Battery health state monitoring method, device and equipment and readable storage medium

Abstract

The invention discloses a battery health state monitoring method, which comprises the following steps: charging a battery to be detected to a selected charge state in a first charging mode, detecting voltages at two ends of the battery to be detected at three selected moments after the charging is finished, and sequentially marking the voltages as a first voltage, a second voltage and a third voltage; applying a single-frequency AC signal to the to-be-tested battery, and obtaining a response signal of the to-be-tested battery to the single-frequency AC signal so as to determine the ohmic internal resistance of the to-be-tested battery; determining an electrochemical transfer parameter and a diffusion parameter of the battery to be detected according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and a current value in the first charging mode; and repeating the process for multiple times to determine the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate so as to determine the health state of the battery to be detected. According to the method, the health state of the battery can be judged more accurately. The invention further discloses a battery health state monitoring device, electronic equipment and a computer readable storage medium.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and in particular to a battery health status detection method, a battery health status monitoring device, an electronic device and a computer-readable storage medium. Background Art

[0002] Lithium-ion batteries have developed rapidly in various markets in recent years, especially in the power market such as electric vehicles. As the number of cars powered by lithium-ion batteries gradually increases, the safety of lithium-ion batteries during use has received more and more attention. During the use of lithium-ion batteries, monitoring the health status of lithium-ion batteries, determining the status of the batteries and issuing early warnings for battery safety issues are important means to ensure the safety performance of lithium-ion batteries during use.

[0003] Due to the characteristics of its working mechanism, lithium-ion batteries will undergo a series of side reactions during use, such as active material breakage, SEI film growth, electrolyte drying, etc. These side reactions cause the internal resistance of lithium batteries to gradually increase with the number of cycles. Excessive internal resistance of batteries will cause certain risks in use. In addition, some abuses of lithium-ion batteries, such as overcharging and over-discharging, as well as occasional failures of the battery itself, can also cause abnormal internal resistance of the battery. Therefore, currently evaluating the battery status based on changes in battery internal resistance is an important method for monitoring battery health status.

[0004] The internal resistance of lithium-ion batteries includes three types: ohmic internal resistance, electrochemical transfer internal resistance and diffusion internal resistance. The changes in these three types of internal resistance can be reflected by the corresponding ohmic polarization voltage, electrochemical transfer polarization voltage and diffusion polarization voltage.

[0005] In the prior art, the differential pressure method and the impedance method are two commonly used methods to monitor the safety status of batteries by monitoring the changes in the internal resistance of batteries. However, these methods usually have disadvantages such as high sampling time requirements and high instrumentation requirements. For example, the internal resistance monitoring of the pure differential pressure method requires a monitoring accuracy of 1 millisecond, and the pure impedance monitoring method requires the output of multi-frequency AC signals. These methods require precise equipment, which limits their potential for deployment in miniaturized BMS (battery management system) equipment.

[0006] In addition, there is an existing technology that determines whether the battery is in a healthy state by measuring the values ​​of ohmic polarization voltage, electrochemical transfer polarization voltage and diffusion polarization voltage respectively. However, the detection of its technical solution is still not accurate enough. The reason is that when detecting part of the voltage, the response time required is very short, usually at the millisecond level. Directly detecting the voltage is prone to large errors, and the errors are greatly affected by the detection equipment. Summary of the invention

[0007] The present invention proposes a battery health status monitoring method to solve the above problems.

[0008] In a first aspect, an embodiment of the present invention discloses a battery health status monitoring method, comprising:

[0009] The battery to be tested is charged to a selected state of charge in a first charging mode, and the voltages at both ends of the battery to be tested are detected at a first selected time, a second selected time, and a third selected time after the charging is completed, and are marked as a first voltage, a second voltage, and a third voltage in sequence; wherein the first voltage and the second voltage are used to determine the sum of the battery's ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage;

[0010] Applying a single-frequency AC signal to the battery to be tested, obtaining a response signal of the battery to the single-frequency AC signal, and determining the ohmic internal resistance of the battery to be tested according to the single-frequency AC signal and the response signal;

[0011] Determine electrochemical transfer parameters and diffusion parameters of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode;

[0012] Charging the battery to be tested to a selected state of charge by the first charging method for multiple times, obtaining the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determining the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate;

[0013] The health status of the battery to be tested is determined according to the change rate of the ohmic parameter, the change rate of the electrochemical transfer parameter and the change rate of the diffusion parameter.

[0014] By adopting the above technical scheme, the battery health status monitoring method of the present invention can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0015] According to another specific embodiment of the present invention, the first selected moment is the moment when charging of the battery to be tested is completed, the second selected moment is the moment between the 1st millisecond and the 10th millisecond after charging of the battery to be tested is completed, and the third selected moment is the moment when the battery to be tested is left to stand and returns to a state of equilibrium after charging of the battery to be tested is completed; and / or, the first charging method is a method of charging with a constant current; and / or, the selected state of charge is 80% of the battery state of charge of the battery to be tested.

[0016] According to another specific embodiment of the present invention, determining the electrochemical transfer parameter and diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode specifically includes:

[0017] Determining the ohmic polarization voltage of the battery according to the ohmic internal resistance and the current in the first charging mode;

[0018] Determining an electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage;

[0019] determining an electrochemical transfer internal resistance based on an electrochemical transfer polarization voltage and a current in a first charging mode;

[0020] determining a diffusion polarization voltage according to the second voltage and the third voltage, and determining a diffusion internal resistance according to the diffusion polarization voltage and the current in the first charging mode;

[0021] Among them, the ohmic parameter change rate is the change rate of the ohmic internal resistance, the electrochemical transfer parameter is the electrochemical transfer internal resistance, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer internal resistance, the diffusion parameter is the diffusion internal resistance, and the diffusion parameter change rate is the change rate of the diffusion internal resistance.

[0022] According to another specific embodiment of the present invention, determining the electrochemical transfer parameter and diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current in the first charging mode specifically includes:

[0023] Determining the ohmic polarization voltage of the battery according to the ohmic internal resistance and the current in the first charging mode;

[0024] Determining an electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage;

[0025] determining a diffusion polarization voltage according to the second voltage and the third voltage;

[0026] Among them, the ohmic parameter change rate is the change rate of the battery ohmic polarization voltage, the electrochemical transfer parameter is the electrochemical transfer polarization voltage, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer polarization voltage, the diffusion parameter is the diffusion polarization voltage, and the diffusion parameter change rate is the change rate of the diffusion polarization voltage.

[0027] According to another specific embodiment of the present invention, charging the battery to be tested to a selected state of charge by the first charging method for multiple times and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determining the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate, specifically includes:

[0028] Determine an ohmic parameter variation curve, an electrochemical transfer parameter variation curve, and a diffusion parameter variation curve by charging the battery to be tested to a selected state of charge multiple times by the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter, and diffusion parameter of the battery to be tested from the first time to the nth time after each charging is completed; wherein n is a positive integer;

[0029] The ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate are determined according to the ohmic parameter change curve, the electrochemical transfer parameter change curve and the diffusion parameter change curve.

[0030] According to another specific embodiment of the present invention, charging the battery to be tested to a selected state of charge by the first charging method for multiple times and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determining the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate, specifically includes:

[0031] Determine the average ohmic parameter, the average electrochemical transfer parameter and the average diffusion parameter by charging the battery to be tested to a selected state of charge multiple times by the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested from the first time to the nth time after each charging is completed; wherein n is a positive integer;

[0032] Determine the ohmic parameter change rate according to the ohmic parameter average value and the ohmic internal resistance of the battery to be tested detected for the nth time;

[0033] Determine the electrochemical transfer parameter change rate according to the electrochemical transfer parameter average value and the electrochemical transfer parameter of the battery to be tested detected for the nth time;

[0034] The diffusion parameter change rate is determined according to the diffusion parameter average value and the diffusion parameter of the battery to be tested detected for the nth time.

[0035] According to another specific embodiment of the present invention, determining the health state of the battery to be tested according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate specifically includes:

[0036] Determine the judgment number according to the change rate of the ohmic parameter, the change rate of the electrochemical transfer parameter and the change rate of the diffusion parameter;

[0037] Determine the health status of the battery to be tested according to the determination number; when the determination number is not within the preset health range, the battery to be tested is in an abnormal state; when the determination number is within the preset health range, the battery to be tested is in a healthy state;

[0038] The judgment number is determined by the following method:

[0039]

[0040] Wherein, N(n) represents the determination number determined by the nth monitoring, ΔX Ω (n) represents the rate of change of the ohmic parameter, ΔX ct (n) represents the rate of change of electrochemical transfer parameters, ΔX diff (n) represents the rate of change of diffusion parameter.

[0041] In a second aspect, an embodiment of the present invention discloses a battery health status monitoring device, comprising:

[0042] A voltage detection module, used to charge the battery to be tested to a selected state of charge in a first charging mode, and detect the voltages at both ends of the battery to be tested at a first selected time, a second selected time, and a third selected time after the charging is completed, and mark them as a first voltage, a second voltage, and a third voltage in sequence; wherein the first voltage and the second voltage are used to determine the sum of the battery's ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage;

[0043] An ohmic internal resistance determination module is used to apply a single-frequency AC signal to the battery to be tested, obtain a response signal of the battery to the single-frequency AC signal, and determine the ohmic internal resistance of the battery to be tested according to the single-frequency AC signal and the response signal;

[0044] A parameter determination module, used to determine the electrochemical transfer parameter and diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode;

[0045] a change rate determination module, used to charge the battery to be tested to a selected state of charge by a first charging method for multiple times, obtain the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determine the change rate of the ohmic parameter, the change rate of the electrochemical transfer parameter and the change rate of the diffusion parameter;

[0046] The battery health status judgment module is used to determine the health status of the battery to be tested based on the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate.

[0047] By adopting the above technical scheme, the battery health status monitoring device of the present invention can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0048] In a third aspect, an embodiment of the present invention discloses an electronic device, including a processor and a memory, wherein the memory stores at least one instruction, and when the at least one instruction is executed by the processor, the battery health status monitoring method in any of the aforementioned embodiments is implemented.

[0049] By adopting the above technical solution, the electronic device can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0050] In a fourth aspect, an embodiment of the present invention discloses a computer-readable storage medium, in which at least one instruction is stored, and when the at least one instruction is executed, the battery health status monitoring method in any of the aforementioned embodiments is implemented.

[0051] By adopting the above technical solution, the computer-readable storage medium can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 1 ;

[0053] Figure 2 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 2 ;

[0054] Figure 3 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 3 ;

[0055] Figure 4 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 4 ;

[0056] Figure 5 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 5 ;

[0057] Figure 6 The process diagram of the battery health status monitoring method in the embodiment of the present invention is shown as follows Figure 6 ;

[0058] Figure 7 A schematic diagram showing the structure of a battery health status monitoring device in an embodiment of the present invention is shown;

[0059] Figure 8 A schematic diagram showing the structure of an electronic device in an embodiment of the present invention is shown;

[0060] Fig. 9 A schematic diagram showing a voltage detection selection time and a voltage monitoring curve in an embodiment of the present invention;

[0061] Fig.10 A graph showing different voltages detected in an embodiment of the present invention;

[0062] Fig.11 A schematic diagram showing an input AC voltage signal recorded at a selected input frequency in an embodiment of the present invention;

[0063] Fig.12 A schematic diagram showing an AC current signal output by a battery recorded at a selected input frequency in an embodiment of the present invention;

[0064] Fig.13 A trend diagram showing the changes of three types of internal resistance to battery cycle times in an embodiment of the present invention;

[0065] Fig.14 A schematic diagram showing the change rate of three types of internal resistance values ​​in an embodiment of the present invention is shown;

[0066] Fig.15 A schematic diagram of a curve showing changes in battery capacity and determination number in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0067] The following specific embodiments illustrate the implementation of the present invention, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Although the description of the present invention will be introduced in conjunction with the preferred embodiment, this does not mean that the features of this invention are limited to this implementation. On the contrary, the purpose of introducing the invention in conjunction with the implementation is to cover other options or modifications that may extend based on the claims of the present invention. In order to provide a deep understanding of the present invention, the following description will include many specific details. The present invention can also be implemented without using these details. In addition, in order to avoid confusion or blurring the focus of the present invention, some specific details will be omitted in the description. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0068] It should be noted that in this specification, similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0069] The terms “first”, “second”, etc. are only used for distinguishing descriptions and should not be understood as indicating or implying relative importance.

[0070] In the description of this embodiment, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this embodiment can be understood according to specific circumstances.

[0071] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0072] The inventor carefully studied the prior art and found that the prior art uses the method of measuring the battery's ohmic polarization voltage, electrochemical transfer polarization voltage, and diffusion polarization voltage respectively, and calculating their rate of change to determine whether the battery is in a healthy state. However, this method of detecting voltage is very prone to large errors, and is greatly affected by the voltage detection equipment, and the battery health status monitoring is not accurate enough. There are orders of magnitude differences in the values ​​of the three types of internal resistances of lithium-ion batteries, namely the ohmic internal resistance, electrochemical transfer internal resistance, and diffusion internal resistance. A large proportional change in the value of each type of internal resistance may have a small effect on the total internal resistance of the battery, which can easily cause the battery to be mistakenly considered to be still in a healthy state. However, a large proportional change in any type of internal resistance indicates that the battery has experienced severe degradation. Therefore, accurate monitoring of the battery health state is crucial. The inventor hopes to provide a method for more accurately monitoring the battery health state by improving the prior art. The inventor also found in his study of the prior art that the accuracy of battery internal resistance monitoring can be improved by applying an AC signal for AC detection. Furthermore, the inventor thought that the accuracy of battery health status monitoring can be improved by combining AC detection and adjusting the timing of voltage acquisition.

[0073] First, reference Figure 1 The present invention provides a battery health status monitoring method, comprising the following steps:

[0074] S1: charging the battery to be tested to a selected state of charge in a first charging mode, detecting the voltages at both ends of the battery to be tested at a first selected time, a second selected time and a third selected time after the charging is completed, and marking them as a first voltage, a second voltage and a third voltage in sequence.

[0075] Among them, the first charging mode is a pre-selected constant charging mode, for example, it can be a mode of charging to a selected state of charge with a constant current. The selected state of charge is a predetermined degree of charge of the battery, for example, it can be 80% of the battery SOC (SOC is the battery state of charge, and 80% of the battery SOC means that the proportion of the available power of the battery to the rated capacity of the battery is 80%). The first voltage and the second voltage are used to determine the sum of the battery ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage. The specific calculation formulas are Formula 1 and Formula 2.

[0076] V ct +V Ω =V2-V1 (Formula 1)

[0077] V diff =V3-V2 (Formula 2)

[0078] Among them, V Ω Indicates the battery ohmic polarization voltage of the battery to be tested, V ct Represents the electrochemical transfer polarization voltage of the battery under test, V diff represents the diffusion polarization voltage of the battery to be tested, V1 represents the first voltage, V2 represents the second voltage, and V3 represents the third voltage.

[0079] Furthermore, the first selected time is the time when the battery to be tested is charged, the second selected time is the time between 1 millisecond and 10 milliseconds after the battery to be tested is charged, and the third selected time is the time when the battery to be tested is stationary and returns to a balanced state after the battery to be tested is charged.

[0080] The ohmic polarization of a battery is polarization caused by the ohmic internal resistance of a lithium-ion battery. The ohmic internal resistance of a battery is composed of electrode materials, electrolyte, diaphragm resistance, and contact resistance of various parts. The occurrence of battery ohmic polarization is usually instantaneous, and it is extremely difficult to accurately monitor the battery ohmic polarization voltage.

[0081] The electrochemical transfer polarization of the battery is polarization caused by the electrochemical reaction speed on the positive and negative electrodes being lower than the electron movement speed. The response time of the electrochemical transfer polarization process is usually in the millisecond level. The specific time selection of the second selected moment is related to the time constant of the electrochemical transfer process in the battery to be tested, and is affected by factors such as the battery material model. The value selection of the second selected moment is usually calibrated in the laboratory based on dynamic impedance. The second selected moment is usually selected within the range of 1 millisecond to 10 milliseconds after the end of charging.

[0082] The present invention calculates the sum of the battery ohmic polarization voltage and the electrochemical transfer polarization voltage of the battery to be tested by detecting the difference between the first voltage measured at the first selected moment and the second voltage measured at the second selected moment, thereby eliminating the step of directly detecting the battery ohmic polarization voltage. The detection of the first voltage and the second voltage is more accurate, and thus the sum of the battery ohmic polarization voltage and the electrochemical transfer polarization voltage is also more accurate, which is conducive to subsequent accurate judgment of the health status of the battery to be tested.

[0083] Battery diffusion polarization is polarization caused by the diffusion rate of lithium ions participating in the reaction in the solid phase being lower than the electrochemical reaction rate. The process of battery diffusion polarization is relatively slow, and its response time is in seconds. The diffusion polarization voltage is obtained by calculating the difference between the second voltage and the third voltage measured at the third selected moment. Therefore, the third selected moment is usually selected after 30 seconds after the end of charging, and is usually selected within the range of 30 seconds to 2 hours after the end of charging. At this time, a more accurate diffusion polarization voltage can be obtained. For example, the third selected moment can be 30 seconds after the end of charging, or 2 hours after the end of charging.

[0084] Continue to refer Figure 1 The battery health status monitoring method provided by the present invention further includes the following steps:

[0085] S2: applying a single-frequency AC signal to the battery to be tested, obtaining a response signal of the battery to the single-frequency AC signal, and determining the ohmic internal resistance of the battery to be tested according to the single-frequency AC signal and the response signal.

[0086] The moment of applying a single-frequency AC signal to the battery to be tested can be any moment from 0.01 seconds to 2 hours after the battery is charged. Specifically, it usually takes about 2 hours to collect the high-precision diffusion polarization voltage and diffusion internal resistance that meet the laboratory requirements. In order to facilitate vehicle deployment and use, the time should take into account the validity of the data, and the time needs to be as short as possible. By applying a single-frequency input AC signal to detect the ohmic internal resistance of the battery to be tested, the battery needs to be left to stand and return to a balanced state after the charging and discharging is completed, and the battery to be tested needs to be given a certain amount of standing time before detecting the ohmic internal resistance. At the third selected moment of this embodiment (i.e., the 30th second after the charging is completed), the battery to be tested can basically reach a balanced state, and the third voltage measured at the 30th second after the charging is completed and the diffusion internal resistance obtained can reach 80% of the diffusion internal resistance value obtained by the laboratory precise test, which is representative, and the time of 30 seconds is short, so that the overall detection time is not too long. At this time, it is suitable for detecting the third voltage to obtain a representative diffusion internal resistance, and it is suitable for applying a single-frequency AC signal to obtain a response signal and calculate a more accurate ohmic internal resistance, and the detection time is not too long.

[0087] Therefore, preferably, in this embodiment, the time when the single-frequency AC signal is applied to the battery to be tested is the 30th second after the charging is completed, and the third selected time is also selected as the 30th second after the charging is completed.

[0088] In other embodiments, if the moment when the battery to be tested is left to stand and returns to a state of equilibrium and the moment when a representative diffusion internal resistance can be detected is 2 hours after the end of charging, then accordingly, the moment when a single-frequency AC signal is applied to the battery to be tested and the third selected moment can both be selected as 2 hours after the end of charging.

[0089] Furthermore, the sinusoidal expression of a single-frequency AC signal is expressed as Formula 3.

[0090] y=y0+A*sin(2πfx-x0)(Formula 3)

[0091] Wherein, A is the sine vector amplitude of the single-frequency AC signal with a frequency of f, f is the frequency of the single-frequency AC signal, x0 is the phase offset of the single-frequency AC signal, and y0 is the DC bias of the single-frequency AC signal.

[0092] The single-frequency AC signal is periodic, can resist interference, and improve the accuracy of signal acquisition. By increasing the AC amplitude of the single-frequency AC signal, or increasing the number of waves collected by the single-frequency AC signal, or increasing the AC amplitude of the single-frequency AC signal and the number of waves collected by the single-frequency AC signal at the same time, the accuracy of AC detection can be further improved, thereby improving the accuracy of subsequent ohmic internal resistance calculation. Among them, increasing the AC amplitude of the single-frequency AC signal can be to increase the A value in Formula 3. Increasing the number of waves collected by the single-frequency AC signal can be, for example, when it is found that there is interference in only collecting 10 sine waves of the single-frequency AC signal, it can be increased to collect 100 sine waves of the single-frequency AC signal to reduce interference.

[0093] When the applied single-frequency AC signal is an AC current signal, the corresponding response signal is an AC voltage signal. When the applied single-frequency AC signal is an AC voltage signal, the corresponding response signal is an AC current signal. Then, the ohmic internal resistance of the battery to be tested is calculated based on the AC current signal and the AC voltage signal. The specific formula is Formula 4.

[0094]

[0095] Among them, R Ω Indicates the ohmic internal resistance of the battery to be tested, A Voltage is the sinusoidal vector amplitude of the AC voltage signal, A Current is the sinusoidal vector amplitude of the AC current signal, is the phase shift of the AC voltage signal, is the phase shift of the AC current signal.

[0096] Continue to refer Figure 1 The battery health status monitoring method provided by the present invention further includes the following steps:

[0097] S3: determining electrochemical transfer parameters and diffusion parameters of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode.

[0098] The electrochemical transfer parameter may be the electrochemical transfer polarization voltage or the electrochemical transfer internal resistance, and the diffusion parameter may be the diffusion polarization voltage or the diffusion internal resistance.

[0099] S4: charging the battery to be tested to a selected state of charge by the first charging method for multiple times, obtaining the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determining the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate.

[0100] Among them, when the electrochemical transfer parameter is the electrochemical transfer polarization voltage and the diffusion parameter is the diffusion polarization voltage, the ohmic parameter change rate is calculated based on the battery ohmic polarization voltage, the electrochemical transfer parameter change rate is calculated based on the electrochemical transfer polarization voltage, and the diffusion parameter change rate is calculated based on the diffusion polarization voltage.

[0101] S5: Determine the health status of the battery to be tested according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate.

[0102] The battery health status monitoring method of the present invention improves the accuracy of battery ohmic internal resistance and battery ohmic polarization voltage detection by combining AC detection and voltage detection, thereby improving the accuracy of electrochemical transfer parameter and diffusion parameter calculation, which is conducive to more accurate determination of the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate, and is conducive to accurate monitoring and judgment of the battery health status. It also reduces the requirements for detection equipment and is more suitable for deployment in miniaturized BMS equipment.

[0103] refer to Figure 2 In one embodiment of the present invention, step S3 specifically includes the following steps:

[0104] S31: Determine the battery ohmic polarization voltage according to the ohmic internal resistance and the current in the first charging mode.

[0105] V Ω =I×R Ω (Formula 5)

[0106] Among them, V Ω Represents the battery ohmic polarization voltage of the battery under test, R Ωrepresents the ohmic internal resistance of the battery to be tested, and I represents the current in the first charging mode.

[0107] S32: Determine an electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage.

[0108] V ct =V ct +V Ω -V Ω =V2-V1-V Ω (Formula 6)

[0109] Among them, V Ω Indicates the battery ohmic polarization voltage of the battery to be tested, V ct represents the electrochemical transfer polarization voltage of the battery to be tested, V1 represents the first voltage, and V2 represents the second voltage.

[0110] S33: Determine the electrochemical transfer internal resistance according to the electrochemical transfer polarization voltage and the current in the first charging mode.

[0111]

[0112] Among them, R ct Represents the electrochemical transfer polarization voltage of the battery under test, V ct represents the electrochemical transfer polarization voltage of the battery to be tested, and I represents the current in the first charging mode.

[0113] S34: determining a diffusion polarization voltage according to the second voltage and the third voltage, and determining a diffusion internal resistance according to the diffusion polarization voltage and the current in the first charging mode.

[0114]

[0115] Among them, V diff Represents the diffusion polarization voltage of the battery under test, R diff represents the diffusion internal resistance of the battery to be tested, and I represents the current in the first charging mode.

[0116] Accordingly, in this embodiment, the ohmic parameter change rate is the change rate of the ohmic internal resistance, the electrochemical transfer parameter is the electrochemical transfer internal resistance, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer internal resistance, the diffusion parameter is the diffusion internal resistance, and the diffusion parameter change rate is the change rate of the diffusion internal resistance. In this way, by accurately calculating the ohmic internal resistance, electrochemical transfer internal resistance and diffusion internal resistance and their change rates, it is possible to accurately determine whether the battery to be tested is in a healthy state.

[0117] refer to Figure 3 In another embodiment of the present invention, step S3 specifically includes the following steps:

[0118] S310: Determine the ohmic polarization voltage of the battery according to the ohmic internal resistance and the current in the first charging mode.

[0119] The battery ohmic polarization voltage can be calculated using the aforementioned formula 5.

[0120] S320: Determine an electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage.

[0121] Among them, the electrochemical transfer polarization voltage can be calculated by the aforementioned formula 6.

[0122] S330: Determine a diffusion polarization voltage according to the second voltage and the third voltage.

[0123] The diffusion polarization voltage can be calculated using the aforementioned formula 2.

[0124] Accordingly, in this embodiment, the ohmic parameter change rate is the change rate of the battery ohmic polarization voltage, the electrochemical transfer parameter is the electrochemical transfer polarization voltage, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer polarization voltage, the diffusion parameter is the diffusion polarization voltage, and the diffusion parameter change rate is the change rate of the diffusion polarization voltage. By calculating the battery ohmic polarization voltage, the electrochemical transfer polarization voltage and the diffusion polarization voltage to calculate the corresponding change rate, the calculation can be simplified. In addition, the accuracy of the ohmic internal resistance detection is conducive to ensuring the accuracy of the battery ohmic polarization voltage calculation, and then ensuring the accuracy of the electrochemical transfer polarization voltage calculation, which is conducive to accurate monitoring of the battery health status.

[0125] refer to Figure 4 In one embodiment of the present invention, step S4 specifically includes the following steps:

[0126] S41: Determine an ohmic parameter variation curve, an electrochemical transfer parameter variation curve, and a diffusion parameter variation curve by charging the battery to be tested to a selected state of charge multiple times by the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter, and diffusion parameter of the battery to be tested from the first to the nth time after each charging, wherein n is a positive integer.

[0127] Specifically, the battery to be tested is charged to a selected state of charge using the same first charging method for multiple times, and the first voltage, the second voltage, and the third voltage are measured after each charging, and a single-frequency AC signal is applied to measure the ohmic internal resistance, and then the electrochemical transfer parameters and the diffusion parameters are calculated accordingly based on the measurement results, and then the ohmic parameter change curve, the electrochemical transfer parameter change curve, and the diffusion parameter change curve are plotted based on the results of the multiple measurements.

[0128] When the electrochemical transfer parameter is the electrochemical transfer polarization voltage and the diffusion parameter is the diffusion polarization voltage, the ohmic parameter change curve is the change curve of the battery ohmic polarization voltage of the battery to be tested, the electrochemical transfer parameter change curve is the change curve of the electrochemical transfer polarization voltage, and the diffusion parameter change curve is the change curve of the diffusion polarization voltage.

[0129] Correspondingly, when the electrochemical transfer parameter is the electrochemical transfer internal resistance and the diffusion parameter is the diffusion internal resistance, the ohmic parameter change curve is the change curve of the ohmic internal resistance of the battery to be tested, the electrochemical transfer parameter change curve is the change curve of the electrochemical transfer internal resistance, and the diffusion parameter change curve is the change curve of the diffusion internal resistance.

[0130] S42: determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate according to the ohmic parameter change curve, the electrochemical transfer parameter change curve and the diffusion parameter change curve.

[0131] Specifically, curve fitting can be performed according to the ohmic parameter change curve, electrochemical transfer parameter change curve and diffusion parameter change curve, respectively, to obtain the corresponding change function, and then the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate can be determined by calculating the slope or performing function derivation. Using the curve fitting method to determine the change rate of different parameters can make the change rate result more accurate and more conducive to improving the accuracy of battery health status monitoring.

[0132] When the electrochemical transfer parameter is the electrochemical transfer polarization voltage and the diffusion parameter is the diffusion polarization voltage, the ohmic parameter change rate is the change rate of the battery ohmic polarization voltage of the battery to be tested, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer polarization voltage, and the diffusion parameter change rate is the change rate of the diffusion polarization voltage.

[0133] Correspondingly, when the electrochemical transfer parameter is the electrochemical transfer internal resistance and the diffusion parameter is the diffusion internal resistance, the ohmic parameter change rate is the change rate of the ohmic internal resistance of the battery to be tested, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer internal resistance, and the diffusion parameter change rate is the change rate of the diffusion internal resistance.

[0134] refer to Figure 5 In another embodiment of the present invention, step S4 may specifically include the following steps:

[0135] S410: Determine an average value of ohmic parameters, an average value of electrochemical transfer parameters, and an average value of diffusion parameters by charging the battery to be tested to a selected state of charge multiple times by the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter, and diffusion parameter of the battery to be tested from the first to the nth time after each charging, wherein n is a positive integer.

[0136] S420: determining the ohmic parameter change rate according to the ohmic parameter average value and the ohmic internal resistance of the battery under test detected for the nth time; determining the electrochemical transfer parameter change rate according to the electrochemical transfer parameter average value and the electrochemical transfer parameter of the battery under test detected for the nth time; determining the diffusion parameter change rate according to the diffusion parameter average value and the diffusion parameter of the battery under test detected for the nth time.

[0137] By taking the average value of multiple measurements to calculate the change rate of different parameters, we can avoid the impact of individual abnormal values ​​on the final result, reduce interference with subsequent battery health status monitoring, and improve the accuracy of battery health status monitoring. The method of using the average value to calculate the change rate is stable, simple to calculate, and has a high fault tolerance rate.

[0138] Taking the ohmic parameter as the ohmic internal resistance, the electrochemical transfer parameter as the electrochemical transfer internal resistance, and the diffusion parameter as the diffusion internal resistance as examples, the following specifically introduces the calculation methods of the average value of the ohmic parameter, the average value of the electrochemical transfer parameter, and the average value of the diffusion parameter, as well as the calculation methods of the change rate of the ohmic parameter, the change rate of the electrochemical transfer parameter, and the change rate of the diffusion parameter.

[0139] The average values ​​of the ohmic parameters, the electrochemical transfer parameters, and the diffusion parameters can be determined using Formula 9, Formula 10, and Formula 11.

[0140]

[0141]

[0142] Among them, ∑R Ω (n) represents the sum of the ohmic internal resistance obtained from n monitorings, ∑R ct (n) represents the sum of the electrochemical transfer internal resistance obtained from n monitorings, ∑R diff (n) represents the sum of the diffusion internal resistance obtained from n monitorings, It represents the average value of the ohmic parameters of the battery under test obtained by n monitoring times. It represents the average value of the electrochemical transfer parameters of the battery under test obtained by n monitoring times. It represents the average value of diffusion parameters of the battery under test obtained by n monitorings.

[0143] The ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate can be determined using Formula 12, Formula 13 and Formula 14.

[0144]

[0145] Among them, ΔR Ω (n) represents the rate of change of the ohmic parameter, ΔR ct (n) represents the rate of change of electrochemical transfer parameters, ΔR diff(n) represents the rate of change of diffusion parameter, R Ω (n) represents the ohmic internal resistance of the battery under test obtained by the nth monitoring, R ct (n) represents the electrochemical transfer internal resistance of the battery under test obtained by the nth monitoring, R diff (n) represents the diffusion internal resistance of the battery under test obtained by the nth monitoring, It represents the average value of the ohmic parameters of the battery under test obtained by n monitoring times. It represents the average value of the electrochemical transfer parameters of the battery under test obtained by n monitoring times. It represents the average value of diffusion parameters of the battery under test obtained by n monitorings.

[0146] It should be noted that when the ohmic parameter is the battery ohmic polarization voltage, the electrochemical transfer parameter is the electrochemical transfer polarization voltage, and the diffusion parameter is the diffusion polarization voltage, the corresponding ohmic parameter average value, electrochemical transfer parameter average value, diffusion parameter average value, ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate are calculated in the same way as the corresponding parameters when the ohmic parameter is the ohmic internal resistance, the electrochemical transfer parameter is the electrochemical transfer internal resistance, and the diffusion parameter is the diffusion internal resistance, and they will not be repeated here.

[0147] refer to Figure 6 In any of the foregoing embodiments, step S5 specifically includes the following steps:

[0148] S51: Determine a determination number according to the ohmic parameter change rate, the electrochemical transfer parameter change rate, and the diffusion parameter change rate.

[0149] S52: Determine the health status of the battery to be tested according to the determination number; when the determination number is not within the preset health range, the battery to be tested is in an abnormal state; when the determination number is within the preset health range, the battery to be tested is in a healthy state.

[0150] The determination number is calculated by formula 15.

[0151]

[0152] Where N(n) represents the number of decisions made during the nth monitoring, ΔX Ω (n) represents the rate of change of the ohmic parameter, ΔX ct (n) represents the rate of change of electrochemical transfer parameters, ΔX diff (n) represents the rate of change of diffusion parameter.

[0153] Specifically, the calculation method of the determination number shown in Formula 15 is derived from the outlier calculation method, or is called Mahalanobis distance or Euclidean distance calculation, which can take into account the abnormal monitoring of multiple different parameters.

[0154] Further, the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate can be the change rate of the ohmic internal resistance, the change rate of the electrochemical transfer internal resistance and the change rate of the diffusion internal resistance, respectively. In other embodiments, the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate can also be the change rate of the battery ohmic polarization voltage, the change rate of the electrochemical transfer polarization voltage and the change rate of the diffusion polarization voltage, respectively.

[0155] The preset health range indicates that when the calculated judgment number is within this range, the battery to be tested is judged to be in a healthy state; when the calculated judgment number is not within this range, the battery to be tested is judged to be in an abnormal state and further safety testing is required. Exemplarily, the preset health range may be N(n) ≥ preset health judgment value. Among them, the selection of the preset health judgment value is related to the model of the battery and the materials used. Specifically, the preset health judgment value mainly depends on the normal increase rate of the three types of internal resistances of the battery itself, namely the ohmic internal resistance, electrochemical transfer internal resistance and diffusion internal resistance. Battery degradation is closely related to the battery material capacity structure model, etc. The preset health judgment value can usually be selected in the range of 0.5 to 1.

[0156] The determination of the preset health judgment value is derived from the calculated value of normal battery cycle data, which may include the following experimental steps: (1) laboratory testing of charge and discharge cycles under various working conditions, taking data to calculate the battery judgment value, and obtaining the normal value range; (2) experimental testing of over-temperature, external short, overcharge and other swelling injection experiments, and calculating the judgment value of the battery to obtain the abnormal value range; (3) based on the test data obtained above, the selection rules of the preset health judgment value of the battery are defined. Furthermore, it is also possible to make judgments through three parameters, two parameters, and one parameter, and select 1 to 5 combinations of preset health judgment values ​​to further trace the cause of battery degradation.

[0157] The battery health status monitoring method of the present invention monitors the voltage values ​​at the end of the charging process and the second selected time and the third selected time after the end of charging, and then determines the sum of the battery's ohmic polarization voltage and electrochemical transfer polarization voltage and the diffusion polarization voltage according to the voltage values ​​at different times, and then detects the battery's ohmic internal resistance through a selected single-frequency AC signal to accurately calculate the ohmic internal resistance, battery ohmic polarization voltage, electrochemical transfer parameters and diffusion parameters, and then more accurately calculates the corresponding change rate to improve the accuracy of battery health status monitoring.

[0158] Compared with the prior art, which calculates the ohmic internal resistance by measuring the voltage 1 millisecond after the end of charging, and then calculates the electrochemical transfer internal resistance by the voltage at the 10th millisecond after the end of charging, the technical solution of the present invention does not measure the voltage 1 millisecond after the end of charging to calculate the ohmic internal resistance alone, but combines the ohmic internal resistance and the electrochemical transfer internal resistance for consideration. The technical solution of the present invention is more accurate in detection and has a small error, so the calculated ohmic internal resistance and electrochemical transfer internal resistance are also more accurate, and the calculated battery ohmic polarization voltage and electrochemical transfer polarization voltage are also more accurate, which solves the problem that ohmic polarization and electrochemical transfer polarization cannot be accurately decoupled. In addition, the recording level requirement of the battery health status monitoring method of the present invention is millisecond level, which reduces the requirements for detection equipment and is easier to implement on miniaturized BMS equipment. Furthermore, compared with the method of using pure multi-frequency AC signals or AC impedance spectra to analyze the battery ohmic internal resistance and electrochemical transfer internal resistance, the technical solution of the present invention only requires a single-frequency AC signal for accurate detection, which is simpler and can additionally analyze the diffusion internal resistance.

[0159] The present invention also calculates the change rate of the three types of internal resistance of the battery or the voltage corresponding to the three types of internal resistance through multiple monitoring, and finally calculates the judgment number to judge the health status of the battery. It can accurately monitor the degradation of the battery in three aspects: ohmic internal resistance, electrochemical transfer internal resistance, and diffusion internal resistance, making the battery health monitoring more comprehensive and accurate. The method of using the change rate of the three types of internal resistance or the three types of voltage corresponding to them instead of the absolute value of the internal resistance or the absolute value of the voltage to calculate the judgment number in the calculation solves the problem of underreporting of safety hazards caused by the differences in the absolute values ​​of the internal resistances in the three processes of ohmic, electrochemical transfer, and diffusion, thereby improving the precision and accuracy of battery safety monitoring.

[0160] The present invention can also be compatible with various battery charging and discharging strategies. In different charging and discharging strategies, there are certain charging and discharging currents and certain cut-off states, which can meet the conditions for the battery health status monitoring method of the present invention to monitor the battery health status. The method of the present invention has the characteristics of strong compatibility.

[0161] A more specific implementation method is introduced below by taking the calculation of the change rate based on three types of internal resistance of the battery as an example.

[0162] First, the battery can be charged or discharged in a constant manner to a selected state of charge. The method of charging or discharging the battery in a constant manner to a selected state of charge can be determined according to the use of the battery or the combination of charging steps. Due to the different charging and discharging methods, the detected polarization values ​​cannot be compared with each other. In addition, the battery has obvious internal resistance differences at different SOCs. When the battery is charged and discharged at different rates, the internal resistance also has obvious differences. The larger the current, the smaller the internal resistance. Therefore, a more appropriate choice is to use a fast charging strategy, which is a charging method that charges to a constant SOC with a constant current. The same charging method (i.e., the first charging method in the aforementioned embodiment) is selected for each charge and discharge to ensure the accuracy of subsequent detection. The following is an example of charging. For example, a battery with a step fast charge as a charging strategy, whose end current is 0.5C and the end voltage state is 4.0V, then when the battery is charged to 4.0V at 0.5C during the second step fast charge, the battery health status monitoring method of the present invention can be started. Commonly used battery charging and discharging strategies are mostly 0%-80% SOC, or 10%-80% SOC fast charging strategies. For example, another battery that uses a certain step fast charging as a charging strategy has an ending current of 0.5C and an ending state of charge of 80% SOC. When the battery is performing a secondary step fast charging, after the battery is charged to 80% SOC at 0.5C, the battery health status monitoring method of the present invention begins.

[0163] like Fig. 9 As shown, after the battery is charged, the voltages at three selected moments are detected, and the three selected moments are the first moment after the charging is completed, the second moment 10 milliseconds after the charging is completed, and the third moment 30 seconds after the charging is completed. Fig.10 A data graph showing voltage values ​​obtained by multiple measurements. Fig.10 The first curve from top to bottom in the figure shows the change of the measured diffusion polarization voltage, and the second curve shows the change of the battery's ohmic polarization voltage and electrochemical transfer polarization voltage.

[0164] After standing still, the battery is tested with a single frequency AC current of a selected frequency, and a voltage and current graph is obtained to analyze the ohmic internal resistance. Fig.11 The figure shows the applied AC voltage signal with a single frequency of 1000kHz and an amplitude of 10mV. The black dots in the figure represent the test AC signals, and the black solid curve is the fitting curve after the trigonometric function fitting. The input AC voltage signal is transformed by Fourier and then has the following sinusoidal expression:

[0165] y=y0+A*sin(2πfx-x0)(Formula 16)

[0166] Among them, y0=3.54, x0=-1260.18, A=0.00357.

[0167] Fig.12 The AC current signal output by the battery is recorded after applying a 1000Hz single frequency 10mV amplitude AC voltage signal. The black dots in the figure represent the test AC signals, and the black solid line curve is the fitting curve after fitting using trigonometric functions. After Fourier transforming the output AC current signal, the following sinusoidal expression can be obtained:

[0168] y=y0+A*sin(2πfx-x0)(Formula 17)

[0169] Among them, y0=0.26794, x0=-1372.18, A=0.703.

[0170] Therefore, according to the above formula 4, the internal resistance of the battery at a frequency of 1kHz can be calculated as:

[0171]

[0172] Then, the ohmic internal resistance, electrochemical transfer internal resistance, and diffusion internal resistance are calculated according to the above formulas 5-8. Fig.13 The calculation result is shown. Then, the corresponding change rate is calculated according to the above formula 9-14, Fig.14 Finally, the judgment number is calculated according to the above formula 15: Fig.15 The battery capacity and judgment number change curve is shown.

[0173] The comparison data of battery capacity and judgment number from the 181st monitoring to the 204th monitoring are listed, and the results are obtained in Table 1 as follows.

[0174] Table 1 Comparison data of battery capacity and judgment number

[0175] Monitoring times Battery capacity (Ah) Number of decisions Abnormal determination result 181 12.3860 0.09409199 normal 182 12.2850 0.125487789 normal 183 12.1493 0.208785641 normal 184 11.9939 0.287445593 normal 185 11.8074 0.420852206 normal 186 11.5632 0.668410681 normal 187 11.2256 0.967818397 normal 188 10.6519 1.883664269 Abnormal X 189 9.1196 4.424024022 Abnormal X 190 7.4356 11.44985844 Abnormal X 191 5.6829 20.76501375 Abnormal X 192 3.5261 38.21423581 Abnormal X 193 2.6844 42.76727497 Abnormal X 194 2.2073 39.1621499 Abnormal X 195 1.6836 40.004158 Abnormal X 196 1.1870 41.40373935 Abnormal X 197 0.8572 44.39538781 Abnormal X 198 0.6594 43.51005601 Abnormal X 199 0.5508 42.08830833 Abnormal X 200 0.4771 42.49837274 Abnormal X 201 0.4112 42.24015271 Abnormal X 202 0.3530 39.88598903 Abnormal X 203 0.3142 39.74567202 Abnormal X 204 0.2870 39.35180876 Abnormal X

[0176] As shown in Table 1 above, in the 188th monitoring, the battery capacity experienced severe degradation from 10.659Ah to 9.1196Ah, and the judgment number was 1.88>1, which was judged as an abnormal battery. After 188 cycles, the battery capacity began to drop sharply, indicating that the battery had undergone severe irreversible degradation after 188 cycles, which posed a great safety hazard. The battery health status monitoring method of this application accurately and sensitively detected the abnormal state of the battery in 189 monitorings.

[0177] Second, refer to Figure 7 The embodiment of the present invention further discloses a battery health status monitoring device 1, which performs battery health status monitoring by using the battery health status monitoring method in any of the above embodiments. The battery health status monitoring device 1 includes a voltage detection module 11, an ohmic internal resistance determination module 12, a parameter determination module 13, a change rate determination module 14 and a battery health status judgment module 15.

[0178] Among them, the data output end of the voltage detection module 11 is connected to the data input end of the ohmic internal resistance determination module 12, the data output end of the ohmic internal resistance determination module 12 is connected to the data input end of the parameter determination module 13, the data output end of the parameter determination module 13 is connected to the data input end of the change rate determination module 14, and the data output end of the change rate determination module 14 is connected to the data input end of the battery health status judgment module 15.

[0179] The voltage detection module 11 is used to charge the battery to be tested to a selected state of charge in a first charging mode, and detect the voltages at both ends of the battery to be tested at a first selected time, a second selected time and a third selected time after the charging is completed, and mark them as a first voltage, a second voltage and a third voltage respectively; wherein the first voltage and the second voltage are used to determine the sum of the battery's ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage.

[0180] The ohmic internal resistance determination module 12 is used to apply a single-frequency AC signal to the battery under test, obtain a response signal of the battery under test to the single-frequency AC signal, and determine the ohmic internal resistance of the battery under test according to the single-frequency AC signal and the response signal.

[0181] The parameter determination module 13 is used to determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode.

[0182] The change rate determination module 14 is used to charge the battery to be tested to a selected state of charge through the first charging method for multiple times, obtain the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested after each charging, and determine the ohmic parameter change rate, electrochemical transfer parameter change rate and diffusion parameter change rate.

[0183] The battery health status judgment module 15 is used to determine the health status of the battery to be tested according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate.

[0184] By adopting the above technical scheme, the battery health status monitoring device 1 of the present invention can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0185] Furthermore, the parameter determination module 13 can also be used to determine the battery ohmic polarization voltage according to the ohmic internal resistance and the current in the first charging mode; determine the electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage and the second voltage; and determine the diffusion polarization voltage according to the second voltage and the third voltage. Alternatively, the parameter determination module 13 can also be used to determine the battery ohmic polarization voltage according to the ohmic internal resistance and the current in the first charging mode; determine the electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage and the second voltage; determine the electrochemical transfer internal resistance according to the electrochemical transfer polarization voltage and the current in the first charging mode; determine the diffusion polarization voltage according to the second voltage and the third voltage, and determine the diffusion internal resistance according to the diffusion polarization voltage and the current in the first charging mode. The relevant calculation formulas can be the aforementioned formulas 5-8.

[0186] The change rate determination module 14 can also be used to determine the ohmic parameter change curve, the electrochemical transfer parameter change curve and the diffusion parameter change curve according to charging the battery to be tested to a selected state of charge multiple times through the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter and diffusion parameter of the battery to be tested from the first time to the nth time after each charging, wherein n is a positive integer; and determine the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate according to the ohmic parameter change curve, the electrochemical transfer parameter change curve and the diffusion parameter change curve. Alternatively, the change rate determination module 14 can also be used to determine the average ohmic parameter value, the average electrochemical transfer parameter value, and the average diffusion parameter value according to charging the battery to be tested to a selected state of charge multiple times through the first charging method and monitoring the corresponding ohmic internal resistance, electrochemical transfer parameter, and diffusion parameter of the battery to be tested from the first to the nth time after each charging, wherein n is a positive integer; determine the ohmic parameter change rate according to the average ohmic parameter value and the ohmic internal resistance of the battery to be tested detected for the nth time; determine the electrochemical transfer parameter change rate according to the average electrochemical transfer parameter value and the electrochemical transfer parameter of the battery to be tested detected for the nth time; determine the diffusion parameter change rate according to the average diffusion parameter value and the diffusion parameter of the battery to be tested detected for the nth time. The relevant calculation formulas can be the aforementioned formulas 9-14.

[0187] The battery health status judgment module 15 can also be used to determine the judgment number according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate; determine the health status of the battery to be tested according to the judgment number; when the judgment number is not within the preset health range, the battery to be tested is in an abnormal state; when the judgment number is within the preset health range, the battery to be tested is in a healthy state. The specific calculation method of the judgment number can be the aforementioned formula 15.

[0188] The battery health status monitoring device 1 of the present invention may also include a testing module, a recording module, an analysis and calculation module, and a judgment module. The testing module is used to monitor the voltage values ​​at both ends of the battery or at both ends of each series-connected battery in the module at three moments, and is used to output an AC signal and collect the response AC signal. The recording module is used to record the voltage value and AC signal of the battery to be monitored at different moments. The calculation and analysis module is used to calculate several internal resistance values ​​or voltage values ​​of the battery, the corresponding average internal resistance value or average voltage value, the internal resistance change rate or the voltage change rate, and the judgment number based on the voltage values, AC signals, constant current values, etc. at both ends of the battery to be tested at different moments recorded by the recording module. The judgment module is used to perform battery consistency judgment based on the judgment number calculated and obtained by the calculation module.

[0189] Thirdly, reference Figure 8 The embodiment of the present invention further discloses an electronic device 2, including a memory 21 and a processor 22, wherein the memory 21 stores at least one instruction, and when the at least one instruction is executed by the processor 22, the battery health status monitoring method in any of the above embodiments is implemented. The memory 21 may include, for example, a system memory, a fixed non-volatile storage medium, etc. The system memory may store, for example, an operating system, an application program, a boot loader (BootLoader), and other programs.

[0190] In this embodiment, the electronic device 2 can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0191] In a fourth aspect, an embodiment of the present invention further discloses a computer-readable storage medium, in which at least one instruction is stored, and when the at least one instruction is executed, the battery health status monitoring method in any of the aforementioned embodiments is implemented.

[0192] By adopting the above technical solution, the computer-readable storage medium can more accurately determine the ohmic internal resistance of the battery to be tested through a single-frequency AC signal, and then more accurately determine the electrochemical transfer parameters and diffusion parameters of the battery to be tested, thereby more accurately determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate, thereby improving the accuracy of battery health status monitoring and being suitable for deployment in miniaturized BMS equipment.

[0193] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable non-transient storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0194] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0195] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0196] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0197] Although the present invention has been illustrated and described with reference to certain preferred embodiments of the present invention, it should be understood by those skilled in the art that the above is a further detailed description of the present invention in conjunction with specific embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. Those skilled in the art may make various changes in form and details, including making several simple deductions or substitutions, without departing from the spirit and scope of the present invention.

Claims

1. A battery health status monitoring method, It is characterized in that include: The battery to be tested is charged to a selected state of charge in a first charging mode, and the voltages at both ends of the battery to be tested are detected at a first selected time, a second selected time, and a third selected time after the charging is completed, and are marked as a first voltage, a second voltage, and a third voltage in sequence; wherein the first voltage and the second voltage are used to determine the sum of the battery ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage; Applying a single-frequency AC signal to the battery to be tested, obtaining a response signal of the battery to be tested to the single-frequency AC signal, and determining the ohmic internal resistance of the battery to be tested according to the single-frequency AC signal and the response signal; Determining electrochemical transfer parameters and diffusion parameters of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance, and the current value in the first charging mode; charging the battery to be tested to the selected state of charge by the first charging method for multiple times, obtaining the corresponding ohmic internal resistance, the electrochemical transfer parameter and the diffusion parameter of the battery to be tested after each charging, and determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate; The health state of the battery to be tested is determined according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate.

2. The battery health status monitoring method according to claim 1, It is characterized in that The first selected time is the time when the battery to be tested is finished charging, the second selected time is the time between 1 millisecond and 10 milliseconds after the battery to be tested is finished charging, and the third selected time is the time when the battery to be tested is left to stand and return to a balanced state after the battery to be tested is finished charging; And / or, the first charging method is a method of charging with a constant current; And / or, the selected state of charge is 80% of the battery state of charge of the battery to be tested.

3. The battery health status monitoring method according to claim 1, It is characterized in that The step of determining the electrochemical transfer parameter and the diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode specifically includes: Determining an ohmic polarization voltage of a battery according to the ohmic internal resistance and the current in the first charging mode; Determining the electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage; Determining the electrochemical transfer internal resistance according to the electrochemical transfer polarization voltage and the current in the first charging mode; determining a diffusion polarization voltage according to the second voltage and the third voltage, and determining the diffusion internal resistance according to the diffusion polarization voltage and the current in the first charging mode; Among them, the ohmic parameter change rate is the change rate of the ohmic internal resistance, the electrochemical transfer parameter is the electrochemical transfer internal resistance, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer internal resistance, the diffusion parameter is the diffusion internal resistance, and the diffusion parameter change rate is the change rate of the diffusion internal resistance.

4. The battery health status monitoring method according to claim 1, It is characterized in that Determining the electrochemical transfer parameter and diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current in the first charging mode specifically includes: Determining the battery ohmic polarization voltage according to the ohmic internal resistance and the current in the first charging mode; Determining the electrochemical transfer polarization voltage according to the battery ohmic polarization voltage, the first voltage, and the second voltage; determining a diffusion polarization voltage according to the second voltage and the third voltage; Among them, the ohmic parameter change rate is the change rate of the battery ohmic polarization voltage, the electrochemical transfer parameter is the electrochemical transfer polarization voltage, the electrochemical transfer parameter change rate is the change rate of the electrochemical transfer polarization voltage, the diffusion parameter is the diffusion polarization voltage, and the diffusion parameter change rate is the change rate of the diffusion polarization voltage.

5. The battery health status monitoring method according to claim 1, It is characterized in that The method of charging the battery to be tested to the selected state of charge by the first charging method for multiple times and monitoring the corresponding ohmic internal resistance, the electrochemical transfer parameter and the diffusion parameter of the battery to be tested after each charging is completed, and determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate specifically includes: Determine an ohmic parameter variation curve, an electrochemical transfer parameter variation curve, and a diffusion parameter variation curve according to charging the battery to be tested to the selected state of charge by the first charging method for multiple times and monitoring the ohmic internal resistance, the electrochemical transfer parameter, and the diffusion parameter of the battery to be tested corresponding to the first to nth times after each charging is completed; wherein n is a positive integer; The ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate are determined according to the ohmic parameter change curve, the electrochemical transfer parameter change curve and the diffusion parameter change curve.

6. The battery health status monitoring method according to claim 1, It is characterized in that The method of charging the battery to be tested to the selected state of charge by the first charging method for multiple times and monitoring the corresponding ohmic internal resistance, the electrochemical transfer parameter and the diffusion parameter of the battery to be tested after each charging is completed, and determining the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate specifically includes: Determine the average ohmic parameter, the average electrochemical transfer parameter and the average diffusion parameter according to charging the battery to be tested to the selected state of charge by the first charging method for multiple times and monitoring the corresponding ohmic internal resistance, the electrochemical transfer parameter and the diffusion parameter of the battery to be tested from the first time to the nth time after each charging is completed; wherein n is a positive integer; Determining the ohmic parameter change rate according to the ohmic parameter average value and the ohmic internal resistance of the battery to be tested detected for the nth time; Determine the electrochemical transfer parameter change rate according to the electrochemical transfer parameter average value and the electrochemical transfer parameter of the battery to be tested detected for the nth time; The diffusion parameter change rate is determined according to the diffusion parameter average value and the diffusion parameter of the battery to be tested detected for the nth time.

7. The battery health status monitoring method according to claim 1, It is characterized in that Determining the health state of the battery to be tested according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate specifically includes: Determining a determination number according to the ohmic parameter change rate, the electrochemical transfer parameter change rate, and the diffusion parameter change rate; Determine the health state of the battery to be tested according to the determination number; when the determination number is not within a preset health range, the battery to be tested is in an abnormal state; when the determination number is within the preset health range, the battery to be tested is in a healthy state; The determination number is determined by the following method: Wherein, N(n) represents the determination number determined by the nth monitoring, ΔX Ω (n) represents the rate of change of the ohmic parameter, ΔX ct (n) represents the rate of change of the electrochemical transfer parameter, ΔX diff (n) represents the rate of change of the diffusion parameter.

8. A battery health status monitoring device, It is characterized in that The battery health status monitoring device comprises: A voltage detection module, used to charge the battery to be tested to a selected state of charge in a first charging mode, and detect the voltages at both ends of the battery to be tested at a first selected time, a second selected time, and a third selected time after the charging is completed, and mark them as a first voltage, a second voltage, and a third voltage in sequence; wherein the first voltage and the second voltage are used to determine the sum of the battery's ohmic polarization voltage and the electrochemical transfer polarization voltage, and the second voltage and the third voltage are used to determine the diffusion polarization voltage; an ohmic internal resistance determination module, configured to apply a single-frequency AC signal to the battery to be tested, obtain a response signal of the battery to be tested to the single-frequency AC signal, and determine the ohmic internal resistance of the battery to be tested according to the single-frequency AC signal and the response signal; a parameter determination module, configured to determine an electrochemical transfer parameter and a diffusion parameter of the battery to be tested according to the first voltage, the second voltage, the third voltage, the ohmic internal resistance and the current value in the first charging mode; a change rate determination module, configured to charge the battery to be tested to the selected state of charge by the first charging method for multiple times, obtain the corresponding ohmic internal resistance, the electrochemical transfer parameter and the diffusion parameter of the battery to be tested after each charging, and determine the change rate of the ohmic parameter, the change rate of the electrochemical transfer parameter and the change rate of the diffusion parameter; The battery health status judgment module is used to determine the health status of the battery to be tested according to the ohmic parameter change rate, the electrochemical transfer parameter change rate and the diffusion parameter change rate.

9. An electronic device, It is characterized in that The electronic device includes a processor and a memory, wherein the memory stores at least one instruction, and when the at least one instruction is executed by the processor, the battery health status monitoring method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed, the battery health status monitoring method according to any one of claims 1 to 7 is implemented.

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