-time charging and discharging data is fitted with the historical charging and discharging data to avoid the problem of insufficient detection accuracy caused by the data. When the battery is in a charging state or a discharging state, the actual health status of the battery can be accurately detected, thereby improving the detection efficiency and accuracy of the battery health status, and solving the problem that the existing battery health status detection method is limited by incomplete historical charging and discharging data and cannot accurately detect the actual health status of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0050] Figure 1 A flowchart of a battery health status detection method provided in an embodiment of the present application;

[0051] Figure 2 It is a schematic diagram of the steps of a battery health status detection method provided by an optional embodiment of the present application;

[0052] Figure 3It is a battery BOL curve and EOL curve deviation trend comparison diagram provided by an optional example of the present application;

[0053] Figure 4 is a flowchart of a method for detecting the health status of a battery during a discharge process provided by an optional example of the present application;

[0054] Figure 5 An optional example of the present application provides a BOL curve and an EOL curve diagram obtained by actually testing a battery;

[0055] Figure 6 It is a charging state curve diagram of a battery in a normal state provided by an optional example of the present application;

[0056] Figure 7 It is an optional example of the present application, which provides a comparison diagram of a standard charging state curve and a real-time charging state curve at different charging stages;

[0057] Figure 8 It is a comparison diagram of key data in a standard charging state curve and a real-time charging state curve at different charging stages provided by an optional example of the present application;

[0058] Fig. 9 It is a trickle stage charging state curve comparison diagram provided by an optional example of the present application;

[0059] Fig.10 It is a comparison diagram of charging state curves in a constant current stage provided by an optional example of the present application;

[0060] Fig.11 It is a comparison diagram of charging state curves in a constant voltage stage provided by an optional example of the present application;

[0061] Fig.12 A structural block diagram of a battery health status detection system provided in an embodiment of the present application;

[0062] Fig.13 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0064] To facilitate the understanding of the embodiments of the present application, further explanation will be given below in conjunction with the drawings and specific embodiments. The embodiments do not constitute a limitation on the embodiments of the present application.

[0065] Figure 1 The flowchart of a battery health status detection method provided in an embodiment of the present application is shown in FIG. In a specific implementation, the battery health status detection method provided in this embodiment can be applied to the health assessment of various large-capacity batteries. Figure 1 As shown, the battery health status detection method provided in the embodiment of the present application may specifically include the following steps:

[0066] Step 110, obtaining an initial state curve of a target battery, and periodically collecting historical charge and discharge state data of the target battery.

[0067] The initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data.

[0068] Specifically, the target battery may include but is not limited to various lithium batteries, storage batteries, etc. The initial state curve is mainly composed of various state data of the battery when it leaves the factory, and is used to characterize the state curve of the target battery at the beginning of life (BOL). Among them, the initial charging state curve can be applied to the charging process of the target battery, combined with multiple real-time state data for health status detection; the initial discharge state curve can be applied to the discharge process of the target battery, combined with multiple real-time state data for health status detection.

[0069] In this embodiment, the target battery may be built with a BMS (Battery Management System), and the BMS periodically collects and stores the charge / discharge data during the charging and discharging stages of the target battery as historical charge / discharge state data. The historical charge / discharge state data may be divided into historical charge state data and historical discharge state data, and the historical charge / discharge state data is mainly used to evaluate the historical attenuation of the target battery.

[0070] It should be noted that, in this embodiment, the initial charge / discharge state curve, the historical charge / discharge state data and the real-time charge / discharge state data may all include relevant data of the corresponding states, such as mainly including but not limited to: voltage, current, temperature, internal resistance, capacity and number of cycles, etc.

[0071] Step 120 , during the discharge process of the target battery, fitting compensation is performed according to the real-time discharge state data and the historical discharge state data of the target battery to obtain a target discharge state curve.

[0072] In this embodiment, the historical discharge state data may include various state data corresponding to multiple discharge cycles. Similarly, the historical charge state data may also include various state data corresponding to multiple charge cycles.

[0073] This embodiment uses the current discharge time as a reference, and uses the last discharge state data closest to the current discharge time (preferably, the discharge state data is the state data of the last complete discharge cycle) as the discharge state data that fits the real-time discharge state data. Specifically, based on the real-time discharge state data, the algorithm is used to fit the historical discharge state data, mainly including fitting the data with obvious errors or missing in the real-time discharge state data, combining the real-time discharge state data and the historical discharge state data, and constructing a fitted SOC (State of Charge) -OCV (Open Circuit Voltage) curve.

[0074] Step 130 , performing curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points.

[0075] Step 140 , performing attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery.

[0076] A unified description of steps 130 to 140 is given as follows:

[0077] In a specific implementation, this embodiment can compare and analyze the initial discharge state curve and the target discharge state curve. Generally speaking, when the battery decays, there is a large difference between its SOC-OCV curve and the initial state curve. Therefore, the embodiment of the present application can set the initial discharge state curve and the target discharge state curve in the same view, compare them, and analyze the close points and deviation points between the two state curves. Specifically, for the points with deviations, as the key points of attenuation change, the attenuation calculation is performed according to the key points of attenuation change, and the OCV values ​​of the key points of attenuation change in the target discharge state curve are determined respectively. The OCV difference between the key points of attenuation change is calculated according to the OCV data, and the actual attenuation of the target battery (or the degree of aging) is obtained according to the OCV difference, as the health status detection result. Among them, the actual attenuation of the target battery can be divided into mild attenuation, moderate attenuation and severe attenuation, etc., and each degree of attenuation can also additionally include the corresponding attenuation value, such as when the attenuation value is 50% (percentage), it means that the battery is aged by 50%.

[0078] Therefore, for the target battery in the discharge process, this embodiment combines the initial discharge state curve, historical discharge state data and real-time discharge state data, performs fitting compensation and change analysis, and finally obtains accurate health status detection results, thereby achieving fast and accurate detection of the health status of the battery during discharge.

[0079] Step 150 , during the charging process of the target battery, charging state fitting is performed according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage.

[0080] Wherein, the charging stage includes at least one of a trickle current stage, a constant current stage and a constant voltage stage;

[0081] In a complete charging cycle, the battery charging process may generally include but is not limited to: trickle charging (corresponding to the trickle stage), constant current charging (corresponding to the constant current stage) and constant voltage charging (corresponding to the constant voltage stage). For example, the target battery may be first trickle charged, then constant current charged (at this time the battery voltage increases rapidly), and finally constant voltage charged (at this time the battery power is close to saturation, charging slowly, and the current gradually decreases until the charging current is reduced to 0).

[0082] Similar to the fitting compensation of the discharge process, this embodiment takes the current charging time as the reference, and uses the last charging state data closest to the current charging time (preferably, the charging state data is the state data of the last complete charging cycle) as the charging state data fitted with the real-time charging state data. Taking the real-time charging state data as the reference, the algorithm and the historical charging state data are used to fit the data with obvious errors or omissions in the real-time charging state data, and the real-time charging state data and the historical charging state data are combined to obtain the fitted charging state data. Subsequently, the fitted charging state data is analyzed for the above three charging stages respectively, and the charging time, charging current (Current), OCV and SOC corresponding to each charging stage are determined, and the target charging state curve corresponding to at least one charging stage is obtained.

[0083] Step 160 , for each of the charging stages, a comparison analysis is performed based on the target charging state curve and the initial charging state curve to obtain a health status detection result of the target battery.

[0084] In this embodiment, for each charging stage, this embodiment can compare and analyze the target charging state curve corresponding to the charging stage with the state curve corresponding to the charging stage in the initial charging state curve, so as to obtain the health status detection result of the target battery.

[0085] In a specific implementation, when the battery ages or becomes abnormal, the target charging state curve will be significantly different from the initial charging state curve, which is numerically represented by quickly reaching the maximum voltage value and being unable to charge, or quickly entering the constant voltage charging mode, with the current gradually decreasing. Therefore, this embodiment determines whether the battery is aged and decayed by detecting the battery charging voltage, capacity, and time changes with the standard charging curve, thereby obtaining a health status detection result.

[0086] It can be seen that the embodiment of the present application utilizes the acquired initial state curve and historical charge and discharge state data of the target battery, and during the discharge process of the target battery, performs fitting compensation according to the real-time discharge data and the historical discharge data to obtain the target discharge state curve, and then performs curve change analysis according to the initial discharge state curve and the target discharge state curve to obtain the attenuation change key points, performs attenuation calculation according to the attenuation change key points, and obtains the health state detection result; during the charging process, the charging state is fitted according to the real-time charging state data and the historical charging state data to obtain the target charging state curve under at least one charging stage, and then for each charging stage, a comparison analysis is performed based on the target charging state curve and the initial charging state curve to obtain the health state detection result of the target battery. It can be seen that the embodiments of the present application reasonably fit the historical charging data, real-time data and initial data, and use the real-time charging and discharging data to accurately evaluate the actual health status. The real-time charging and discharging data is fitted with the historical charging and discharging data to avoid the problem of insufficient detection accuracy caused by the data. When the battery is in a charging state or a discharging state, the actual health status of the battery can be accurately detected, thereby improving the detection efficiency and accuracy of the battery health status, and solving the problem that the existing battery health status detection method is limited by incomplete historical charging and discharging data and cannot accurately detect the actual health status of the battery.

[0087] Reference Figure 2 , shows a schematic flow chart of a method for detecting the health status of a battery provided by an optional embodiment of the present application. The method may specifically include the following steps:

[0088] Step 210, obtaining an initial state curve of a target battery, and periodically collecting historical charge and discharge state data of the target battery.

[0089] The initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data.

[0090] For example, by building a system that continuously captures BMS data in the battery's built-in flash, the battery's BMS data is continuously and periodically collected as charge / discharge status data, and a data set is constructed using the collected data. Data analysis is performed to determine the health of the battery, thereby reminding the user of the health status.

[0091] Step 220 , during the discharge process of the target battery, fitting compensation is performed according to the real-time discharge state data and the historical discharge state data of the target battery to obtain a target discharge state curve.

[0092] For the description of step 220, reference may be made to the above step 120, which will not be described in detail in this embodiment.

[0093] In an optional embodiment, the above-mentioned fitting and compensation are performed according to the real-time discharge state data and the historical discharge state data of the target battery to obtain the target discharge state curve, which may specifically include: respectively analyzing the real-time discharge state data and the historical discharge state data to obtain the characteristic points and missing points of the charge change; according to the characteristic points and the missing points of the charge change, fitting and compensating the real-time discharge state data and the historical discharge state data to obtain the target discharge state curve.

[0094] In a specific implementation, the real-time discharge state data and the historical discharge state data can be analyzed separately, and the change time, SOC and OCV corresponding to the turning point of the power change in the real-time discharge state data can be analyzed, and the turning point can be used as the characteristic point of power change. At the same time, since in the discharge process of the target battery, there may be a point where the discharge is missing or there are detailed errors in order to perform a complete discharge cycle, this embodiment can analyze the missing or obviously erroneous parts of the real-time discharge state in parallel, so as to obtain the characteristic points and missing points of power change, and use the historical discharge state data to fit the relevant parts of the real-time discharge state data, so as to make the subsequent health status detection / assessment more accurate and improve the accuracy of health status detection.

[0095] Step 230 : performing an offset analysis based on the initial discharge state curve and the target discharge state curve to obtain curve offset information.

[0096] Step 240: Perform trend analysis based on the curve offset information to obtain the curve change trend.

[0097] The curve change trend is used to characterize the attenuation change of the target discharge state curve relative to the initial discharge state curve.

[0098] A unified description of steps 230 to 240 is given as follows:

[0099] In a specific implementation, after the battery has gone through a charge and discharge cycle, the number of active lithium ions decreases and it is prone to attenuation. At this time, the initial discharge state curve, as the SOC-OCV curve of the battery BOL, will be somewhat different from the target discharge state curve, which is specifically manifested as a curve offset between the two state curves, and a certain change trend. In the embodiment of the present application, the initial discharge state curve and the target discharge state curve are set in the same coordinate view for offset analysis to obtain curve offset information, which can be used to characterize the offset direction and offset situation of the curve. Then, a trend analysis is performed based on the offset direction, offset situation, etc. to obtain the curve change trend.

[0100] Specifically, when the battery capacity decays, from the coordinate view containing two state curves (assuming that the X-axis is SOC from 0-100%, and the Y-axis is OCV), the target discharge state curve may move to the right (i.e., shift to the right) relative to the initial discharge state curve, and have a trend of gradually shifting to the right, or according to the change in the orientation of the coordinate view, there is a trend of moving to the left or to other orientations. Specifically, the offset is proportional to the attenuation, that is, the more severe the attenuation of the target battery, the more severe the offset in the two state curves, and the more obvious the curve change trend. The curve change trend can characterize the health of the battery to a certain extent.

[0101] Step 250: Perform key point change analysis according to the curve change trend to obtain attenuation change key points.

[0102] In this embodiment, by comparing and analyzing the initial discharge state curve and the target discharge state curve, the positions where the change trend occurs are analyzed as key points to obtain the attenuation change key points. By analyzing the key points of battery attenuation change, the health status of the battery can be accurately analyzed.

[0103] For example, refer to Figure 3 , taking the SOC-OCV at the beginning and end of battery life (EOL) as an example, the EOL battery capacity decays and its SOC-OCV curve moves to the right. Figure 3 It can be seen that for SOC≤35%, its OCV shows a more obvious downward trend; for 55%~70% SOC, its corresponding OCV is greatly reduced; for 60% and 65% SOC, the OCV of BOL and EOL batteries has a significant difference. These positions with obvious downward trends can be used as key points and key sections of attenuation changes. In addition, according to Figure 3It can be seen that at 60% and 65% SOC, the difference between the OCV of the BOL and EOL batteries is relatively large. For example, at 60% SOC, the difference between the two may be 26mV, and at 65% SOC, the difference between the two may be 33mV. This is mainly due to the reduced capacity attenuation of the EOL battery. At the same SOC state, the negative electrode graphite is less embedded with lithium than the BOL battery. Therefore, the potential of the negative electrode is higher, causing the OCV value to decrease. As a result, the negative electrode potential of the EOL battery lags behind that of the BOL battery. When the BOL battery almost completes the OCV step, the EOL battery begins to have an OCV step.

[0104] In an optional embodiment, the above-mentioned key point change analysis is performed according to the curve change trend to obtain the attenuation change key point, which can specifically include: determining the key change segment in the initial discharge state curve and the target discharge state curve according to the curve change trend; performing voltage difference analysis on each change point in the key change segment to obtain the voltage difference change point, and using the voltage difference change point as the attenuation change key point.

[0105] In this embodiment, for the position where an obvious change trend occurs, there is a certain section of SOC between the target discharge state curve and the initial discharge state curve, but the voltage difference corresponding to each SOC point between the two is greatly different. At this time, the SOC section is the key change section (such as Figure 3 In the SOC≤35% part, 55%-70% SOC part, and 60% and 65% SOC part), each point of the key change section is used as a key change point for subsequent attenuation calculation.

[0106] In this embodiment, when there are certain differences between the entire target discharge state curve and the initial discharge state curve, that is, there is no portion with a zero or extremely small voltage difference in the same SOC point, the target discharge state curve all belongs to the key change segment.

[0107] Step 260 , performing attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery.

[0108] In a specific implementation, for each critical attenuation change point, this embodiment uses the critical attenuation change point as a reference, determines the voltage value corresponding to the initial discharge state curve and the voltage value corresponding to the target discharge state curve at the critical attenuation change point, and calculates the voltage difference between the two voltage values. Then, the health status detection result of the target battery is obtained based on the voltage difference calculation corresponding to all the critical attenuation change points.

[0109] Optionally, performing attenuation calculation according to the attenuation change key point to obtain the health status detection result of the target battery may specifically include the following sub-steps:

[0110] Sub-step 2601, obtaining a complete aging curve of the target battery in a discharge cycle.

[0111] Sub-step 2602, performing difference calculation based on the initial discharge state curve and the complete aging curve to obtain a complete aging difference.

[0112] Sub-step 2603, performing difference calculation based on the attenuation change key points to obtain the real-time aging difference.

[0113] The real-time aging difference is used to characterize the voltage attenuation of the target battery during the current discharge process.

[0114] Sub-steps 2601 to 2603 are described uniformly:

[0115] In a specific implementation, the full aging curve of the target battery is used to characterize the discharge state curve corresponding to the target battery when it is discharged under full aging. For the full aging difference, this embodiment compares the full aging curve of the target battery with the initial discharge state curve. Specifically, for each SOC percentage point, the voltage value corresponding to the point in the initial discharge state curve and the full aging curve is determined, and the voltage difference is calculated. Then all voltage differences are added to obtain the full aging difference.

[0116] For the real-time aging difference, this embodiment determines the voltage value corresponding to each attenuation change key point in the initial discharge state curve and the real-time discharge state curve, compares the two voltage values, and calculates the difference between the two voltage values ​​as the attenuation difference. Then, the attenuation differences of all attenuation change key points are added together to obtain the total difference as the real-time aging difference.

[0117] For example, Figure 3 Based on the attenuation change principle and attenuation change situation of the characterization, refer to Figure 4 and Figure 5 .in, Figure 4 A flowchart of a method for detecting the battery health status during discharge is provided for this example. Figure 5 This example provides a BOL curve and EOL curve obtained by actual battery testing. During the battery discharge process, the BMS data is read, and then the two curves are compared to calculate the total voltage difference of the battery from the initial to the fully aged. For example, Figure 5 The red line in the figure is the initial SOC / OCV curve. Figure 5The black line in the middle is the SOC / OCV curve after the battery is fully aged. First calculate the difference between the two curves. The voltage difference corresponding to each percentage point of SOC from 1% to 100% is obtained. For example, when the SOC is 1%, the corresponding voltage difference is 20 millivolts (MV); when the SOC is 2%, the corresponding voltage difference is 30MV..., when the SOC is 100%, the corresponding voltage difference is 10MV. Then sum up all the voltage differences to get the total voltage difference of all SOC points from BOL to EOL of the battery as the full aging difference. Assume that the full aging difference is 400MV.

[0118] For the initial state curve and the target discharge state curve, the voltage difference between the voltage value of the initial state curve and the voltage value of the target discharge state curve corresponding to each SOC point is calculated according to the above principle, and finally the total voltage difference of all SOC points is obtained as the real-time aging difference. It is assumed that the real-time aging value is 200MV.

[0119] In an optional embodiment, the embodiment of the present application performs difference calculation based on the attenuation change key points to obtain the real-time aging difference, which may specifically include: for each of the attenuation change key points, using the initial discharge state curve and the real-time discharge state curve to perform difference calculation to obtain the attenuation difference corresponding to each of the attenuation change key points; performing calculation based on the attenuation difference to obtain the real-time aging difference.

[0120] Sub-step 2604, performing an aging comparison based on the real-time aging difference and the complete aging difference to obtain a health status detection result of the target battery.

[0121] In a specific implementation, this embodiment calculates the percentage based on the full aging difference and the real-time aging difference to obtain the battery aging degree as the health status detection result of the target battery during this discharge process. For example, the battery aging degree calculation formula is: this difference / total difference=battery aging degree. The corresponding data above is: 200mv / 400mv*100%=50%, that is, the target battery is aged by 50% at this time.

[0122] Therefore, in the embodiment of the present application, when the battery is in the discharge process, the real-time discharge status curve and the standard discharge status curve are combined to determine whether the battery is aged through the voltage / power data of each status curve, and a calculation method for determining the degree of aging is provided, thereby effectively improving the detection efficiency and accuracy of the battery health status.

[0123] Step 270, during the charging process of the target battery, charging state fitting is performed according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage.

[0124] Wherein, the charging stage includes at least one of a trickle current stage, a constant current stage and a constant voltage stage.

[0125] In an optional embodiment, the embodiment of the present application performs charging state fitting based on the real-time charging state data and the historical charging state data of the target battery to obtain a target charging state curve of the target battery in at least one charging stage, which may specifically include: performing current and voltage analysis based on the real-time charging state data to obtain at least one charging stage, and using the real-time charging state data and the historical charging state data to perform fitting compensation to obtain a complete charging state curve; matching the charging stage in the complete charging state curve to obtain the target charging state curve of the target battery in the charging stage.

[0126] In the specific implementation, for the target battery in charge, this embodiment collects the corresponding charging status data in real time through the BMS as the real-time charging status data. By performing data analysis on the real-time charging status data, including analyzing the charging voltage value, current value, power and charging time of the target battery, the charging stage of the target battery in real-time charging and the detailed status data corresponding to each charging stage are determined. Then, the historical charging status data is used to fit and compensate for the obvious errors or missing data in the real-time charging status data, and finally a complete charging status curve is formed, and the charging stage is matched in the complete charging status curve to obtain the target charging status curve corresponding to each charging stage. This embodiment uses real-time charging status data and historical data for fitting, and accurately obtains various key data of the battery in the real-time charging process, providing a basis for battery health status analysis.

[0127] In actual processing, this embodiment analyzes the state data such as voltage value, current value, power and charging time to determine the corresponding position of each charging stage in the complete charging state curve.

[0128] For example, refer to Figure 6 ,by Figure 6 Taking the charging state curve of the battery under normal conditions as an example, each charging stage is obtained by matching the charging state data. The target charging state curve of each charging stage in the real-time charging process can be referred to Figure 6 The normal charging state curve is divided as shown.

[0129] Step 280 , performing charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage.

[0130] In the specific implementation, refer to Figure 7 , Figure 7The black curve in the middle is the normal charging state curve, which can be used as the standard charging state curve or the initial charging state curve. When the battery is aged and abnormal, the charging curve is as follows Figure 7 As shown by the orange or yellow curve in Figure 7 As shown, when the battery ages and becomes abnormal, it will quickly reach the maximum voltage value when charging, and cannot be charged, and quickly enter the constant voltage charging mode, and the current gradually decreases. Based on this principle, this embodiment performs decay analysis on the target charging state curve corresponding to each charging stage and the initial charging state curve, and compares the two charging state curves, including comparing the key data such as current, voltage, charging time, etc. corresponding to each percentage of power in the two state curves, to obtain the decay of the target battery.

[0131] In actual implementation, for each charging stage, such as the trickle charging stage, this embodiment extracts the curve corresponding to the trickle charging state from the initial charging state curve, and compares and analyzes it with the target charging state curve of the trickle charging stage. Specifically, the initial charging state curve is used as the standard charging curve, and the battery charging voltage, power and time changes of the two state curves corresponding to the trickle charging stage are detected to determine whether the battery is aged and decayed, and the attenuation change of the target battery in each charging stage is obtained. Among them, the attenuation change includes but is not limited to: mild attenuation, moderate attenuation and severe attenuation.

[0132] In an optional embodiment, the embodiment of the present application performs a charging decay analysis based on the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage, which may specifically include: for each of the charging stages, using the target charging state curve and the initial charging state curve to perform a decay point analysis to obtain a slope key point; performing analysis and calculation based on the slope key point to obtain the slope information corresponding to the charging stage; performing an attenuation comparison based on the slope information to obtain the attenuation change of the target battery.

[0133] As an example, see Figure 8 When charging, read the BMS voltage, current, SOC change and other data to build a charging state curve. Then use the three-segment comparison method to intercept a segment of value for comparison, including comparing the slope of the target charging state curve corresponding to the trickle stage, constant current stage and constant voltage stage. According to the standard charging curve, calculate the voltage value max, charging time t and curve change slope k corresponding to each charging stage. For example, for the trickle stage, the voltage value max1, t1 (duration) and k1 (change slope) are calculated respectively. Fig. 9 As shown; for the constant current stage, max2, t2 and k2 (slope) are calculated, as shown Fig.10As shown; for the constant pressure stage, max3, t3 and k3 (slope) are calculated, as shown Fig.11 shown.

[0134] Then, the max, t, and k corresponding to each stage are used as data features for identification and judgment to obtain the attenuation change. The criteria for identifying and judging the attenuation change can include: mild attenuation, which is mainly manifested in changes in the constant voltage stage, that is, changes in t3 and k3, and the battery is quickly fully charged, while the other two stages may be normal; moderate attenuation, which is mainly manifested in the constant current stage, the voltage rises quickly, the t2 time is shortened, and the k2 slope becomes larger; severe attenuation, severe attenuation may cause battery damage, at which time the max, t, k and other related indicators of the three stages all change.

[0135] Step 290: Perform aging analysis based on the attenuation change to obtain a health status detection result of the target battery.

[0136] In this embodiment, during the charging process of the target battery, the attenuation changes detected are analyzed to mainly characterize the health of the battery. For a target battery analyzed as mild attenuation, it indicates that the battery has aged and its health has declined; for a target battery analyzed as moderate attenuation, it indicates that the battery may have aged more seriously, its health has declined sharply, and its health is poor. At this time, an early warning can be used to remind the user to replace and repair it in time; for a target battery analyzed as severe attenuation, it indicates that the battery is very dangerous and its health is very poor. There is a risk of overcharge and explosion. An early warning can be used to remind the user to replace and repair it in time.

[0137] Therefore, in the embodiment of the present application, when the battery is in a charging state, for different charging stages, the corresponding standard state curve and actual state curve are used to extract key data such as voltage, charging time and curve slope for judgment, and the degree of battery aging is obtained, thereby realizing the detection of battery health, analyzing the degree of battery attenuation for customers, or whether the battery has been damaged, etc., and issuing danger warnings for batteries in poor or very poor health.

[0138] In summary, the embodiment of the present application obtains the initial charge / discharge state curve and historical charge / discharge state data of the target battery, and during the discharge process of the target battery, performs fitting compensation according to the acquired real-time discharge state data and historical discharge state data to obtain the target discharge state curve, and then performs offset analysis based on the initial discharge state curve and the target discharge state curve to obtain curve offset information, and performs trend analysis according to the curve offset information to obtain the curve change trend, and then performs key point change analysis according to the curve change trend to obtain attenuation change key points, performs attenuation calculation according to the attenuation change key points, and obtains the health state detection result of the target battery, thereby realizing accurate health state assessment of the target battery in the discharge state; during the charging process of the target battery, performs charging state fitting according to the acquired real-time charging state data and historical charging state data to obtain the target charging state curve of the target battery in at least one charging stage, performs charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage, and then performs aging analysis according to the attenuation change to obtain the health state detection result of the target battery, thereby realizing accurate health state assessment of the target battery in the charging state. The embodiment of the present application first utilizes historical charge / discharge state data and real-time charge / discharge state data to fit and obtain a target charge / discharge state curve, thereby improving the accuracy and availability of detection data. Then, the attenuation comparison and judgment are performed in combination with the standard charge / discharge state curve, thereby accurately detecting the actual health state of the battery, thereby improving the detection efficiency and accuracy of the battery health state, and solving the problem that the existing battery health state detection method is limited by incomplete historical charge / discharge data and cannot accurately detect the actual health state of the battery.

[0139] It should be noted that, for the purpose of simple description, the method embodiments are expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present application are not limited to the described order of actions, because according to the embodiments of the present application, certain steps may be performed in other orders or simultaneously.

[0140] like Fig.12 As shown, the embodiment of the present application also provides a battery health status detection system 1200, including:

[0141] The state curve and state data acquisition module 1210 is used to acquire the initial state curve of the target battery, and periodically collect the historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data;

[0142] A fitting compensation module 1220 is used to perform fitting compensation according to the real-time discharge state data and the historical discharge state data of the target battery during the discharge process of the target battery to obtain a target discharge state curve;

[0143] A curve change analysis module 1230, configured to perform curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points;

[0144] An attenuation calculation module 1240 is used to perform attenuation calculation according to the attenuation change key point to obtain a health status detection result of the target battery;

[0145] A charging state fitting module 1250 is used to perform charging state fitting according to the real-time charging state data and the historical charging state data of the target battery during the charging process of the target battery to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage and a constant voltage stage;

[0146] The comparison and analysis module 1260 is used to perform a comparison and analysis based on the target state of charge curve and the initial state of charge curve for each of the charging stages to obtain a health status detection result of the target battery.

[0147] Optionally, the fitting compensation module 1220 includes:

[0148] A first analysis submodule is used to analyze the real-time discharge state data and the historical discharge state data respectively to obtain the power change characteristic points and missing points;

[0149] The fitting compensation submodule is used to perform fitting compensation on the real-time discharge state data and the historical discharge state data according to the power change characteristic point and the missing point to obtain a target discharge state curve.

[0150] Optionally, the curve change analysis module 1230 includes:

[0151] An offset analysis submodule, configured to perform an offset analysis based on the initial discharge state curve and the target discharge state curve to obtain curve offset information;

[0152] A trend analysis submodule, used for performing trend analysis according to the curve offset information to obtain a curve change trend, wherein the curve change trend is used to characterize the attenuation change of the target discharge state curve relative to the initial discharge state curve;

[0153] The key point change analysis submodule is used to perform key point change analysis according to the curve change trend to obtain attenuation change key points.

[0154] Optionally, the key point change analysis submodule includes:

[0155] A key change segment determination unit, used to determine the key change segments in the initial discharge state curve and the target discharge state curve according to the curve change trend;

[0156] The voltage difference analysis unit is used to perform voltage difference analysis on each change point in the key change section to obtain a voltage difference change point, and use the voltage difference change point as the attenuation change key point.

[0157] Optionally, the attenuation calculation module 1240 includes:

[0158] An aging curve acquisition submodule, used to acquire a complete aging curve of the target battery in a discharge cycle;

[0159] A difference calculation submodule, used to perform difference calculation based on the initial discharge state curve and the complete aging curve to obtain a complete aging difference; perform difference calculation based on the attenuation change key points to obtain a real-time aging difference, and the real-time aging difference is used to characterize the voltage attenuation of the target battery during this discharge process;

[0160] The aging comparison submodule is used to perform aging comparison according to the real-time aging difference and the complete aging difference to obtain the health status detection result of the target battery.

[0161] Optionally, the difference calculation submodule is specifically used to: for each of the attenuation change key points, perform difference calculation using the initial discharge state curve and the real-time discharge state curve to obtain the attenuation difference corresponding to each of the attenuation change key points; and perform calculation based on the attenuation difference to obtain the real-time aging difference.

[0162] Optionally, the charging state fitting module 1250 includes:

[0163] A voltage and current analysis submodule, configured to perform current and voltage analysis according to the real-time charging state data to obtain at least one charging stage, and to perform fitting compensation using the real-time charging state data and the historical charging state data to obtain a complete charging state curve;

[0164] The matching submodule is used to match the charging stage in the complete charging state curve to obtain a target charging state curve of the target battery in the charging stage.

[0165] Optionally, the comparison and analysis module 1260 includes:

[0166] A charging decay analysis submodule, used to perform charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage;

[0167] The aging analysis submodule is used to perform aging analysis according to the attenuation change to obtain a health status detection result of the target battery.

[0168] Optionally, the charging decay analysis submodule is specifically used to: for each of the charging stages, perform decay point analysis using the target charging state curve and the initial charging state curve to obtain slope key points; perform analysis and calculation based on the slope key points to obtain slope information corresponding to the charging stage; perform attenuation comparison based on the slope information to obtain the attenuation change of the target battery.

[0169] It should be noted that the battery health status detection system provided in the embodiments of the present application can execute the battery health status detection method provided in any embodiment of the present application, and has the corresponding functions and beneficial effects of executing the battery health status detection method.

[0170] In a specific implementation, the battery health status detection system can be integrated into a device, so that the device can fit and analyze the real-time charge and discharge data, historical charge and discharge data, and initial data, so as to accurately evaluate the actual health status of the battery. As an electronic device, it can accurately and quickly detect the actual health status of the battery when the battery is in a charging state or a discharging state. The electronic device can be composed of two or more physical entities, or it can be composed of one physical entity. For example, the electronic device can be a personal computer (PC), a computer, a server, etc., and the embodiments of the present application do not impose specific restrictions on this.

[0171] like Fig.13As shown, an embodiment of the present application provides an electronic device, including a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114; the memory 113 is used to store computer programs; the processor 111 is used to implement the steps of the battery health status detection method provided by any of the aforementioned method embodiments when executing the program stored in the memory 113. Exemplarily, the steps of the battery health state detection method may include the following steps: obtaining an initial state curve of a target battery, and periodically collecting historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data; during the discharge process of the target battery, performing fitting compensation according to the real-time discharge state data of the target battery and the historical discharge state data to obtain a target discharge state curve; performing curve change analysis according to the initial discharge state curve and the target discharge state curve to obtain attenuation change key points; performing attenuation calculation according to the attenuation change key points to obtain a health state detection result of the target battery; during the charging process of the target battery, performing charging state fitting according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage, and a constant voltage stage; for each of the charging stages, performing comparison and analysis according to the target charging state curve and the initial charging state curve to obtain a health state detection result of the target battery.

[0172] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the battery health status detection method provided in any of the aforementioned method embodiments are implemented.

[0173] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0174] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A battery health status detection method, characterized in that: include: Acquire an initial state curve of a target battery, and periodically collect historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data; During the discharge process of the target battery, fitting compensation is performed according to the real-time discharge state data of the target battery and the historical discharge state data to obtain a target discharge state curve; Performing curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points; Perform attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery; During the charging process of the target battery, charging state fitting is performed according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage, and a constant voltage stage; For each of the charging stages, a comparison analysis is performed based on the target charging state curve and the initial charging state curve to obtain a health status detection result of the target battery.

2. The method according to claim 1, characterized in that The fitting compensation is performed according to the real-time discharge state data of the target battery and the historical discharge state data to obtain a target discharge state curve, including: Analyze the real-time discharge state data and the historical discharge state data respectively to obtain the characteristic points and missing points of the power change; According to the electric quantity change characteristic point and the missing point, the real-time discharge state data and the historical discharge state data are fitted and compensated to obtain a target discharge state curve.

3. The method according to claim 1, characterized in that The curve change analysis is performed based on the initial discharge state curve and the target discharge state curve to obtain the attenuation change key points, including: Performing an offset analysis based on the initial discharge state curve and the target discharge state curve to obtain curve offset information; Performing trend analysis according to the curve offset information to obtain a curve change trend, wherein the curve change trend is used to characterize an attenuation change of the target discharge state curve relative to the initial discharge state curve; According to the curve change trend, key point change analysis is performed to obtain attenuation change key points.

4. The method according to claim 3, characterized in that The key point change analysis is performed according to the curve change trend to obtain the attenuation change key point, including: Determining key change segments in the initial discharge state curve and the target discharge state curve according to the curve change trend; A voltage difference analysis is performed on each change point in the key change section to obtain a voltage difference change point, and the voltage difference change point is used as the attenuation change key point.

5. The method according to claim 4, characterized in that The attenuation calculation is performed according to the attenuation change key point to obtain the health status detection result of the target battery, including: Obtaining a complete aging curve of the target battery during a discharge cycle; Performing difference calculation based on the initial discharge state curve and the complete aging curve to obtain a complete aging difference; Performing difference calculation based on the key points of attenuation change to obtain a real-time aging difference, wherein the real-time aging difference is used to characterize the voltage attenuation of the target battery during this discharge process; An aging comparison is performed based on the real-time aging difference and the complete aging difference to obtain a health status detection result of the target battery.

6. The method according to claim 5, characterized in that The difference calculation based on the attenuation change key points to obtain the real-time aging difference includes: For each of the attenuation change key points, difference calculation is performed using the initial discharge state curve and the real-time discharge state curve to obtain an attenuation difference corresponding to each of the attenuation change key points; The real-time aging difference is obtained by performing calculation based on the attenuation difference.

7. The method according to claim 1, characterized in that The performing charging state fitting according to the real-time charging state data of the target battery and the historical charging state data to obtain a target charging state curve of the target battery in at least one charging stage includes: Performing current and voltage analysis according to the real-time charging state data to obtain at least one charging stage, and performing fitting compensation using the real-time charging state data and the historical charging state data to obtain a complete charging state curve; The charging stage is matched in the complete charging state curve to obtain a target charging state curve of the target battery in the charging stage.

8. The method according to claim 1, characterized in that For each of the charging stages, a comparison analysis is performed based on the target charging state curve and the initial charging state curve to obtain a health state detection result of the target battery, including: Performing charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage; An aging analysis is performed based on the attenuation change to obtain a health status detection result of the target battery.

9. The method according to claim 8, characterized in that The performing charging decay analysis according to the target charging state curve and the initial charging state curve to obtain the attenuation change of the target battery in the charging stage includes: For each of the charging stages, using the target state of charge curve and the initial state of charge curve to perform decay point analysis to obtain slope key points; Analyze and calculate the slope key points to obtain slope information corresponding to the charging stage; An attenuation comparison is performed according to the slope information to obtain the attenuation change of the target battery.

10. A battery health status detection system, characterized in that: include: A state curve and state data acquisition module, used to acquire an initial state curve of a target battery, and periodically collect historical charge and discharge state data of the target battery, wherein the initial state curve includes an initial discharge state curve and an initial charge state curve, and the historical charge and discharge state data includes historical discharge state data and historical charge state data; A fitting compensation module, used for performing fitting compensation according to the real-time discharge state data and the historical discharge state data of the target battery during the discharge process of the target battery to obtain a target discharge state curve; A curve change analysis module, used to perform curve change analysis based on the initial discharge state curve and the target discharge state curve to obtain attenuation change key points; An attenuation calculation module, used to perform attenuation calculation according to the attenuation change key points to obtain a health status detection result of the target battery; a charging state fitting module, used for performing charging state fitting according to the real-time charging state data and the historical charging state data of the target battery during the charging process of the target battery, so as to obtain a target charging state curve of the target battery in at least one charging stage, wherein the charging stage includes at least one of a trickle current stage, a constant current stage and a constant voltage stage; The comparison and analysis module is used to compare and analyze the target charging state curve and the initial charging state curve for each charging stage to obtain a health state detection result of the target battery.

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