Current signal sampling circuit and method and battery system

Abstract

A current signal sampling circuit is applied to a battery system, a current acquisition module acquires a battery current signal of a target battery and sends the battery current signal to a multi-stage filtering module, and then the multi-stage filtering module sequentially filters the battery current signal to respectively filter out a high-frequency interference signal, a ripple signal and a random noise signal; through sequential filtering of the multi-stage filtering module, high-frequency interference, ripple signals and random noise in the battery current signals are removed, so that after interference components in the battery current signals are gradually eliminated, digital processing is further performed on the filtered battery current signals through the data processing module; the battery current signals are converted into a series of discrete data points, so that the average value of the battery current signals can be conveniently calculated according to a set sampling period, and a more accurate current sampling value can be obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of frequency converters, and in particular relates to a current signal sampling circuit, method and battery system. Background Art

[0002] In the prior art, when sampling the battery current, the current signal at both ends of the battery is usually collected through a current sampling circuit, and the collected current signal is processed as the current sampling value of the battery. However, in actual applications, the battery is usually connected to the DC bus together with loads, inverters and other equipment. Load disturbances will generate ripple signals in the DC bus, and these ripple signals may be superimposed with random noise and high-frequency interference signals. Existing battery current signal processing methods are difficult to effectively distinguish ripple signals, random noise and high-frequency interference signals, resulting in the collected current signal being affected by multiple factors, reducing the authenticity and reliability of the data, and thus affecting the accuracy of the battery current sampling value. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a current signal sampling circuit, method and battery system, aiming to solve the problem of inaccurate battery current sampling values ​​caused by the difficulty in effectively distinguishing and filtering out ripple signals, random noise and high-frequency interference signals in traditional technical solutions.

[0004] A first aspect of an embodiment of the present invention provides a current signal sampling circuit, which is applied to a battery system. The current signal sampling circuit includes: A current sampling module is used to collect the battery current signal of the target battery and send the battery current signal to the multi-stage filtering module; A multi-stage filtering module is used to filter the battery current signal in sequence, filtering out high-frequency interference signals, ripple signals and random noise signals respectively; The data processing module is connected to the multi-stage filtering module and is used to digitally process the filtered battery current signal and calculate the average value of the battery current signal according to the set sampling period to obtain the current sampling value of the target battery.

[0005] In one embodiment, the multi-stage filtering module includes a low-pass filter, a band-pass filter and a Kalman filter; The input end of the low-pass filter is connected to the current sampling module to filter out high-frequency interference signals in the battery current signal; The input end of the bandpass filter is connected to the output end of the lowpass filter, and is used to select the effective frequency range of the battery current signal, suppress the interference component in the ripple signal, and increase the ripple signal; The input end of the Kalman filter is connected to the output end of the bandpass filter, and is used to filter out the random noise signal in the battery current signal based on the dynamic noise model.

[0006] In one embodiment, the low-pass filter includes a resistor-capacitor network, which is used to dynamically control the cutoff frequency by adjusting the resistance value and / or the capacitance value, and utilize the cutoff frequency to filter out high-frequency interference signals in the battery current signal. The cutoff frequency is the highest frequency allowed to pass by the low-pass filter.

[0007] In one embodiment, the bandpass filter includes an adjustable resonant circuit, which includes an adjustable inductance element, an adjustable capacitance element and a variable resistor; the adjustable inductance element works together with the adjustable capacitance element to adjust the resonant frequency of the bandpass filter; the adjustable capacitance element is used to adjust the frequency response characteristics of the bandpass filter by adjusting the capacitance value in conjunction with the adjustable inductance element to ensure that the bandpass filter can transmit effective ripple signals within a required frequency range; the variable resistor is used to adjust the quality factor and bandwidth of the bandpass filter to optimize the effect of the bandpass filter in suppressing ripple signals.

[0008] In one embodiment, the Kalman filter is used to predict the battery current signal at the next moment based on a dynamic noise model, and after receiving the battery current signal actually measured at the next moment, the predicted value is corrected based on the Kalman gain according to the deviation between the predicted value and the measured value, and the Kalman gain is dynamically adjusted according to the real-time changes of the measurement noise covariance and the prediction noise covariance to filter out the random noise in the battery current signal.

[0009] In one embodiment, the processing module is used to adjust the set sampling period according to the periodic characteristics of the ripple signal, and calculate the average value of the battery current signal after multi-stage filtering according to the adjusted sampling period to obtain the current sampling value of the target battery.

[0010] In one embodiment, the processing module is used to adjust the set sampling period to be an integer multiple of the ripple signal period.

[0011] A second aspect of an embodiment of the present application provides a current signal sampling method, including: being applied to a battery system, the battery system including a current signal sampling circuit, the current signal sampling circuit including: a current sampling module, a multi-stage filtering module; the current sampling module is used to collect a battery current signal of a target battery, and send the battery current signal to the multi-stage filtering module; the multi-stage filtering module is used to filter the battery current signal in sequence, and filter out high-frequency interference signals, ripple signals, and random noise signals respectively; the current signal sampling method includes: The filtered battery current signal is digitized; the average value of the battery current signal is calculated according to the set sampling period to obtain the current sampling value of the target battery.

[0012] In one embodiment, calculating the average value of the battery current signal according to a set sampling period includes: According to the periodic characteristics of the ripple signal, the set sampling period is adjusted; The average value of the battery current signal after multi-stage filtering is calculated according to the adjusted sampling period.

[0013] A third aspect of an embodiment of the present application provides a battery system, which includes any current signal sampling circuit as described above.

[0014] The beneficial effects of the embodiments of the present application are as follows: the battery current signal of the target battery is collected by the current acquisition module, and the battery current signal is sent to the multi-stage filtering module, and then the multi-stage filtering module sequentially filters the battery current signal to filter out high-frequency interference signals, ripple signals and random noise signals respectively. The high-frequency interference, ripple signals and random noise in the battery current signal are removed by sequential filtering of the multi-stage filtering module, so that the interference components in the battery current signal are gradually eliminated, and then the filtered battery current signal is further digitized by the data processing module to convert the battery current signal into a series of discrete data points, so as to facilitate the calculation of the average value of the battery current signal according to the set sampling period to obtain a more accurate current sampling value. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be 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 labor.

[0016] Figure 1 A circuit diagram of a current signal sampling circuit is provided for one embodiment of the present invention; Figure 2 A circuit diagram of a multi-stage filtering module provided by an embodiment of the present invention; Figure 3 A circuit diagram of a low-pass filter provided by an embodiment of the present invention; Figure 4 A circuit diagram of a bandpass filter provided by an embodiment of the present invention; Figure 5 A schematic diagram of the implementation flow of a current signal sampling method provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0017] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0019] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0020] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0021] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0022] In the description of the embodiments of the present application, the term "multi-frame" refers to more than two (including two).

[0023] In the description of the embodiments of the present application, the technical terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the embodiments of the present application.

[0024] The present application embodiment provides a current signal sampling circuit, which is applied to a battery system. Figure 1 As shown, Figure 1 A circuit diagram of a current signal sampling circuit provided by an embodiment of the present application. Figure 1 It can be known that the current signal sampling circuit provided in the embodiment of the present application includes: a current sampling module 100, a multi-stage filtering module 200 and a processing module 300. Among them, the current sampling module 100 is used to collect the battery current signal of the target battery and send the battery current signal to the multi-stage filtering module 200; the multi-stage filtering module 200 is used to filter the battery current signal in sequence, and filter out high-frequency interference signals, ripple signals and random noise signals respectively; the data processing module 300 is connected to the multi-stage filtering module 200, and is used to digitally process the filtered battery current signal, and calculate the average value of the battery current signal according to the set sampling period to obtain the current sampling value of the target battery.

[0025] Through the multi-stage filtering module, various interference components in the battery current signal, such as high-frequency noise, ripple signal and random noise, are filtered out one by one, which significantly improves the quality and stability of the signal. After the battery current signal is processed by the filtering module, the remaining valid signal will be digitized, which helps to improve the accuracy and reliability of the processing. The digitized signal is no longer affected by the instability of the analog signal. The average value of the battery current signal is calculated by the processing module to obtain the current sampling value of the target battery. This calculation process can reflect the actual working state of the battery, eliminate short-term fluctuations caused by instantaneous current changes or noise, make the sampling results more stable, and accurately reflect the actual use of the battery.

[0026] Among them, high-frequency interference signals and random noise are introduced by changes in battery current, external environment or the circuit itself. These interferences will affect the accuracy of the current signal, and these effects can be effectively eliminated through multi-stage filtering. Ripple signals are usually periodic fluctuations during the battery charging and discharging process. The use of multi-stage filtering can suppress its interference components while retaining the effective components of the ripple signal.

[0027] Specifically, see Figures 2 to 4 shown. Figure 2 A circuit diagram of a multi-stage filtering module provided in an embodiment of the present application. Figure 2 It can be seen that the multi-stage filtering module 200 includes a low-pass filter 210, a band-pass filter 220 and a Kalman filter 230; The input end of the low-pass filter 210 is connected to the output end of the current sampling module 100 to filter out high-frequency interference signals in the battery current signal. Specifically, the low-pass filter 210 only allows signals below a certain cutoff frequency to pass through, and signals above the cutoff frequency are attenuated or filtered out.

[0028] For example, Figure 3 A circuit diagram of a low-pass filter provided in an embodiment of the present application. Figure 3 It can be seen that the low-pass filter 210 includes a resistor-capacitor network 211, which is used to dynamically control the cutoff frequency by adjusting the resistance value and / or the capacitance value, and use the cutoff frequency to filter out high-frequency interference signals in the battery current signal. The cutoff frequency is the highest frequency allowed to pass by the low-pass filter.

[0029] Depend on Figure 3 It can be known that in the present application, the RC network 211 includes a first resistor 2111 and a first capacitor 2112. One end of the first resistor 2111 is connected to the output end of the current sampling module 100, and the other end is connected to one end of the first capacitor 2112 as the output end, and the other end of the first capacitor 2112 is grounded. The first resistor 2111 determines the frequency response characteristics of the RC network 211. The effect of the first resistor 2111 is to produce certain restrictions on the amplitude of the passing signal, thereby affecting the attenuation and filtering effect of the battery current signal. In the RC network, the value of the resistor and the value of the capacitor jointly determine the cut-off frequency of the low-pass filter. In the present application, by adjusting the resistance value of the first resistor 2111, the response of the RC network 211 can be dynamically adjusted to control the frequency components that can pass. The first capacitor 2112 is connected after the first resistor 2111 and is connected to the ground, which can produce a phase delay to the passing signal and filter the signal when the frequency is high. The value of the first capacitor 2112 and the value of the first resistor 2111 jointly determine the cutoff frequency, which is the highest frequency that the low-pass filter can pass. The first capacitor 2112 suppresses high-frequency signals by storing charges and allows low-frequency signals to pass.

[0030] The larger the value of the first capacitor 2112 is, the lower the cut-off frequency is, which means that a wider range of high-frequency components can be filtered out.

[0031] The design of the resistor-capacitor network can effectively control the high-frequency noise in the battery current signal and ensure the quality of the output signal. By adjusting the values ​​of the resistor and capacitor, the cutoff frequency of the low-pass filter can be flexibly set, thereby filtering out interference signals within a specific frequency range according to actual needs and improving the accuracy and reliability of the battery monitoring system.

[0032] The input end of the bandpass filter 220 is connected to the output end of the low-pass filter 210, and is used to select the effective frequency range of the battery current signal to suppress the interference components in the ripple signal. Specifically, the bandpass filter 220 can select the effective frequency range in the received battery current signal and suppress the DC ripple signal by adjusting the resonant frequency, frequency response characteristics and quality factor.

[0033] For example, Figure 4 A circuit diagram of a bandpass filter provided in an embodiment of the present application. Figure 4 It can be seen that the bandpass filter 220 includes an adjustable resonant circuit, which includes an adjustable inductance element 221, an adjustable capacitance element 222 and a variable resistor 223; the adjustable inductance element 221 and the adjustable capacitance element 222 work together to adjust the resonant frequency of the bandpass filter 220; the adjustable capacitance element 222, by adjusting the capacitance value in conjunction with the adjustable inductance element 221, is used to adjust the frequency response characteristics of the bandpass filter 220 to ensure that the bandpass filter 220 can transmit effective signals within the required frequency range; the variable resistor is used to adjust the quality factor and bandwidth of the bandpass filter to optimize the effect of the bandpass filter in suppressing interference components in the ripple signal.

[0034] Specifically, by Figure 4It can be known that the input end of the adjustable resonant circuit is connected to the output end of the low-pass filter 210 to receive the filtered battery current signal. After the high-frequency components of the battery current signal are filtered out by the low-pass filter, it enters the band-pass filter. The band-pass filter further suppresses the interference components in the ripple signal by selecting an effective frequency range. One end of the adjustable inductance element 221 is connected to one end of the variable resistor 223 as the input end of the adjustable resonant circuit, and the other end of the adjustable inductance element 221 is connected to one end of the adjustable capacitance element 222 and the other end of the variable resistor 223 and then grounded. The other end of the adjustable capacitance element 222 is grounded as the output end of the adjustable resonant circuit. By adjusting the value of the adjustable inductance element 221, the resonant frequency of the adjustable resonant circuit can be changed, so that the adjustable resonant circuit can transmit signals within a specific frequency range and prevent the passage of other frequency components. By adjusting the capacitance value of the adjustable capacitance element 222, the frequency response characteristics of the adjustable resonant circuit are adjusted in conjunction with the adjustable inductance element. The change in capacitance value will affect the resonant frequency of the adjustable resonant circuit, thereby determining the signal range transmitted by the adjustable resonant circuit. The capacitor and the inductor element work together to ensure that the adjustable resonant circuit only allows signals in a specific frequency range to pass through, which can effectively suppress unwanted high-frequency or low-frequency noise in the battery current signal (high-frequency or low-frequency noise includes ripple signals). The variable resistor 223 is used to adjust the quality factor (Q factor) and bandwidth of the adjustable resonant circuit. By adjusting the resistance value, the suppression effect of the ripple signal can be optimized. The adjustment of the resistance value can change the bandwidth of the adjustable resonant circuit, thereby affecting the selectivity of the adjustable resonant circuit, so that it can more accurately filter out unwanted frequency signals.

[0035] The input end of the Kalman filter 230 is connected to the output end of the bandpass filter 220 and is used to filter out the random noise signal in the battery current signal based on the dynamic noise model.

[0036] Exemplarily, the Kalman filter is used to predict the battery current signal at the next moment based on the dynamic noise model, and after receiving the battery current signal actually measured at the next moment, the predicted value is corrected based on the Kalman gain according to the deviation between the predicted value and the measured value, and the Kalman gain is dynamically adjusted according to the real-time changes of the measurement noise covariance and the prediction noise covariance to filter out the random noise in the battery current signal. Specifically, the prediction of the battery current signal at the next moment based on the dynamic noise model can be expressed as: ,in, is the predicted value of the battery current signal at time k, A is the state transfer matrix, which represents the dynamic changes of the battery system. is the estimated value of the battery current signal at the previous moment of time K, B is the control input matrix, It is the control input and represents the external factors affecting the battery current signal, such as load changes.

[0037] In this application, the Kalman gain is not fixed, it will be dynamically adjusted according to the real-time changes of the measurement noise covariance and the prediction noise covariance. Specifically, once the actual measured battery current signal arrives, the Kalman filter will correct the predicted value based on the Kalman gain according to the deviation between the predicted value and the measured value. The specific correction process includes calculating the Kalman gain and updating the predicted value and the predicted noise covariance.

[0038] Exemplarily, the calculation formula of Kalman gain is expressed as: in, is the Kalman gain at time k, which represents the weighted ratio between the predicted value and the measured value; H is the observation matrix, and R is the prediction noise covariance.

[0039] In this application, the degree of dependence on the predicted value and the measured value can be dynamically adjusted according to the size of the Kalman gain. The larger the Kalman gain, the more dependent on the actual measured value; conversely, if the signal is more stable, the Kalman gain is smaller, and it is more dependent on the predicted value.

[0040] The prediction value update formula is expressed as: ),in, is the updated prediction value at time k, is the actual measured battery current signal.

[0041] The prediction noise covariance update formula is expressed as: ,in, is the updated prediction noise covariance and I is the identity matrix.

[0042] Kalman Gain It is based on the measurement noise covariance R and the prediction noise covariance When the measurement noise is large or the prediction error is large, the Kalman gain will increase, which means that it relies more on the measured value. On the contrary, when the system state is stable or the measurement error is small, the Kalman gain will decrease and rely more on the predicted value.

[0043] By using the Kalman filter, the filtering process can be dynamically adjusted to accurately remove random noise caused by the environment, sensor instability or other external factors from the battery current signal, ensuring the accuracy of the battery current signal, thereby providing more reliable battery status monitoring.

[0044] In one embodiment, the processing module 300 is used to adjust the set sampling period according to the periodic characteristics of the ripple signal, calculate the average value of the battery current signal after multi-stage filtering according to the adjusted sampling period, and obtain the current sampling value of the target battery.

[0045] Specifically, the processing module 300 is used to adjust the set sampling period to be an integer multiple of the ripple signal period.

[0046] It should be noted that since the main task of the bandpass filter is to remove unnecessary frequency components in the signal and retain the signal part within a specific frequency band. For ripple signals, the bandpass filter can remove ripple signal interference components that are not within the specific frequency band, such as low frequency and high frequency, but the ripple signal components related to the frequency of the battery current signal in the specific frequency band will be retained. This is because the role of the bandpass filter is frequency screening. It can suppress unnecessary frequencies, but it does not reduce the components related to the frequency of the battery current signal in the specific frequency band. Therefore, some ripple signals related to the battery current signal cannot be eliminated, and the sampling distortion and error problems caused by the mismatch between the ripple signal period and the sampling period cannot be reduced. Therefore, in the present application, the sampling period is adjusted to an integer multiple of the ripple signal period by the processing module to achieve multiple sampling in each ripple period, avoid errors or distortions caused by the mismatch between the sampling period and the ripple signal period, accurately capture the complete period of the ripple signal and its waveform characteristics, and further ensure the accurate acquisition of the signal, thereby improving the quality of the battery current signal.

[0047] The beneficial effects of the embodiments of the present application are as follows: the battery current signal of the target battery is collected by the current acquisition module, and the battery current signal is sent to the multi-stage filtering module, and then the multi-stage filtering module sequentially filters the battery current signal to filter out high-frequency interference signals, ripple signals and random noise signals respectively. The high-frequency interference and random noise in the battery current signal are removed by the sequential filtering of the multi-stage filtering module, and the ripple signal is suppressed as much as possible, so that the interference components in the battery current signal are gradually eliminated, and then the filtered battery current signal is further digitized by the data processing module to convert the battery current signal into a series of discrete data points, so as to facilitate the calculation of the average value of the battery current signal according to the set sampling period, so as to obtain a more accurate current sampling value.

[0048] See also Figure 5 As shown, Figure 5 The current signal sampling method provided in the embodiment of the present application is applied to a battery system, and the battery system includes: Figures 1 to 4 The current signal sampling circuit shown in any embodiment. Specifically, the current signal sampling circuit is not described in detail in this embodiment. Figure 5 It can be seen that the current signal sampling method provided by the present application includes: S501: Digitally process the filtered battery current signal.

[0049] The filtered battery current signal is a continuous analog electrical signal, which is converted into a discrete-time digital signal by digitizing it for subsequent signal processing.

[0050] S502: Calculate the average value of the battery current signal according to the set sampling period to obtain the current sampling value of the target battery.

[0051] In one embodiment, calculating the average value of the battery current signal according to a set sampling period includes: adjusting the set sampling period according to the periodic characteristics of the ripple signal; and calculating the average value of the battery current signal after multi-stage filtering according to the adjusted sampling period.

[0052] It should be noted that, for the ripple signal, after filtering, the components related to the frequency of the battery current signal can be retained, while the interference of the ripple signal in other frequency ranges can be removed. Therefore, the battery current signal after filtering may also include a ripple signal. In other words, the battery current signal after filtering may include a ripple signal related to the frequency of the battery current signal, and therefore, the sampling distortion and error problems caused by the mismatch between the ripple signal period and the sampling period will not be reduced. Therefore, in the present application, the sampling period is adjusted to an integer multiple of the ripple signal period through the processing module, so as to achieve multiple sampling in each ripple period, avoid errors or distortions caused by the mismatch between the sampling period and the ripple signal period, accurately capture the complete period of the ripple signal and its waveform characteristics, and further ensure the accurate acquisition of the signal, thereby improving the quality of the battery current signal.

[0053] From the above analysis, it can be seen that the current signal sampling method provided in the embodiment of the present application adjusts the sampling period to an integer multiple of the ripple signal period through the processing module, so as to realize multiple sampling in each ripple period, avoid errors or distortions caused by the mismatch between the sampling period and the ripple signal period, accurately capture the complete period of the ripple signal and its waveform characteristics, and further ensure the accurate acquisition of the signal, thereby improving the quality of the battery current signal.

[0054] In addition, the present application also provides a battery system, the battery system comprising: Figures 1 to 4 The current signal sampling circuit shown in any embodiment.

[0055] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0056] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0057] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A current signal sampling circuit, applied to a battery system, characterized in that: The current signal sampling circuit comprises: A current sampling module, used for collecting a battery current signal of a target battery and sending the battery current signal to a multi-stage filtering module; A multi-stage filtering module, used to filter the battery current signal in sequence, and filter out high-frequency interference signals, ripple signals and random noise signals respectively; The data processing module is connected to the multi-stage filtering module and is used to digitally process the filtered battery current signal and calculate the average value of the battery current signal according to a set sampling period to obtain the current sampling value of the target battery.

2. The current signal sampling circuit according to claim 1, characterized in that: The multi-stage filtering module includes a low-pass filter, a band-pass filter and a Kalman filter; The input end of the low-pass filter is connected to the current sampling module, and is used to filter out high-frequency interference signals in the battery current signal; The input end of the bandpass filter is connected to the output end of the low-pass filter, and is used to select an effective frequency range of the battery current signal to suppress the ripple signal; The input end of the Kalman filter is connected to the output end of the bandpass filter, and is used to filter out the random noise signal in the battery current signal based on a dynamic noise model.

3. The current signal sampling circuit according to claim 2, characterized in that: The low-pass filter includes a resistor-capacitor network, which is used to dynamically control a cutoff frequency by adjusting a resistance value and / or a capacitor value, and utilize the cutoff frequency to filter out high-frequency interference signals in the battery current signal. The cutoff frequency is the highest frequency allowed to pass by the low-pass filter.

4. The current signal sampling circuit according to claim 2, characterized in that: The bandpass filter includes an adjustable resonant circuit, which includes an adjustable inductance element, an adjustable capacitance element and a variable resistor; the adjustable inductance element works in conjunction with the adjustable capacitance element to adjust the resonant frequency of the bandpass filter; the adjustable capacitance element, by adjusting the capacitance value in conjunction with the adjustable inductance element, is used to adjust the frequency response characteristics of the bandpass filter to ensure that the bandpass filter can transmit effective signals within a required frequency range; the variable resistor is used to adjust the quality factor and bandwidth of the bandpass filter to optimize the effect of the bandpass filter in suppressing ripple signals.

5. The current signal sampling circuit according to claim 2, characterized in that: The Kalman filter is used to predict the battery current signal at the next moment based on the dynamic noise model, and after receiving the battery current signal actually measured at the next moment, correct the predicted value based on the Kalman gain according to the deviation between the predicted value and the measured value, and dynamically adjust the Kalman gain according to the real-time changes of the measurement noise covariance and the prediction noise covariance to filter out the random noise in the battery current signal.

6. The current signal sampling circuit according to claim 1, characterized in that: The processing module is used to adjust the set sampling period according to the periodic characteristics of the ripple signal, calculate the average value of the battery current signal after multi-stage filtering according to the adjusted sampling period, and obtain the current sampling value of the target battery.

7. The current signal sampling circuit according to claim 6, characterized in that: The processing module is used to adjust the set sampling period to be an integer multiple of the ripple signal period.

8. A current signal sampling method, characterized in that: Applied to a battery system, the battery system includes a current signal sampling circuit, the current signal sampling circuit includes: a current sampling module, a multi-stage filtering module; the current sampling module is used to collect the battery current signal of the target battery, and send the battery current signal to the multi-stage filtering module; the multi-stage filtering module is used to filter the battery current signal in sequence, and filter out high-frequency interference signals, ripple signals and random noise signals respectively; the method includes: The filtered battery current signal is digitally processed; the average value of the battery current signal is calculated according to a set sampling period to obtain the current sampling value of the target battery.

9. The current signal sampling method according to claim 8, characterized in that: The step of calculating the average value of the battery current signal according to the set sampling period includes: According to the periodic characteristics of the ripple signal, the set sampling period is adjusted; The average value of the battery current signal after multi-stage filtering is calculated according to the adjusted sampling period.

10. A battery system, characterized in that: The battery system comprises the circuit signal sampling circuit according to any one of claims 1 to 7.

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