A method and system for detecting battery charge and discharge pulse frequency

Abstract

The present application provides a battery charge and discharge pulse frequency detection method and system, which divides the pulse current signal of the target battery during charge and discharge into multiple pulse signal segments, determines the static offset of the current of the target battery during charge and discharge based on the local current characteristics of each pulse signal segment; determines the time domain positioning error of the time interval through the static offset and the pulse width of the pulse current signal; monitors the surface temperature of the target battery during charge and discharge, and determines the disturbance characteristics of the target battery's temperature on the current during charge and discharge based on all monitored temperatures and the pulse current signal; performs pulse identification on the pulse current signal based on all time domain positioning errors and disturbance characteristics, obtains the effective pulse time sequence of the target battery during charge and discharge, and determines the effective pulse frequency of the target battery during charge and discharge based on the effective pulse time sequence. The use of the present application solution can reduce the impact of current signal drift on pulse frequency detection during battery charge and discharge.

Description

Technical Field

[0001] The present application relates to the technical field of pulse frequency detection, and more specifically, to a method and system for detecting battery charge and discharge pulse frequency. Background Art

[0002] Pulse frequency detection refers to a technology that analyzes the current or voltage pulse signals during the battery charging and discharging process, extracts their periodic characteristics (such as pulse interval, duty cycle, rise / fall edge time, etc.), and then calculates the pulse repetition frequency. This technology is widely used in battery management systems (BMS), power electronics control, energy recovery systems and other fields.

[0003] With the widespread application of new energy batteries (such as lithium-ion batteries and solid-state batteries) in electric vehicles, energy storage systems and other fields, accurate monitoring of battery charging and discharging status is crucial to improving battery life and ensuring safety. At present, battery management systems usually rely on parameters such as voltage, current and temperature for state estimation. However, during the dynamic charging and discharging process, the current signal often contains high-frequency pulse components (such as pulse width modulation charging and discharging, and current fluctuations during fast charging). These pulse signals may be interfered by factors such as temperature drift and circuit noise, making it difficult for traditional methods to accurately extract the effective pulse frequency. Existing technologies (such as fast Fourier transform analysis and sliding average filtering) are prone to frequency misjudgment in strong noise environments, and do not fully consider the dynamic impact of temperature on the current signal, resulting in insufficient robustness of pulse frequency detection. Therefore, how to reduce the impact of current signal drift on pulse frequency detection during battery charging and discharging has become a problem facing the industry. Summary of the Invention

[0004] The present application provides a method and system for detecting the charge and discharge pulse frequency of a battery, which can reduce the influence of current signal drift on the pulse frequency detection during the charge and discharge process of the battery.

[0005] In a first aspect, the present application provides a method for detecting the charge and discharge pulse frequency of a battery, comprising the following steps:

[0006] Collect pulse current signals of the target battery during charging and discharging;

[0007] Dividing the pulse current signal into a plurality of pulse signal segments according to a preset time window, and determining a static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment;

[0008] Performing time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal by using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval;

[0009] Monitoring the surface temperature of the target battery during charging and discharging, correlating all monitored temperatures with the pulse current signal, and thereby obtaining a characteristic of the temperature disturbance on the current of the target battery during charging and discharging;

[0010] The pulse current signal is pulse identified according to all time domain positioning errors and the disturbance characteristics to obtain an effective pulse time sequence of the target battery during charging and discharging, and the effective pulse frequency of the target battery during charging and discharging is determined based on the effective pulse time sequence.

[0011] In some embodiments, dividing the pulse current signal into a plurality of pulse signal segments according to a preset time window specifically includes:

[0012] Determine the preset time window;

[0013] The pulse current signal is divided according to the preset time window to obtain a plurality of pulse signal segments.

[0014] In some embodiments, determining the static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment specifically includes:

[0015] Determine the local current characteristics of each pulse signal segment;

[0016] determining a plurality of DC component values ​​of the pulse current signal according to all local current characteristics;

[0017] All DC component values ​​are taken as static offsets of the target battery's current during charging and discharging.

[0018] In some embodiments, performing time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal using the static offset and the pulse width of the pulse current signal to obtain the time domain positioning error of the time interval specifically includes:

[0019] determining a pulse width of the pulse current signal;

[0020] determining the time interval between adjacent rising edges of the pulse current signal;

[0021] Performing positioning correction on the time interval according to the static offset and the pulse width to obtain multiple correction values ​​of the time interval;

[0022] The time domain positioning error of the time interval is determined based on all the corrections.

[0023] In some embodiments, correlation analysis is performed on all monitored temperatures and the pulse current signal to obtain the disturbance characteristics of the target battery's temperature on the current during charging and discharging, specifically including:

[0024] Correlating all monitored temperatures with the pulse current signal to obtain temperature-pulse correlation information;

[0025] Determining a correlation coefficient sequence between the temperature and current of the target battery during charging and discharging according to the temperature-pulse correlation information;

[0026] The disturbance characteristics of the temperature on the current of the target battery during charging and discharging are determined by the correlation coefficient sequence.

[0027] In some embodiments, performing pulse identification on the pulse current signal based on all time-domain positioning errors and the disturbance characteristics to obtain an effective pulse timing sequence of the target battery during charging and discharging specifically includes:

[0028] Determining dynamic adjustment information of the pulse current signal according to all time domain positioning errors and the disturbance characteristics;

[0029] The pulse current signal is dynamically adjusted according to the dynamic adjustment information to obtain an effective pulse timing sequence of the target battery during charging and discharging.

[0030] In some embodiments, determining the effective pulse frequency during charging and discharging of the target battery based on the effective pulse time-stamp sequence specifically includes:

[0031] Determining each credible rising edge in the valid pulse time stamp sequence;

[0032] The effective pulse frequency during charging and discharging of the target battery is determined based on all credible rising edges.

[0033] In some embodiments, a current sensor is used to collect pulse current signals of the target battery during charging and discharging.

[0034] In some embodiments, the surface temperature of the target battery during charging and discharging is monitored by a temperature sensor.

[0035] In a second aspect, the present application provides a battery charge and discharge pulse frequency detection system, comprising:

[0036] An acquisition module is used to collect pulse current signals of the target battery during charging and discharging;

[0037] a processing module, configured to divide the pulse current signal into a plurality of pulse signal segments according to a preset time window, and determine a static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment;

[0038] The processing module is further configured to perform time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal by using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval;

[0039] The processing module is further configured to monitor the surface temperature of the target battery during charging and discharging, and to correlate and analyze all monitored temperatures with the pulse current signal to obtain a disturbance characteristic of the target battery's temperature on the current during charging and discharging;

[0040] An execution module is used to perform pulse identification on the pulse current signal according to all time domain positioning errors and the disturbance characteristics, obtain an effective pulse time sequence of the target battery during charging and discharging, and determine the effective pulse frequency of the target battery during charging and discharging based on the effective pulse time sequence.

[0041] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0042] In the battery charge and discharge pulse frequency detection method and system provided in the present application, the pulse current signal of the target battery during charge and discharge is first collected; the pulse current signal is divided into multiple pulse signal segments according to a preset time window, and the static offset of the current of the target battery during charge and discharge is determined based on the local current characteristics of each pulse signal segment; the time interval of adjacent rising edges in the pulse current signal is time-domain positioned and calibrated by the static offset and the pulse width of the pulse current signal to obtain the time-domain positioning error of the time interval; the surface temperature of the target battery during charge and discharge is monitored, and all the monitored temperatures are correlated and analyzed with the pulse current signal to obtain the disturbance characteristics of the temperature on the current of the target battery during charge and discharge; the pulse current signal is pulse identified according to all the time-domain positioning errors and the disturbance characteristics to obtain the effective pulse time-mark sequence of the target battery during charge and discharge, and the effective pulse frequency of the target battery during charge and discharge is determined based on the effective pulse time-mark sequence.

[0043] It can be seen that in the process of detecting the battery charge and discharge pulse frequency, the present application first divides the pulse signal segments by a preset time window, and determines the current static offset based on the local current characteristics, and uses the segmented processing method to refine the current signal change, effectively capture the signal drift trend, and avoid masking the local offset details due to the overall analysis, so as to provide accurate basic data for the subsequent time domain positioning calibration, and reduce the error caused by signal drift from the root; then, the time domain positioning calibration of the time interval of adjacent rising edges is performed in combination with the static offset and the pulse width, and the time domain positioning error is introduced to quantify the offset effect, which not only considers the static characteristics of the signal drift, but also combines the pulse width as a key parameter, evaluates the time interval accuracy through the time domain positioning error, constrains and corrects the time positioning deviation caused by signal drift, and improves the detection accuracy of the pulse time interval; then, the battery is monitored in real time. The cell surface temperature is correlated with the pulse current signal and analyzed to obtain the disturbance characteristics of temperature on the current. Since temperature change is one of the important factors causing current signal drift, incorporating temperature disturbance into the analysis system can dynamically compensate for signal fluctuations caused by temperature change, avoid misjudging the pulse frequency due to temperature influence, and make the detection results more consistent with the actual charge and discharge status of the battery. Thus, the pulse current signal is identified by combining the time domain positioning error and the disturbance characteristics to form a double verification mechanism. The time domain positioning error ensures the accuracy of pulse time positioning, and the disturbance characteristics eliminate interference signals caused by factors such as temperature. The two work together to achieve accurate screening of effective pulse time-scale sequences, effectively eliminate false pulses caused by signal drift, and provide reliable data support for pulse frequency calculation. Finally, the effective pulse frequency of the target battery during charging and discharging is determined based on the effective pulse time-scale sequence. The above scheme can reduce the impact of current signal drift on pulse frequency detection during battery charging and discharging. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is an exemplary flow chart of a method for detecting battery charge and discharge pulse frequency according to some embodiments of the present application;

[0045] Figure 2 is an exemplary flow chart of determining a static offset according to some embodiments of the present application;

[0046] Figure 3 is a partial diagram of a pulse current signal according to some embodiments of the present application;

[0047] Figure 4 is a structural diagram of a battery charge and discharge pulse frequency detection system according to some embodiments of the present application;

[0048] Figure 5 It is a structural diagram of a computer device for implementing a method for detecting battery charge and discharge pulse frequency according to some embodiments of the present application. DETAILED DESCRIPTION

[0049] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0050] refer to Figure 1 , which is an exemplary flow chart of a method for detecting a battery charge and discharge pulse frequency according to some embodiments of the present application. The battery charge and discharge pulse frequency detection method 100 mainly includes the following steps:

[0051] In step 101, pulse current signals of a target battery during charging and discharging are collected.

[0052] In specific implementation, the current path of the current sensor is connected in series with the charge and discharge circuit of the target battery to charge and discharge the target battery. The pulse current signal of the target battery during charging and discharging is collected by the series current sensor. In other embodiments, other methods can also be used for collection, which will not be elaborated here.

[0053] In step 102, the pulse current signal is divided into a plurality of pulse signal segments according to a preset time window, and a static offset of the current of the target battery during charging and discharging is determined based on the local current characteristics of each pulse signal segment.

[0054] In some embodiments, dividing the pulse current signal into a plurality of pulse signal segments according to a preset time window can be achieved by using the following steps:

[0055] Determine the preset time window;

[0056] The pulse current signal is divided according to the preset time window to obtain a plurality of pulse signal segments.

[0057] In a specific implementation, first, the historical pulse current signal of the target battery is used, and an integer multiple of the pulse period of the historical pulse current signal is used as a preset time window to ensure that multiple pulse periods are included in the divided signal segment. Then, the pulse current signal is preprocessed using the median filtering method in the prior art to remove noise in the pulse current signal (such as removing isolated noise points and retaining the true change trend of the signal). Finally, a sliding step size is set, which is smaller than the preset time window. Starting from the starting position of the pulse current signal, the preset time window is gradually slid according to the sliding step size. Each sliding captures a signal segment within the current time period, and each captured signal segment is used as a pulse signal segment. For example, the first window is from 0 milliseconds to 120 milliseconds, the second window is from 60 milliseconds to 180 milliseconds, the third window is from 120 milliseconds to 240 milliseconds, and so on, until the window slides past the end position of the entire signal. In other embodiments, other division methods can also be used, which are not limited here.

[0058] It should be noted that the pulse signal segment in the present application represents a signal segment in a pulse current signal, which can be used to analyze the characteristics of the pulse current signal.

[0059] In some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart for determining a static offset in some embodiments of the present application. In this embodiment, determining the static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment can be achieved by using the following steps:

[0060] First, in step 1021, the local current characteristics of each pulse signal segment are determined;

[0061] Then, in step 1022, multiple DC component values ​​of the pulse current signal are determined based on all local current characteristics;

[0062] Finally, in step 1023, all DC component values ​​are used as static offsets of the target battery's current during charging and discharging.

[0063] It should be noted that the static offset changes slowly and exists in the entire signal, while the real pulse has transient characteristics. Therefore, dynamic estimation and compensation of the offset can be achieved by time domain or frequency domain separation of local current characteristics.

[0064] In the specific implementation, first, a pulse signal segment is selected as the selected pulse signal segment, the mean of the amplitude in each pulse period in the selected pulse signal segment is calculated, all the mean values ​​are used as the local current characteristics of the selected pulse signal segment, and the local current characteristics of the remaining pulse signal segments are further determined, wherein the local current characteristics represent the local current characteristics in the signal segment; then, for each local current characteristic, the least squares method is used to perform linear fitting on all the mean values ​​in the local current characteristics to obtain a fitting straight line, and the intercept of the fitting straight line is used as the DC component value, thereby obtaining multiple DC component values, wherein the DC component value represents the parameter value of the average level of the current in the pulse signal segment; in other embodiments, other methods can also be used for implementation, which are not limited here.

[0065] It should be noted that the static offset in this application represents the low-frequency component of the current signal of the target battery that drifts slowly during charging and discharging, and can be used to correct the pulse current signal to ensure accurate measurement of the charging and discharging current.

[0066] In step 103, a time domain positioning calibration is performed on the time interval between adjacent rising edges in the pulse current signal using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval.

[0067] In some embodiments, time domain positioning calibration is performed on the time interval between adjacent rising edges of the pulse current signal using the static offset and the pulse width of the pulse current signal to obtain the time domain positioning error of the time interval. The following steps can be used:

[0068] determining a pulse width of the pulse current signal;

[0069] determining the time interval between adjacent rising edges of the pulse current signal;

[0070] Performing positioning correction on the time interval according to the static offset and the pulse width to obtain multiple correction values ​​of the time interval;

[0071] The time domain positioning error of the time interval is determined based on all the corrections.

[0072] It should be noted that since static offset will change the time when the signal exceeds or falls below the threshold, thereby affecting the accurate measurement of the rising edge time interval, the static offset in the pulse current signal is removed to return the signal to a relatively real dynamic change state. In addition, the difference in pulse width will cause the slope and shape of the rising edge to change, thereby affecting the accurate identification of the rising edge and the measurement of the time interval. Therefore, by combining the pulse current signal after static offset compensation and the known pulse width characteristics, the time intervals between adjacent pulse rising edges can be accurately identified, and the timing stability of the signal can be evaluated by statistically analyzing the fluctuations of these intervals (time domain positioning error). In addition, the collaborative analysis of static offset and pulse width can significantly improve the anti-interference ability of time domain positioning.

[0073] In specific implementation, the pulse width of the pulse current signal can be determined in the following manner, namely: extract each rising edge and falling edge from the pulse current signal through the threshold comparison method in the prior art, arrange each rising edge and falling edge in chronological order, use the arranged sequence as a rising-falling edge sequence, calculate the time difference between each adjacent rising edge and falling edge in the rising-falling edge sequence, and use the average of all time differences as the pulse width. In this embodiment, the threshold comparison method can be: set a current amplitude threshold (such as 50% of the peak value in the pulse current signal), when the amplitude of the pulse current signal changes from lower than the current amplitude threshold to higher than the current amplitude threshold, it is determined to be a rising edge, conversely, when the amplitude of the pulse current signal changes from higher than the current amplitude threshold to lower than the current amplitude threshold, it is determined to be a falling edge. In other embodiments, other methods can be used for determination, which are not limited here.

[0074] In specific implementation, the time interval between adjacent rising edges in the pulse current signal can be determined in the following manner, namely: each rising edge in the pulse current signal is determined by the threshold comparison method in the prior art, and the time interval between each adjacent rising edge is calculated, and all intervals are used as the time interval between adjacent rising edges in the pulse current signal, wherein the time interval represents the time interval between adjacent rising edges in the pulse current signal; in other embodiments, other methods can also be used for determination, which are not limited here.

[0075] In a specific implementation, positioning correction is performed on the time interval according to the static offset and the pulse width to obtain multiple correction values ​​for the time interval. This can be achieved in the following manner: obtaining an ideal pulse width from a battery corresponding database, determining the ideal pulse width based on a statistical analysis method in the prior art in combination with a historical pulse current signal, for example, taking the average of all pulse widths in the historical pulse current signal as the ideal pulse width, taking the difference between the pulse width and the ideal pulse width as the width correction value, selecting an interval in the time interval as a selected interval, extracting the signal segment corresponding to the selected interval in the pulse current signal, extracting the DC component value corresponding to the selected interval in the static offset, subtracting the extracted DC component value from the signal segment to obtain a de-biased signal segment, re-detecting the rising and falling edges of the de-biased signal segment, calculating the intervals between adjacent rising edges, taking the difference between the selected interval and the interval as a time correction value, taking the sum of the time correction value and the width correction value as the correction value for the selected interval, and continuing to determine the correction values ​​for the remaining intervals in the time interval. The correction value represents a parameter value representing the degree of correction of the time between rising edges in the pulse current. In other embodiments, other methods can also be used for determination, which are not limited here.

[0076] In specific implementation, the time domain positioning error of the time interval can be determined based on all correction amounts in the following manner, namely: the root mean square error of all correction amounts is calculated based on the mean and standard deviation of all correction amounts, and the time domain positioning error of the time interval is characterized by the root mean square error. If the root mean square error is larger, the positioning error is more dispersed, and the time domain positioning error is larger, and vice versa, the time domain positioning error is smaller. In other embodiments, other methods can also be used for determination, which is not limited here.

[0077] It should be noted that the time domain positioning error in this application represents the degree of error in positioning the time intervals between adjacent rising edges in the current signal of the battery during charging and discharging, which can be used to judge the current conditions of the battery during charging and discharging, and to facilitate the identification of the pulse frequency of the current during charging and discharging of the battery.

[0078] In step 104, the surface temperature of the target battery during charging and discharging is monitored, and all monitored temperatures are correlated with the pulse current signal to obtain a disturbance characteristic of the target battery's temperature on the current during charging and discharging.

[0079] In a specific implementation, monitoring the surface temperature of the target battery during charging and discharging can be achieved in the following manner, namely: placing the sensing node of the temperature sensor on the surface of the target battery, and monitoring the surface temperature of the target battery during charging and discharging through the temperature sensor, wherein the surface temperature represents the temperature of the battery surface of the target battery during charging and discharging. In other embodiments, other methods can also be used to determine the temperature, which is not limited here.

[0080] In some embodiments, correlating all monitored temperatures with the pulse current signal to obtain the current disturbance characteristics of the target battery during charge and discharge can be achieved by the following steps:

[0081] Correlating all monitored temperatures with the pulse current signal to obtain temperature-pulse correlation information;

[0082] Determining a correlation coefficient sequence between the temperature and current of the target battery during charging and discharging according to the temperature-pulse correlation information;

[0083] The disturbance characteristics of the temperature on the current of the target battery during charging and discharging are determined by the correlation coefficient sequence.

[0084] It should be noted that during the battery charging and discharging process, the chemical reactions inside the battery will generate heat, causing temperature changes. The temperature changes will affect the battery's internal resistance, electrode reaction rate, etc., and thus affect the current. By monitoring the temperature and pulse current signals and correlating the two, the intrinsic connection between temperature and current can be revealed.

[0085] In addition, in this embodiment, a synchronous clock is used to trigger the temperature and current sensors to ensure that the data acquisition time is consistent. In specific implementation, all temperatures obtained by monitoring are associated with the pulse current signal, and the temperature-pulse correlation information can be obtained in the following manner, namely: the optimal lag time of the temperature and current signals is determined by combining all temperatures obtained by monitoring with the pulse current signal through time-shift cross-correlation analysis, and the acquisition time of all temperatures obtained by monitoring and the pulse current signal is time-shift compensated by the optimal lag time, and then all temperatures obtained by monitoring after time-shift compensation are timestamp aligned with the pulse current signal, and the aligned data set is used as the temperature-pulse correlation information. For example, the corresponding amplitudes in the temperature and pulse current signal corresponding to the same timestamp are combined into a vector, for example, vector = (temperature, amplitude), and all vectors obtained by the combination are used as the temperature-pulse correlation information. In other embodiments, other methods can also be used for determination, which is not limited here.

[0086] In a specific implementation, determining a correlation coefficient sequence between the temperature and current of the target battery during charging and discharging based on the temperature-pulse correlation information can be achieved in the following manner, namely: obtaining each pulse signal segment in the pulse current signal, selecting a pulse signal segment as the selected pulse signal segment, extracting each vector corresponding to the selected pulse signal segment from the temperature-pulse correlation information, and calculating the correlation coefficient of each extracted vector using a nonlinear correlation indicator (such as mutual information) in the prior art, using this correlation coefficient as the correlation coefficient of the selected pulse signal segment, continuing to determine the correlation coefficients of the remaining pulse signal segments, arranging all the correlation coefficients in ascending order, and using the sequence obtained by arrangement as the correlation coefficient sequence between the temperature and current of the target battery during charging and discharging, wherein the correlation coefficient in the correlation coefficient sequence represents a parameter of the degree of correlation between the temperature and current of the target battery during charging and discharging; in other embodiments, other methods can also be used for determination, which are not limited here.

[0087] In a specific implementation, determining the disturbance characteristics of the temperature on the current of the target battery during charging and discharging through the correlation coefficient sequence can be achieved in the following manner, namely: setting a dynamic correlation threshold, which can be set according to the actual correlation coefficient according to the threshold setting (such as the normal distribution method), and defining each correlation coefficient in the correlation coefficient sequence that is greater than the dynamic correlation threshold as a disturbance correlation coefficient, wherein the disturbance correlation coefficient represents a parameter value of the degree of correlation of the disturbance of the temperature on the current, extracting all vectors corresponding to each disturbance correlation coefficient from the temperature-pulse correlation information, calculating the standard deviation and mean of the temperature and the standard deviation and mean of the amplitude in each vector, and taking the set of the standard deviation and mean of the temperature, the standard deviation and mean of the amplitude, the optimal lag time, and the first correlation coefficient segment as the disturbance characteristics of the temperature on the current of the target battery during charging and discharging; in other embodiments, other methods can also be used for determination, which are not limited here.

[0088] It should be noted that the disturbance characteristics in this application represent the characteristics of the degree of disturbance of the temperature of the target battery on the current during charging and discharging, and can be used to analyze the interference of the temperature of the target battery on the current during charging and discharging.

[0089] In step 105, pulse identification is performed on the pulse current signal according to all time domain positioning errors and the disturbance characteristics to obtain an effective pulse time sequence of the target battery during charging and discharging, and the effective pulse frequency of the target battery during charging and discharging is determined based on the effective pulse time sequence.

[0090] In some embodiments, pulse identification is performed on the pulse current signal based on all time-domain positioning errors and the disturbance characteristics to obtain an effective pulse timing sequence of the target battery during charging and discharging, which can be achieved by the following steps:

[0091] Determining dynamic adjustment information of the pulse current signal according to all time domain positioning errors and the disturbance characteristics;

[0092] The pulse current signal is dynamically adjusted according to the dynamic adjustment information to obtain an effective pulse timing sequence of the target battery during charging and discharging.

[0093] It should be noted that the time domain positioning error reflects the stability of the pulse time interval and can eliminate signals with timing disorders caused by noise or hardware failure. The disturbance characteristics characterize the quality reliability of the signal and can eliminate signals with amplitude / waveform distortion caused by temperature interference. Therefore, high-precision pulse screening can be achieved through dual constraints.

[0094] In a specific implementation, the dynamic adjustment information of the pulse current signal is determined based on all the time domain positioning errors and the disturbance characteristics. This can be achieved in the following manner: a dynamic adjustment information model is initialized based on a machine learning algorithm (such as linear regression, decision tree regression), the dynamic adjustment information model is trained using historical pulse current signals, the time domain positioning error and the disturbance characteristics are used as input features of the dynamic adjustment information model, the pulse amplitude correction coefficient, the width adjustment amount and the time offset compensation value are used as output features of the dynamic adjustment information model, and the dynamic adjustment information model is optimized using a cross-validation method. All the time domain positioning errors and disturbance characteristics are used to update the input features of the dynamic adjustment information model, thereby calculating the updated pulse amplitude correction coefficient, the width adjustment amount and the time offset compensation value through the dynamic adjustment information model, and using the pulse amplitude correction coefficient, the width adjustment amount and the time offset compensation value as the dynamic adjustment information of the pulse current signal, wherein the dynamic adjustment information represents information about the degree of dynamic adjustment of the pulse current signal; in other embodiments, other methods can also be used for determination, which is not limited here.

[0095] In specific implementation, the pulse current signal is dynamically adjusted by the dynamic adjustment information to obtain the effective pulse time sequence of the target battery during charging and discharging, which can be achieved in the following manner, namely: the pulse current signal is dynamically adjusted using digital signal processing technology, and the adjusted signal is used as the effective pulse time sequence of the target battery during charging and discharging. For example, when adjusting the amplitude, the original signal is multiplied by the amplitude correction coefficient output by the model using Python's numpy library; when adjusting the pulse width, the signal is interpolated or extracted according to the width adjustment amount with the help of the resampling function of Python's scipy.signal library; for time offset, the pulse position calibration is achieved by modifying the timestamp of the signal. In other embodiments, other methods can also be used for adjustment, which are not limited here.

[0096] It should be noted that the effective pulse time-stamp sequence in the present application represents an effective pulse signal of the target battery during the charging and discharging process, and can be used to determine the pulse frequency of the target battery during charging and discharging.

[0097] In some embodiments, determining the effective pulse frequency during charging and discharging of the target battery based on the effective pulse time-stamp sequence can be achieved by using the following steps:

[0098] Determining each credible rising edge in the valid pulse time stamp sequence;

[0099] The effective pulse frequency during charging and discharging of the target battery is determined based on all credible rising edges.

[0100] In a specific implementation, first, each rising edge is identified from a valid pulse time-stamp sequence by a threshold comparison method in the prior art, and each rising edge is regarded as a credible rising edge; then, the time interval between each adjacent credible rising edge is calculated, and the reciprocal of each time interval is regarded as a single pulse frequency, and the average of all single pulse frequencies is regarded as the effective pulse frequency when the target battery is charged and discharged; in other embodiments, other methods can also be used for implementation, which are not limited here.

[0101] In some embodiments, reference Figure 3 As shown, this figure is a partial diagram of the pulse current signal in some embodiments of the present application, such as Figure 3 As described above, the lines in the figure represent the numerical changes of the pulse current signal at different times, with the rising edge and the falling edge being more obvious. The trend of the lines can intuitively present information such as the size and change trend of the pulse current.

[0102] In addition, in another aspect of the present application, in some embodiments, the present application provides a battery charge and discharge pulse frequency detection system, the battery charge and discharge pulse frequency detection system includes a battery charge and discharge pulse frequency detection system, reference Figure 4 , which is a schematic structural diagram of a battery charge and discharge pulse frequency detection system according to some embodiments of the present application. The battery charge and discharge pulse frequency detection system 400 includes: an acquisition module 401, a processing module 402, and an execution module 403, which are described as follows:

[0103] Acquisition module 401, in this application, acquisition module 401 is mainly used to collect pulse current signals of the target battery during charging and discharging;

[0104] Processing module 402, in this application, is used to divide the pulse current signal into multiple pulse signal segments according to a preset time window, and determine the static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment;

[0105] It should be noted that the processing module 402 in the present application is further configured to perform time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval;

[0106] In addition, it should be noted that the processing module 402 in the present application is also used to monitor the surface temperature of the target battery during charging and discharging, and to correlate and analyze all the monitored temperatures with the pulse current signal to obtain the disturbance characteristics of the target battery's temperature on the current during charging and discharging;

[0107] Execution module 403. In this application, execution module 403 is mainly used to perform pulse identification on the pulse current signal according to all time domain positioning errors and the disturbance characteristics, obtain the effective pulse time sequence of the target battery during charging and discharging, and determine the effective pulse frequency of the target battery during charging and discharging based on the effective pulse time sequence.

[0108] In addition, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores code, and the processor is configured to obtain the code and execute the above-mentioned battery charge and discharge pulse frequency detection method.

[0109] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a method for detecting the battery charge and discharge pulse frequency according to some embodiments of the present application. The battery charge and discharge pulse frequency detection method in the above embodiment can be Figure 5 The computer device 500 shown in FIG. 5 is implemented as shown in FIG. 5 . The computer device 500 includes at least one processor 501 , a communication bus 502 , a memory 503 , and at least one communication interface 504 .

[0110] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0111] The communication bus 502 may be used to transmit information between the aforementioned components.

[0112] The memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, a random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory 503 may be independent and connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0113] The memory 503 is used to store program code for executing the solution of the present application, and is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0114] The communication interface 504 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0115] In a specific implementation, as an example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0116] The aforementioned computer device can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of this application do not limit the type of computer device.

[0117] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned battery charge and discharge pulse frequency detection method.

[0118] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0119] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A method for detecting battery charge and discharge pulse frequency, characterized in that: The steps include: Collect pulse current signals of the target battery during charging and discharging; Dividing the pulse current signal into a plurality of pulse signal segments according to a preset time window, and determining a static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment; Performing time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal by using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval; Monitoring the surface temperature of the target battery during charging and discharging, correlating all monitored temperatures with the pulse current signal, and thereby obtaining a characteristic of the temperature disturbance on the current of the target battery during charging and discharging; Performing pulse identification on the pulse current signal according to all time-domain positioning errors and the disturbance characteristics to obtain an effective pulse time-scale sequence of the target battery during charging and discharging, and determining an effective pulse frequency of the target battery during charging and discharging based on the effective pulse time-scale sequence; The method of determining the static current offset of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment specifically includes: Determine the local current characteristics of each pulse signal segment; determining a plurality of DC component values ​​of the pulse current signal according to all local current characteristics; All DC component values ​​are taken as static offsets of the target battery's current during charging and discharging.

2. The method according to claim 1, wherein Dividing the pulse current signal into a plurality of pulse signal segments according to a preset time window specifically includes: Determine the preset time window; The pulse current signal is divided according to the preset time window to obtain a plurality of pulse signal segments.

3. The method according to claim 1, wherein Performing time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal by using the static offset and the pulse width of the pulse current signal to obtain the time domain positioning error of the time interval specifically includes: determining a pulse width of the pulse current signal; determining the time interval between adjacent rising edges of the pulse current signal; Performing positioning correction on the time interval according to the static offset and the pulse width to obtain multiple correction values ​​of the time interval; The time domain positioning error of the time interval is determined based on all the corrections.

4. The method according to claim 1, wherein Correlation analysis is performed on all monitored temperatures and the pulse current signal to obtain the disturbance characteristics of the target battery's temperature on the current during charging and discharging, specifically including: Correlating all monitored temperatures with the pulse current signal to obtain temperature-pulse correlation information; Determining a correlation coefficient sequence between the temperature and current of the target battery during charging and discharging according to the temperature-pulse correlation information; The disturbance characteristics of the temperature on the current of the target battery during charging and discharging are determined by the correlation coefficient sequence.

5. The method according to claim 1, wherein The pulse current signal is pulse identified based on all time domain positioning errors and the disturbance characteristics to obtain the effective pulse time sequence of the target battery during charging and discharging, specifically including: Determining dynamic adjustment information of the pulse current signal according to all time domain positioning errors and the disturbance characteristics; The pulse current signal is dynamically adjusted according to the dynamic adjustment information to obtain an effective pulse timing sequence of the target battery during charging and discharging.

6. The method according to claim 1, wherein Determining the effective pulse frequency during charging and discharging of the target battery based on the effective pulse time-stamp sequence specifically includes: Determining each credible rising edge in the valid pulse time stamp sequence; The effective pulse frequency during charging and discharging of the target battery is determined based on all credible rising edges.

7. The method according to claim 1, wherein The pulse current signal of the target battery during charging and discharging is collected through the current sensor.

8. The method according to claim 1, wherein The surface temperature of the target battery during charging and discharging is monitored by a temperature sensor.

9. A battery charge and discharge pulse frequency detection system, which uses the method according to any one of claims 1 to 8 to detect the battery charge and discharge pulse frequency, characterized in that: The system includes: An acquisition module is used to collect pulse current signals of the target battery during charging and discharging; a processing module, configured to divide the pulse current signal into a plurality of pulse signal segments according to a preset time window, and determine a static offset of the current of the target battery during charging and discharging based on the local current characteristics of each pulse signal segment; The processing module is further configured to perform time domain positioning calibration on the time interval between adjacent rising edges in the pulse current signal by using the static offset and the pulse width of the pulse current signal to obtain a time domain positioning error of the time interval; The processing module is further configured to monitor the surface temperature of the target battery during charging and discharging, and to correlate and analyze all monitored temperatures with the pulse current signal to obtain a disturbance characteristic of the target battery's temperature on the current during charging and discharging; An execution module is used to perform pulse identification on the pulse current signal according to all time domain positioning errors and the disturbance characteristics, obtain an effective pulse time sequence of the target battery during charging and discharging, and determine the effective pulse frequency of the target battery during charging and discharging based on the effective pulse time sequence.

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