A lithium battery health status monitoring method and system

Abstract

The present invention relates to the field of lithium battery monitoring technology, and in particular to a lithium battery health status monitoring method and system, the method comprising: collecting current signal data of a target monitored lithium battery group and the corresponding sampling time, and performing preprocessing; calculating the battery power balance node coefficient through the preprocessed current signal data and the sampling time, obtaining the time when the target monitored lithium battery group reaches power balance, respectively calculating the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group, constructing the battery capacity health degree coefficient of the current state of the target monitored lithium battery group, calculating the battery degradation coefficient of the current state of the target monitored lithium battery group, and analyzing to obtain the battery degradation degree of the current battery state of the target monitored lithium battery group; obtaining the battery degradation coefficient of the same type of battery as the target monitored lithium battery group in a poor health state, and evaluating the health state of the target monitored lithium battery group; realizing accurate evaluation of the real-time state of the lithium battery to reflect its true state.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium battery monitoring, and in particular to a lithium battery health status monitoring method and system. Background Art

[0002] Lithium batteries are widely used in electric vehicles, mobile devices, and renewable energy storage due to their high energy density, long cycle life, and low self-discharge rate. However, as the requirements for battery performance continue to increase, monitoring the health status of lithium batteries becomes increasingly important. The state of health (SOH) of a lithium battery is an assessment of the overall performance and availability of the battery during use compared to its initial state. Monitoring the health status of a lithium battery is mainly done by collecting data such as voltage, temperature, and current in real time to assess the current health status of the battery, so as to identify potential faults in advance and avoid safety hazards such as overheating and explosion.

[0003] Current lithium battery health status monitoring methods mainly rely on real-time current data to evaluate battery condition. During actual use, the capacity of lithium batteries will gradually decrease and undergo natural aging, which in turn causes nonlinear effects. The generation of these effects will cause inconsistencies between the expected current changes and the actual measured current, reducing the accuracy of the battery health status assessment and failing to fully reflect the true situation of the battery's current status. Summary of the invention

[0004] In order to solve the technical problem that the existing methods are inaccurate in monitoring the health status of lithium batteries and affect the assessment of the real situation, the purpose of the present invention is to provide a method and system for monitoring the health status of lithium batteries. The technical solutions adopted are as follows:

[0005] Collect current signal data of the target monitored lithium battery pack and the corresponding sampling time, the current signal data including charging signal data and discharging signal data, and perform preprocessing;

[0006] The battery power balance node coefficient is calculated through the preprocessed current signal data and sampling time to obtain the time when the target monitored lithium battery group reaches power balance, and the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group are calculated respectively, and the battery capacity health degree coefficient of the current state of the target monitored lithium battery group is constructed, and the battery degradation coefficient of the current state of the target monitored lithium battery group is calculated, and the battery degradation degree of the current battery state of the target monitored lithium battery group is obtained by analysis;

[0007] Obtain the battery degradation coefficient of the same type of battery as the target monitored lithium battery group in a poor health state, and evaluate the health state of the target monitored lithium battery group.

[0008] Preferably, the current signal data of the target monitoring lithium battery pack and the corresponding sampling time are collected and preprocessed, including:

[0009] The current sensor is installed at the positive and negative connection points of the target monitored lithium battery pack, and the charging and discharging signal data during the charging and discharging process are respectively collected, and the corresponding sampling time is recorded. The current signal data is converted into digital signal data through an analog-to-digital converter and filtered.

[0010] Preferably, the battery power balance node coefficient is calculated by using the preprocessed current signal data and the sampling time to obtain the time when the target monitored lithium battery pack reaches power balance, including:

[0011] Determine the target sampling point based on the charging signal data of the target monitored lithium battery pack during a single charging process, iterate the signal sampling points with the target sampling point as the starting point to build a local window, calculate the mean of the charging signal data in the window area corresponding to the target sampling point and the slope of the charging signal data at each sampling point, and obtain the variance of the slope of the charging signal data at each sampling point in the window area corresponding to the target sampling point;

[0012] Calculate the battery power balance node coefficient, the corresponding calculation formula is:

[0013]

[0014] in, Indicates The battery power balancing node coefficient of the current signal at the target sampling point; Indicates the charging signal data target sampling points; Indicates The mean value of the charging signal data in the window area corresponding to the target sampling points; Indicates The variance of the slope of the current signal at each sampling point in the window area corresponding to the target sampling point;

[0015] Based on the battery power balance node coefficient, determine whether it exceeds the marking threshold. If so, mark the battery power balance node coefficient currently being analyzed as the battery power balance node, obtain the time point when the battery power balance node first appears in the single complete charge and discharge current signal of the target monitored lithium battery group, calculate the time difference between the start time and the start time of collecting the current signal data of the target monitored lithium battery group, and obtain the time when the current reaches power balance during a single charge and discharge process in the current state of the target monitored lithium battery group.

[0016] Preferably, calculating the charging health factor of the target monitoring lithium battery pack includes:

[0017] Based on the current signal data, the time when the current reaches the power balance in all historical charging and discharging processes is obtained;

[0018] Calculate the charging health factor of the target monitoring lithium battery pack. The corresponding calculation formula is:

[0019]

[0020] in, Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the time it takes for the current to reach the balance of charge during a single charge and discharge process of the target monitored lithium battery pack in the current state; Represents the current signal data set of all historical charging and discharging processes of the target monitored lithium battery pack; express The collection Charging signal data; Indicates The time it takes for the current to reach the charge balance in a single charging signal data in the current signal data; Represents the normalization function.

[0021] Preferably, calculating the discharge health factor of the target monitored lithium battery pack includes:

[0022] Obtain the discharge signal data of the current state of the target monitored lithium battery pack, and identify all signal peaks and corresponding time positions of the discharge signal data of the current state through peak detection technology;

[0023] The variance is calculated based on the time intervals between all adjacent signal peaks of the discharge signal data in the current state, and the average value of the current difference of all any adjacent signal sampling points of the discharge signal data in the current state is calculated to obtain the current attenuation coefficient;

[0024] Calculate the discharge health factor of the target monitoring lithium battery pack. The corresponding calculation formula is:

[0025]

[0026] in, Indicates the discharge health factor of the current state of the target monitored lithium battery pack; Represents the variance of the time intervals between all adjacent peaks in the current state of a single discharge current signal of the target monitored lithium battery pack; Indicates the current attenuation coefficient.

[0027] Preferably, the battery capacity health coefficient of the current state of the target monitoring lithium battery pack is constructed, and the corresponding calculation formula is:

[0028]

[0029] in, Indicates the battery capacity health coefficient of the current state of the target monitored lithium battery pack; Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the discharge health factor of the target monitored lithium battery pack in its current state.

[0030] Preferably, calculating the battery degradation coefficient of the current state of the target monitored lithium battery pack includes:

[0031] Based on the pre-processed charging signal data, discharging signal data, and corresponding sampling time, all charging time nodes and discharging time nodes of the target monitored lithium battery pack are obtained, and the slope is calculated through the discharging time node and the next adjacent charging time node;

[0032] Monitoring target monitors all historical current signal data of the battery pack, regards any charge and discharge process as a complete state, and obtains the battery capacity health coefficient corresponding to all complete states;

[0033] Calculate the time interval between the discharge time node and the next adjacent charging time node to obtain the depth discharge coefficient;

[0034] Calculate the battery degradation factor of the current state of the target monitoring lithium battery pack. The corresponding calculation formula is:

[0035]

[0036] in, Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Represents the collection of charging and discharging processes of all complete states of the target monitored lithium battery pack; Representing a collection Middle A complete state of charging and discharging process; Indicates The slope of the discharge time node of the charge and discharge process of a complete state and the charging time node in the next complete state; Indicates The depth of discharge coefficient corresponding to the complete state; Indicates The battery capacity health coefficient corresponding to the complete state.

[0037] Preferably, obtaining a battery degradation coefficient of a battery of the same type as the target monitored lithium battery pack in a poor health state, and evaluating the health state of the target monitored lithium battery pack includes:

[0038] The corresponding calculation formula is:

[0039]

[0040] in, Indicates the degree of difference between the target monitored lithium battery pack and the same type of batteries when the health status is poor; Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Indicates the battery degradation factor of the same type of battery with poor health status;

[0041] Based on the degree of difference, it is determined whether the abnormal threshold is exceeded. If so, the health status of the target monitored lithium battery pack is abnormal.

[0042] To solve the above problems, the present invention also provides a lithium battery health status monitoring system, comprising the following modules:

[0043] The data acquisition and preprocessing module is used to: acquire the current signal data of the target monitored lithium battery pack and the corresponding sampling time, wherein the current signal data includes charging signal data and discharging signal data, and perform preprocessing;

[0044] The data processing and analysis module is used to: calculate the battery power balance node coefficient through the preprocessed current signal data and sampling time, obtain the time when the target monitored lithium battery group reaches power balance, respectively calculate the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group, construct the battery capacity health degree coefficient of the current state of the target monitored lithium battery group, calculate the battery degradation coefficient of the current state of the target monitored lithium battery group, and analyze and obtain the battery degradation degree of the current battery state of the target monitored lithium battery group;

[0045] The status evaluation module is used to obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery group in a poor health state, and evaluate the health state of the target monitored lithium battery group.

[0046] Preferably, the lithium battery health status monitoring system also includes an early warning and alarm module and a user interface module. When the health status of the target monitored lithium battery group is abnormal, the early warning and alarm module reminds with light or sound, and transmits the battery capacity health coefficient of the current state of the target monitored lithium battery group to the user interface module.

[0047] The present invention has the following beneficial effects:

[0048] 1. The collection of charge and discharge signal data provides a sufficient basis for subsequent data analysis, improves the accuracy of comprehensively reflecting the health status of lithium battery packs, and ensures the timeliness of evaluation through real-time monitoring, quickly identifies potential problems, and ensures the safe use of battery packs. The combination of charging health factor and discharge health factor can accurately identify performance degradation, and the aging of lithium battery packs can be understood through the battery degradation factor, which is convenient for maintenance personnel to optimize the response. Comparative analysis based on batteries of the same type can more objectively evaluate the health status of lithium battery packs and enhance the reliability of evaluation results. The obtained battery capacity health factor quantifies the health status of lithium battery packs, facilitates tracking of battery performance changes, and provides a scientific basis for maintenance and replacement.

[0049] 2. A lithium battery health status monitoring system provided by the present invention has the same beneficial effects as a lithium battery health status monitoring method provided by the present invention, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 A method flow chart of a lithium battery health status monitoring method provided by one embodiment of the present invention;

[0052] Figure 2 A flowchart of a method for monitoring the health status of a lithium battery provided by an embodiment of the present invention;

[0053] Figure 3 A schematic diagram of the connection of charging and discharging time nodes of a lithium battery health status monitoring method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0054] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a lithium battery health status monitoring method and system proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0055] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0056] A specific scheme of a lithium battery health status monitoring method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0057] Existing lithium battery health status monitoring methods are prone to nonlinear effects, resulting in inconsistencies between expected current changes and actual measured currents, reducing the accuracy of battery health status assessment and failing to fully reflect the true state of the battery's current state; a lithium battery health status monitoring method provided in one embodiment of the present invention monitors the signal change characteristics in the target lithium battery pack, analyzes its own real-time health status during the charging and discharging process, obtains the battery capacity health status of the current target monitored lithium battery pack, further analyzes the normativeness of the historical charging and discharging behavior of the target monitored lithium battery pack, and corrects its battery health status, ultimately achieving an accurate assessment of the real-time status of the lithium battery. In order to implement a lithium battery health status monitoring method, a lithium battery health status monitoring system is provided. The system is essentially a software system, which is composed of modules that implement corresponding functions. The specific steps in the method are now introduced in detail.

[0058] Please combine Figure 1 and Figure 2 , which respectively show a method flow chart and a step flow chart of a lithium battery health status monitoring method provided by an embodiment of the present invention, the method comprising:

[0059] Step S1: collecting current signal data of a target monitored lithium battery pack and corresponding sampling time, wherein the current signal data includes charging signal data and discharging signal data, and performing preprocessing;

[0060] Step S2: Calculate the battery power balance node coefficient through the preprocessed current signal data and sampling time, obtain the time when the target monitored lithium battery group reaches power balance, calculate the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group respectively, construct the battery capacity health degree coefficient of the current state of the target monitored lithium battery group, calculate the battery degradation coefficient of the current state of the target monitored lithium battery group, and analyze and obtain the battery degradation degree of the current battery state of the target monitored lithium battery group;

[0061] Step S3: Obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery pack in a poor health state, and evaluate the health state of the target monitored lithium battery pack.

[0062] To explain, the health status of a lithium battery indicates the ratio of its current capacity to its designed capacity, usually referring to the performance level maintained by the battery during use, reflecting the battery's charging capacity, discharging capacity and overall efficiency. There are many influencing factors, such as a large number of charge and discharge cycles, high or low temperatures, and excessive voltage range. The health status of a lithium battery is the key to ensuring its performance and extending its service life. Through reasonable use and regular monitoring, the health status of a lithium battery can be effectively maintained, thereby improving the overall efficiency and reliability of the equipment.

[0063] Further, step S1 includes:

[0064] The current sensor is installed at the positive and negative connection points of the target monitored lithium battery pack, and the charging and discharging signal data during the charging and discharging process are respectively collected, and the corresponding sampling time is recorded. The current signal data is converted into digital signal data through an analog-to-digital converter and filtered.

[0065] As an optional implementation, the current sensor in this embodiment uses a Hall effect sensor based on the scenario. The Hall effect sensor is a sensor based on the Hall effect principle and is used to detect the presence and strength of a magnetic field. The Hall effect refers to the fact that when a magnetic field is applied perpendicular to the direction of the current in a conductor or semiconductor, a voltage difference, namely the Hall voltage, is generated in the perpendicular direction of the conductor. The Hall effect sensor can achieve contactless monitoring between the sensor and the object being measured, with little wear and high reliability. It has a fast response time and is suitable for dynamic measurement. It is also highly adaptable and can work reliably in harsh environments.

[0066] An analog-to-digital converter (ADC) is an electronic device that converts analog signals into digital signals. Analog signals are continuous and can take on any value, such as sound, temperature, voltage, etc., while digital signals are discrete and usually represented in binary form. Analog signals are sampled periodically to obtain discrete values, and the continuous analog values ​​obtained by sampling are converted into discrete digital values. The discrete values ​​obtained by quantization are then converted into binary codes, and finally digital signals are output.

[0067] Filtering is mainly used to remove or suppress noise in signals and extract the required signal components. It is used for signal modulation and demodulation in communication systems, to select signals in specific frequency bands, and to improve the signal's anti-interference ability.

[0068] Specifically, the Hall effect sensor is installed at the positive and negative connection points of the target monitoring lithium battery pack, and before monitoring, the connection of the sensor is ensured to be reliable to avoid data errors caused by poor contact; when collecting current signals, the current direction of the target monitoring lithium battery pack is regarded as positive current when charging, and negative current otherwise, so as to respectively collect the charging and discharging current signals of the target monitoring lithium battery pack during a single charging and discharging process, that is, charging signal data and discharging signal data; the sampling frequency of the Hall effect sensor is set to 1kHz, so as to capture the current changes of the target monitoring lithium battery pack in real time, and then convert the analog current signal into a digital signal through an analog-to-digital converter; the signal is then filtered to remove noise and interference to ensure data accuracy, and the processed data is transmitted to the subsequent analysis part to update the current information of the target monitoring lithium battery pack in real time.

[0069] To better illustrate, as the use time and charge and discharge times of lithium batteries increase, their capacity will gradually decrease and the reaction rate will slow down, resulting in a reduction in effective capacity. The aged battery will exhibit different current responses under the same current conditions, causing the linear relationship between the expected current and the actual battery state to deviate. Therefore, by monitoring the internal resistance and current change characteristics of the battery, the health status of the lithium battery during the charge and discharge process is analyzed in real time to obtain the capacity health level of the current target monitored lithium battery pack, and further analyze the normativeness of its historical charge and discharge behavior to correct the assessment of the battery health level, thereby achieving accurate assessment of the real-time status of the target monitored lithium battery pack.

[0070] Further, in step S2, the battery power balance node coefficient is calculated by the preprocessed current signal data and the sampling time to obtain the time when the target monitored lithium battery pack reaches power balance, including:

[0071] Step S211: Determine the target sampling point based on the charging signal data of the target monitored lithium battery pack during a single charging process, iterate the signal sampling points with the target sampling point as the starting point to construct a local window, calculate the mean of the charging signal data in the window area corresponding to the target sampling point and the slope of the charging signal data at each sampling point, and obtain the variance of the slope of the charging signal data at each sampling point in the window area corresponding to the target sampling point.

[0072] To explain, battery charge balance means that the current level of the battery remains basically the same during the charging and discharging process, and the fluctuation is close to zero, indicating that the battery is not in a significant charging or discharging state; specifically, in the charge and discharge cycle of a lithium battery, once the battery reaches the charge balance stage, its charge and discharge current will gradually decrease until it stabilizes at a constant value with almost no obvious fluctuations, indicating that the chemical reaction inside the battery has reached a state of equilibrium and the charge and discharge process is about to end.

[0073] Specifically, the target sampling point is determined based on the charging signal data of the target monitoring lithium battery pack during a single charging process, which refers to the peak value, characteristic point and other meaningful sampling points, in preparation for the subsequent extraction of signal features; the signal sampling points are iterated with the target sampling point as the starting point to construct a local window, that is, a small range area is defined around the target sampling point for local analysis and feature extraction. In this embodiment, the local window is constructed by iterating 19 signal sampling points backwards with the target sampling point as the starting point, so that it focuses on the local features of the signal and can capture the changes in the signal more accurately; if the backward iteration is less than 19 signal sampling points, all the remaining signal sampling points are used as the local window. The sampling point is taken as a window, wherein the window corresponding to the signal sampling point is regarded as the signal characteristic analysis range of the sampling point; the mean value of the charging signal data in the window area corresponding to the target sampling point and the slope of the charging signal data at each sampling point are calculated to reflect the rate of change between adjacent signal sampling points; the variance of the slope of the charging signal data at each sampling point in the window area corresponding to the target sampling point is obtained to understand the fluctuation of the charging signal data in the window area. When the variance value is smaller, it means that the slope of the current signal changes less in the current window, indicating that the charging process is relatively stable. At this time, the charging state of the target monitored lithium battery pack is relatively stable, and the charging current remains consistent.

[0074] Step S212: Calculate the battery power balance node coefficient, the corresponding calculation formula is:

[0075]

[0076] in, Indicates The battery power balancing node coefficient of the current signal at the target sampling point; Indicates the charging signal data target sampling points; Indicates The mean value of the charging signal data in the window area corresponding to the target sampling points; Indicates The variance of the slope of the current signal at each sampling point in the window area corresponding to the target sampling points.

[0077] It can be explained that under normal circumstances, when the battery reaches a balance during the charging and discharging process, it means that the charge inside the battery has reached the upper limit of charging or the lower limit of discharging, that is, when the battery charge balance node is reached, the current will gradually decrease, and the rate of current reduction is usually relatively stable.

[0078] It is understandable that since there are fractions in the calculation formula, in order to ensure the feasibility of the formula, The variance of the slope of the current signal at each sampling point in the window area corresponding to the target sampling point is explained, and there is no situation where it is zero. This is because in the actual battery charging and discharging process, due to the complexity of the chemical reaction and charge transfer process inside the target monitored lithium battery pack, the influence of factors such as temperature and aging, the resistance and capacitance characteristics inside the battery change, and the slope of the current signal cannot be completely consistent. Even near the battery charge balance node, the slope of the current signal will produce a certain variance due to slight fluctuations; and the existence of the variance explains that the charge distribution and chemical reaction state inside the battery are constantly changing.

[0079] Step S213: Determine whether the battery power balance node coefficient exceeds the marking threshold based on the battery power balance node coefficient. If so, mark the battery power balance node coefficient currently being analyzed as the battery power balance node, obtain the time point when the battery power balance node first appears in the current signal of a single complete charge and discharge of the target monitored lithium battery pack, calculate the time difference between the start time and the start time of collecting the current signal data of the target monitored lithium battery pack, and obtain the time when the current reaches power balance during a single charge and discharge process in the current state of the target monitored lithium battery pack.

[0080] Preferably, in this embodiment, the marking threshold is 0.7, and the battery power balance node coefficient is judged based on this value. If the battery power balance node coefficient is greater than the marking threshold, it is a battery power balance node, and the time difference between the time point corresponding to the node and the starting time is calculated to obtain the time when the target monitored lithium battery pack reaches power balance; conversely, if the battery power balance node coefficient is less than the marking threshold, it is not marked, indicating that the current of the target monitored lithium battery pack is changing at this time, that is, it is in normal use.

[0081] Furthermore, in step S2, the charging health factor of the target monitored lithium battery pack is calculated, including:

[0082] Based on the current signal data, the time when the current reaches the power balance in all historical charging and discharging processes is obtained;

[0083] Calculate the charging health factor of the target monitoring lithium battery pack. The corresponding calculation formula is:

[0084]

[0085] in, Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the time it takes for the current to reach the balance of charge during a single charge and discharge process of the target monitored lithium battery pack in the current state; Represents the current signal data set of all historical charging and discharging processes of the target monitored lithium battery pack; express The collection Charging signal data; Indicates The time it takes for the current to reach the charge balance in a single charging signal data in the current signal data; Represents the normalization function.

[0086] It is explained that the charging health factor is an indicator used to evaluate and represent the health status and performance of a target monitored lithium battery pack during the charging process.

[0087] To better illustrate, in actual operation, lithium batteries use a constant current-constant voltage charging strategy, initially charging with a constant current until the voltage reaches the set value, then switching to a constant voltage, with the current gradually decreasing until fully charged; healthy batteries can maintain this strategy more effectively, keeping the time to reach power balance during the charging process consistent, and calculating the charging health factor can effectively evaluate the charging health status of the target monitored lithium battery pack in its current state.

[0088] Understandably, during the discharge process of a healthy lithium battery, the time required for the battery to reach charge balance may vary significantly due to multiple factors such as load type, discharge characteristics and temperature. During the discharge process, as the battery storage capacity decreases, the internal resistance gradually increases, resulting in a decrease in the stability of the load voltage. When the battery is close to being exhausted, it cannot provide a stable current and cannot meet the load requirements, causing the waveform of the discharge current signal to exhibit a stable time-varying characteristic, thereby reducing the overall power supply capacity. As the battery approaches emptying, the discharge current will gradually decrease, showing a smooth attenuation trend. Therefore, the discharge health factor is calculated and combined with the charging health factor to measure the overall health of the target monitored lithium battery pack. That is, by reasonably calculating and evaluating the discharge health factor and the charging health factor, the use status of the target monitored lithium battery pack can be effectively monitored and managed to ensure that it is within a safe and efficient working range and to extend the battery life.

[0089] Furthermore, in step S2, the discharge health factor of the target monitored lithium battery pack is calculated, including:

[0090] Step S221: obtaining discharge signal data of the target monitored lithium battery pack in the current state, and identifying all signal peaks and corresponding time positions of the discharge signal data in the current state through peak detection technology.

[0091] It is explained that the discharge health factor is an indicator used to evaluate and represent the health status and performance of a target monitored lithium battery pack during the discharge process.

[0092] Peak detection technology is a method used to identify and quantify the maximum value points in a signal or data set, that is, to accurately identify the peak points in the signal, which usually represent important features or events in the signal data; it usually distinguishes between true peaks and fluctuations with very little noise by setting certain thresholds or conditions.

[0093] Step S222: calculating the variance based on the time intervals between all adjacent signal peaks of the discharge signal data in the current state, and calculating the average value of the current difference of all arbitrary adjacent signal sampling points of the discharge signal data in the current state to obtain the current attenuation coefficient.

[0094] It is explained that the variance is used to reflect the waveform and continuity of the discharge current. If the value is smaller, it means that the waveform of the discharge current of the target monitored lithium battery pack is smooth and continuous during the current discharge process; otherwise, the waveform of the discharge current is steep and discrete; the current attenuation coefficient is used to reflect the attenuation rate of the discharge current. If the value is larger, the attenuation rate of the discharge current is faster, indicating that the battery's power supply capacity decreases faster; otherwise, the attenuation rate of the discharge current is slower.

[0095] Step S223: Calculate the discharge health factor of the target monitored lithium battery pack, and the corresponding calculation formula is:

[0096]

[0097] in, Indicates the discharge health factor of the current state of the target monitored lithium battery pack; Represents the variance of the time intervals between all adjacent peaks in the current state of a single discharge current signal of the target monitored lithium battery pack; Indicates the current attenuation coefficient.

[0098] It is explained that by analyzing the stability of the discharge current waveform and the overall attenuation rate, the discharge health status of the target monitored lithium battery pack in its current state can be effectively evaluated.

[0099] It is understandable that in the actual use of the target monitored lithium battery pack, the variance of the time intervals between all adjacent peaks in the single discharge current signal of the current state of the target monitored lithium battery pack does not equal 0. If it equals 0, it means that in the current discharge process, the discharge signal data of the target monitored lithium battery pack has not fluctuated at all, that is, the time intervals between all adjacent peaks are exactly the same; however, this situation is almost impossible to occur in real life. During the discharge process, the battery is usually affected by multiple factors such as internal impedance changes, temperature changes, load changes, etc., which causes fluctuations in the discharge current signal.

[0100] Furthermore, in step S2, a battery capacity health coefficient of the current state of the target monitored lithium battery pack is constructed, and the corresponding calculation formula is:

[0101]

[0102] in, Indicates the battery capacity health coefficient of the current state of the target monitored lithium battery pack; Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the discharge health factor of the target monitored lithium battery pack in its current state.

[0103] Understandably, the battery capacity health coefficient mainly affects the battery's service life. The currently calculated battery capacity health coefficient cannot fully reflect the health status of the target monitored lithium battery pack. Generally, lithium batteries will experience reduced storage efficiency and aging after multiple charge and discharge cycles. Frequent improper charging and deep discharge will aggravate the degradation of lithium batteries. Therefore, a comprehensive analysis is also required in combination with the battery degradation coefficient.

[0104] Furthermore, in step S2, the battery degradation coefficient of the current state of the target monitored lithium battery pack is calculated, including:

[0105] Step S231: based on the preprocessed charging signal data, discharging signal data, and corresponding sampling time, all charging time nodes and discharging time nodes of the target monitored lithium battery pack are obtained, and the slope is calculated through the discharging time node and the next adjacent charging time node.

[0106] It is explained that the battery degradation factor is used to describe the degree of performance degradation caused by factors such as cycling, temperature changes, and charge and discharge rates during battery use.

[0107] Step S232: monitor all historical current signal data of the target monitoring battery pack, regard any charge and discharge process as a complete state, and obtain battery capacity health coefficients corresponding to all complete states.

[0108] Step S233: Calculate the time interval between the discharge time node and the next adjacent charge time node to obtain the depth of discharge coefficient.

[0109] To be clear, deep discharge refers to discharging the battery to close to its lowest voltage level. This operation may damage the internal structure of the battery, resulting in battery capacity decay and shortened cycle life.

[0110] See also Figure 3 Specifically, in this embodiment, all charging time nodes of the target monitored lithium battery pack are recorded as set A, and all discharging time nodes are recorded as set B. The time node after each charging process of the target monitored lithium battery pack is completed is connected with the time node of the discharge process completed closest to the time series, wherein, Indicates the charging end time of the target monitoring lithium battery pack. Indicates the discharge end time point of the target monitored lithium battery pack. For a complete charging and discharging process, It is the discharge shelving time after a discharge, and the length of the discharge shelving time is used to determine whether the target monitored lithium battery pack has deep discharge. If the discharge shelving time is longer, there is no deep discharge, otherwise there is deep discharge.

[0111] The slope is calculated by the discharge time node and the next adjacent charge time node, for example The slope of the line between them, the larger the value, the more it means that the target monitored lithium battery pack will be discharged immediately after a charge, and the load power during discharge is large.

[0112] Take any charge and discharge process as a complete state, that is, , ...any charge and discharge process in order to obtain the battery capacity health coefficient of the lithium battery pack with the goal of monitoring all complete states.

[0113] Calculate the time interval between the discharge time node and the next adjacent charging time node, such as The time interval between them is used to obtain the deep discharge coefficient of the target monitored lithium battery pack in the complete state of the previous discharge process. The smaller the value, the deeper the deep discharge of the target monitored lithium battery pack is in the current analysis state.

[0114] Step S234: Calculate the battery degradation coefficient of the current state of the target monitored lithium battery pack, and the corresponding calculation formula is:

[0115]

[0116] in, Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Represents the collection of charging and discharging processes of all complete states of the target monitored lithium battery pack; Representing a collection Middle A complete state of charging and discharging process; Indicates The slope of the discharge time node of the charge and discharge process of a complete state and the charging time node in the next complete state; Indicates The depth of discharge coefficient corresponding to the complete state; Indicates The battery capacity health coefficient corresponding to the complete state.

[0117] It can be explained that when the target monitored lithium battery pack is degraded, its health will gradually deteriorate during a single charge and discharge process; and frequent deep discharge will aggravate the damage to the internal structure of the battery, leading to the attenuation of battery capacity and the shortening of cycle life, further deteriorating the overall health of the target monitored lithium battery pack.

[0118] Further, step S3 includes:

[0119] The corresponding calculation formula is:

[0120]

[0121] in, Indicates the degree of difference between the target monitored lithium battery pack and the same type of batteries when the health status is poor; Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Indicates the battery degradation factor of batteries of the same type with poor health status.

[0122] Based on the degree of difference, it is determined whether the abnormal threshold is exceeded. If so, the health status of the target monitored lithium battery pack is abnormal.

[0123] For better explanation, a poor health status means that the health status of this type of lithium battery is 0.

[0124] Obtain the difference between the target monitored lithium battery group and the same type of batteries when their health status is poor, so as to conduct a systematic evaluation of the target monitored lithium battery group, timely discover potential problems, optimize battery management, improve safety and efficiency, analyze the normativeness of the historical charging and discharging behavior of the monitored target monitored lithium battery group, and correct the battery health status, thereby achieving an accurate evaluation of the real-time status of the target monitored lithium battery group, and both timeliness and accuracy are guaranteed.

[0125] Preferably, in order to evaluate the health status of the target monitored lithium battery group, the difference between the target monitored lithium battery group and the same type of batteries when they are in good health status can also be calculated, and the analysis of the same type of batteries when they are in poor health status is similar, where a good health status means that the health status of this type of lithium battery is 1.

[0126] Specifically, in this embodiment, the abnormal threshold is 0.5. When the difference degree exceeds the abnormal threshold, the health status of the target monitored lithium battery pack is abnormal. Otherwise, the target monitored lithium battery pack operates normally.

[0127] An embodiment of the present invention also provides a lithium battery health status monitoring system, the system comprising the following modules:

[0128] The data acquisition and preprocessing module is used to: acquire the current signal data of the target monitored lithium battery pack and the corresponding sampling time, the current signal data includes charging signal data and discharging signal data, and perform preprocessing;

[0129] The data processing and analysis module is used to: calculate the battery power balance node coefficient through the preprocessed current signal data and sampling time, obtain the time when the target monitored lithium battery group reaches power balance, respectively calculate the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group, construct the battery capacity health degree coefficient of the current state of the target monitored lithium battery group, calculate the battery degradation coefficient of the current state of the target monitored lithium battery group, and analyze and obtain the battery degradation degree of the current battery state of the target monitored lithium battery group;

[0130] The status evaluation module is used to obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery group in a poor health state, and evaluate the health state of the target monitored lithium battery group.

[0131] Furthermore, the lithium battery health status monitoring system also includes an early warning and alarm module and a user interface module. When the health status of the target monitored lithium battery pack is abnormal, the early warning and alarm module reminds with light or sound, and transmits the battery capacity health coefficient of the current state of the target monitored lithium battery pack to the user interface module.

[0132] It is explained that the data acquisition and preprocessing module, data processing and analysis module, status assessment module, early warning and alarm module and user interface module cooperate with each other. The data acquisition and preprocessing module provides the basis for subsequent signal data processing and analysis, and the analysis results provide data support for the status assessment module. The early warning module ensures system security based on the assessment results, and the user interface module ensures that users can interact with the system conveniently. Continuity analysis is performed on the target monitored lithium battery pack to ensure the accuracy of the target monitored lithium battery pack while ensuring the timeliness of monitoring the health status of the lithium battery pack.

[0133] Preferably, in the system, data transmission between different modules relies on wireless network technology.

[0134] The data acquisition and preprocessing module is used to monitor and collect relevant signal data that needs to be analyzed from the lithium battery pack in real time, record the sampling time of the signal data, and ensure the timeliness and accuracy of the signal data; preprocess the collected signal data, such as removing noise, data smoothing, normalization, etc., to improve the accuracy of subsequent analysis; the data processing and analysis module is used to analyze the preprocessed signal data, calculate the charging health factor, discharge health factor, degradation factor and battery capacity health factor of the lithium battery pack, etc., to quantitatively display the current status of the lithium battery pack; the status evaluation module comprehensively analyzes the current status of the lithium battery pack, evaluates its overall health status, and obtains a more objective evaluation result.

[0135] The early warning and alarm module, through the setting of abnormal thresholds, triggers light or sound for early warning when certain conditions are met, promptly notifies the user of possible safety hazards in the battery, and identifies specific problems of the lithium battery pack, such as overheating, overcharging or abnormal discharge, in combination with the correlation coefficients in the data processing and analysis module; the user interface module is used to display the real-time health status coefficient of the target monitored lithium battery pack for visual management of relevant personnel, allowing users to set parameters, view alarm information, and other operations, thereby improving the convenience and operability of users in obtaining information.

[0136] It can be understood that when the various modules of a lithium battery health status monitoring system are in operation, it is necessary to utilize a lithium battery health status monitoring method provided by the aforementioned embodiment. Therefore, whether the data acquisition and preprocessing module, the data processing and analysis module, the status assessment module, the early warning and alarm module and the user interface module are integrated or different hardware is configured to produce functions similar to the effects achieved by the present invention, they all fall within the scope of protection of the present invention.

[0137] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0138] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for monitoring the health status of a lithium battery, characterized in that: The method comprises: Collect current signal data of the target monitored lithium battery pack and the corresponding sampling time, the current signal data including charging signal data and discharging signal data, and perform preprocessing; The battery power balance node coefficient is calculated through the preprocessed current signal data and the sampling time to obtain the time when the target monitored lithium battery group reaches power balance, and the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group are calculated respectively. The battery capacity health degree coefficient of the current state of the target monitored lithium battery group is constructed according to the charging health coefficient and the discharging health coefficient, and the battery degradation coefficient of the current state of the target monitored lithium battery group is calculated. The battery degradation degree of the current battery state of the target monitored lithium battery group is obtained by analysis; Obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery group in a poor health state, and evaluate the health state of the target monitored lithium battery group; The calculation formula of the battery power balance node coefficient is: in, Indicates The battery power balancing node coefficient of the current signal at the target sampling point; Indicates the charging signal data target sampling points; Indicates The mean value of the charging signal data in the window area corresponding to the target sampling points; Indicates The variance of the slope of the current signal at each sampling point in the window area corresponding to the target sampling point; Based on the battery power balance node coefficient, determine whether it exceeds the marking threshold. If so, mark the battery power balance node coefficient currently analyzed as a battery power balance node, obtain the time point when the battery power balance node first appears in the single complete charge and discharge current signal of the target monitored lithium battery group, calculate the time difference between the start time and the start time of collecting the current signal data of the target monitored lithium battery group, and obtain the time when the current reaches power balance in the single charge and discharge process of the current state of the target monitored lithium battery group; Calculate the charging health factor of the target monitoring lithium battery pack, including: Based on the current signal data, the time when the current reaches the power balance in all historical charging and discharging processes is obtained; Calculate the charging health factor of the target monitoring lithium battery pack. The corresponding calculation formula is: in, Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the time it takes for the current to reach the balance of charge during a single charge and discharge process of the target monitored lithium battery pack in the current state; Represents the current signal data set of all historical charging and discharging processes of the target monitored lithium battery pack; express The collection Charging signal data; Indicates The time it takes for the current to reach the charge balance in a single charging signal data in the current signal data; represents the normalization function; in, Indicates the discharge health factor of the current state of the target monitored lithium battery pack; Represents the variance of the time intervals between all adjacent peaks in the current state of a single discharge current signal of the target monitored lithium battery pack; Represents the current attenuation coefficient; The calculation formula of the battery degradation factor of the current state of the target monitoring lithium battery pack is: in, Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Represents the collection of charging and discharging processes of all complete states of the target monitored lithium battery pack; Representing a collection Middle A complete state of charging and discharging process; Indicates The slope of the discharge time node of the charge and discharge process of a complete state and the charging time node in the next complete state; Indicates The depth of discharge coefficient corresponding to the complete state; Indicates The battery capacity health coefficient corresponding to the complete state.

2. A lithium battery health status monitoring method as claimed in claim 1, characterized in that: Collect the current signal data of the target monitoring lithium battery pack and the corresponding sampling time, and perform preprocessing, including: The current sensor is installed at the positive and negative connection points of the target monitored lithium battery pack, and the charging and discharging signal data during the charging and discharging process are respectively collected, and the corresponding sampling time is recorded. The current signal data is converted into digital signal data through an analog-to-digital converter and filtered.

3. A lithium battery health status monitoring method as claimed in claim 1, characterized in that: The battery power balance node coefficient is calculated through the pre-processed current signal data and sampling time to obtain the time when the target monitored lithium battery pack reaches power balance, which also includes: The target sampling point is determined based on the charging signal data of the target monitored lithium battery pack during a single charging process. The signal sampling points are iterated with the target sampling point as the starting point to construct a local window. The mean of the charging signal data in the window area corresponding to the target sampling point and the slope of the charging signal data at each sampling point are calculated to obtain the variance of the slope of the charging signal data at each sampling point in the window area corresponding to the target sampling point.

4. A lithium battery health status monitoring method as claimed in claim 1, characterized in that: Calculate the discharge health factor of the target monitoring lithium battery pack, including: Obtain the discharge signal data of the current state of the target monitored lithium battery pack, and identify all signal peaks and corresponding time positions of the discharge signal data of the current state through peak detection technology; The variance is calculated based on the time intervals between all adjacent signal peaks of the discharge signal data in the current state, and the current attenuation coefficient is obtained by calculating the average value of the current difference of all arbitrary adjacent signal sampling points of the discharge signal data in the current state.

5. A lithium battery health status monitoring method as claimed in claim 4, characterized in that: Construct the battery capacity health coefficient of the current state of the target monitoring lithium battery pack, and the corresponding calculation formula is: in, Indicates the battery capacity health coefficient of the current state of the target monitored lithium battery pack; Indicates the charging health factor of the current state of the target monitored lithium battery pack; Indicates the discharge health factor of the target monitored lithium battery pack in its current state.

6. A lithium battery health status monitoring method as claimed in claim 5, characterized in that: Calculate the battery degradation factor of the current state of the target monitored lithium battery pack, including: Based on the pre-processed charging signal data, discharging signal data, and corresponding sampling time, all charging time nodes and discharging time nodes of the target monitored lithium battery pack are obtained, and the slope is calculated through the discharging time node and the next adjacent charging time node; Monitoring target monitors all historical current signal data of the battery pack, regards any charge and discharge process as a complete state, and obtains the battery capacity health coefficient corresponding to all complete states; The depth of discharge coefficient is obtained by calculating the time interval between the discharge time node and the next adjacent charging time node.

7. A lithium battery health status monitoring method as claimed in claim 1, characterized in that: Obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery pack in a poor health state, and evaluate the health state of the target monitored lithium battery pack, including: The corresponding calculation formula is: in, Indicates the degree of difference between the target monitored lithium battery pack and the same type of batteries when the health status is poor; Indicates the battery degradation factor of the current state of the target monitored lithium battery pack; Indicates the battery degradation factor of the same type of battery with poor health status; Based on the degree of difference, it is determined whether the abnormal threshold is exceeded. If so, the health status of the target monitored lithium battery pack is abnormal.

8. A lithium battery health status monitoring system, the system being used to perform the steps of the method according to any one of claims 1 to 7, characterized in that: Includes the following modules: The data acquisition and preprocessing module is used to: acquire the current signal data of the target monitored lithium battery pack and the corresponding sampling time, wherein the current signal data includes charging signal data and discharging signal data, and perform preprocessing; The data processing and analysis module is used to: calculate the battery power balance node coefficient through the preprocessed current signal data and sampling time, obtain the time when the target monitored lithium battery group reaches power balance, respectively calculate the charging health coefficient and the discharging health coefficient of the target monitored lithium battery group, construct the battery capacity health degree coefficient of the current state of the target monitored lithium battery group, calculate the battery degradation coefficient of the current state of the target monitored lithium battery group, and analyze and obtain the battery degradation degree of the current battery state of the target monitored lithium battery group; The status evaluation module is used to obtain the battery degradation coefficient of the battery of the same type as the target monitored lithium battery group in a poor health state, and evaluate the health state of the target monitored lithium battery group.

9. A lithium battery health status monitoring system as claimed in claim 8, characterized in that: The lithium battery health status monitoring system also includes an early warning and alarm module and a user interface module. When the health status of the target monitored lithium battery pack is abnormal, the early warning and alarm module reminds with light or sound, and transmits the battery capacity health coefficient of the current state of the target monitored lithium battery pack to the user interface module.

Images