Battery pack charging and discharging state detection method

Abstract

The invention relates to the technical field of battery detection, and discloses a battery pack charge-discharge state detection method, which does not need to additionally install a current sensor to detect the current of a battery pack, only needs to detect the voltage signal of the battery pack, and can analyze the charge-discharge state of the battery pack through an algorithm, thereby reducing the additional hardware, simplifying the circuit design, and reducing the cost. And the cost and the complexity are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and in particular to a method for detecting the charge and discharge status of a battery pack. Background Art

[0002] During the long-term operation of energy storage systems, the issue of battery pack voltage discreteness is a key factor that cannot be ignored. Specifically, due to differences in the manufacturing process, operating environment, and inherent characteristics of the individual cells within the battery pack, the voltage performance of each cell in the battery pack will be inconsistent during the charge and discharge process, which is the phenomenon of voltage discreteness. This voltage discreteness can have a significant negative impact on the performance of the energy storage system. On the one hand, it will cause the system's energy utilization rate to drop significantly, making it impossible to fully utilize the energy that could be stored and released, resulting in energy waste. On the other hand, it will accelerate the degradation of the overall life of the battery pack, shortening the battery pack's service life and increasing the system's maintenance and replacement costs.

[0003] To effectively address the issue of battery pack voltage discreteness, the industry has developed and implemented an automatic recharging system. The core operating principle of this system relies on precise detection of the battery pack current to accurately determine the charge and discharge status of the battery pack. By real-time monitoring of current magnitude, direction, and other parameters, the system can clearly determine whether the battery pack is currently charging, discharging, or in an idle state. On this basis, the automatic recharging system ensures that when the battery pack is not charging or discharging, the lower-voltage cells are recharged in a timely manner, thereby balancing the voltage of each cell within the battery pack, maintaining stable performance and extending its service life.

[0004] However, in actual engineering applications, current detection presents a pressing problem. Currently, current detection primarily relies on current sensors. As high-precision measurement equipment, current sensors require significant investment in procurement, installation, and maintenance. In actual engineering cases, to meet the accuracy and stability requirements of current detection in energy storage systems, the current sensors used are often expensive, with the hardware cost alone potentially adding thousands of yuan. This undoubtedly increases the overall construction cost of energy storage systems, placing financial pressure on their promotion and application.

[0005] Therefore, there is a need to improve the existing technology.

[0006] The above information is presented as background information only to assist with an understanding of the present disclosure and is not a determination or admission that any of the above may be applicable as prior art with respect to the present disclosure. Summary of the Invention

[0007] The present invention provides a method for detecting the charge and discharge status of a battery pack to solve the problems existing in the prior art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A method for detecting the charge and discharge status of a battery pack, comprising:

[0010] S1, collect battery pack voltage signals and cache them;

[0011] S2. Performing wavelet transform analysis on the collected signal to determine the charge and discharge status of the battery pack.

[0012] Furthermore, in the battery pack charge and discharge status detection method, in S1, the sampling frequency is 1-100 kHz.

[0013] Furthermore, in the battery pack charge and discharge status detection method, in S1, the sampling frequency is 10 Hz.

[0014] Furthermore, in the battery pack charge and discharge status detection method, in S1, the cache mechanism adopts a dual-cache ring queue, that is, it is divided into two cache areas, namely cache area A and cache area B. When cache area A is full, processing is started, and cache area B is continuously filled while processing cache area A to achieve parallel operation.

[0015] Furthermore, in the battery pack charge and discharge status detection method, S2 includes:

[0016] S21, selecting the wavelet basis function as Haar wavelet;

[0017] S22 . Performing wavelet transform analysis on the collected signal using the Haar wavelet to determine the charge and discharge status of the battery pack.

[0018] Furthermore, in the battery pack charge and discharge status detection method, the step S22 includes:

[0019] S221, performing multi-level wavelet decomposition on the collected signal to extract the approximate coefficients and detail coefficients of each layer;

[0020] S222, based on the approximate coefficients and detail coefficients obtained by multi-level wavelet decomposition, suppress noise through layered threshold processing, and use multi-scale entropy theory to calculate entropy values and approximate slopes to extract characteristic information of the signal;

[0021] S223 : Compare the entropy value and the approximate slope obtained in the feature extraction stage with the set threshold value, and judge the charge and discharge state of the battery pack according to different conditions.

[0022] Furthermore, in the battery pack charge and discharge status detection method, S221 includes:

[0023] S2211, input original sampling data array;

[0024] S2212. Check whether the length is greater than or equal to an integer power of 2 and is an even number; otherwise, report an error.

[0025] S2213, initialization process calculation array, the length of which is equal to the original data array;

[0026] S2214. For each layer:

[0027] a. Check whether the length is greater than or equal to an integer power of 2 and is an even number, otherwise an error is reported;

[0028] b. Decompose to obtain the approximate coefficient and detail coefficient of the current layer;

[0029] c. Save the approximate coefficients and detail coefficients of the current layer;

[0030] d. Store the updated coefficients in the process calculation array and update the length to half of the original length;

[0031] S2215. After three-layer decomposition, the approximate coefficient and detail coefficient are obtained.

[0032] Furthermore, in the battery pack charge and discharge status detection method, the step S222 includes:

[0033] S2221, performing strong noise suppression on the primary detail coefficients while retaining the effective signal components in the high-level coefficients;

[0034] S222. Using the multi-scale entropy theory, the entropy value H is calculated based on the energy distribution of the detail coefficients of each layer, and the approximate slope slope_avg is calculated using the approximate coefficient:

[0035] Entropy , , where D j represents the detail coefficient of the jth layer, P j is the energy proportion of the corresponding layer;

[0036] Approximate slope , A3 is the approximate coefficient of the third layer.

[0037] Furthermore, in the battery pack charge and discharge status detection method, S223 includes:

[0038] S2231, the entropy value H and the entropy value threshold H th Compare the approximate slope slope_avg with the slope threshold S th Make comparisons;

[0039] S2232: Convert the following comparison results into the charge and discharge status of the battery pack:

[0040] When the approximate slope slope_avg> slope threshold-S th , and the approximate slope slope_avg < slope threshold S th , the battery pack is in a static state;

[0041] When the entropy value H ≥ the entropy threshold H th And the approximate slope slope_avg> slope threshold S th , the battery pack is in a charging state;

[0042] When the entropy value H ≥ the entropy threshold H th And the approximate slope slope_avg ≤ slope threshold - S th , the battery pack is in a discharged state.

[0043] Furthermore, in the battery pack charge and discharge status detection method, after S2, the method further includes:

[0044] S3. Outputting the determined charge and discharge status of the battery pack.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention provides a method for detecting the charge and discharge status of a battery pack. Since there is no need to install an additional current sensor to detect the current of the battery pack, only the voltage signal of the battery pack needs to be detected. Then, the charge and discharge status of the battery pack can be analyzed through an algorithm. This method reduces additional hardware, simplifies circuit design, and reduces cost and complexity.

[0047] The present invention has other features and advantages that will be apparent from or will be described in detail in the accompanying drawings and the following detailed description incorporated herein, which together serve to explain certain principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0049] Figure 1This is a flow chart of a method for detecting the charge and discharge status of a battery pack provided by an embodiment of the present invention;

[0050] Figure 2 yes Figure 1 Schematic diagram of the detailed process of S2;

[0051] Figure 3 yes Figure 2 Detailed process diagram of S22. DETAILED DESCRIPTION

[0052] In order to explain in detail the possible application scenarios, technical principles, specific solutions that can be implemented, and the purpose and effects of this application, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of this application and are therefore only examples and are not intended to limit the scope of protection of this application.

[0053] References to "embodiments" herein mean that the specific features, structures, or characteristics described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the word "embodiment" in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or relevance to other embodiments. In principle, in this application, as long as there are no technical contradictions or conflicts, the various technical features mentioned in the embodiments can be combined in any manner to form a corresponding implementable technical solution.

[0054] Unless otherwise defined, the technical terms used herein have the same meanings as those generally understood by those skilled in the art to which this application belongs; the use of relevant terms herein is only for describing specific embodiments and is not intended to limit this application.

[0055] In the description of this application, the term "and / or" is used to describe a logical relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A exists, B exists, and both A and B exist. In addition, the character " / " in this document generally indicates that the objects before and after are in a logical "or" relationship.

[0056] In this application, terms such as "first" and "second" are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual quantity, priority or sequence relationship between these entities or operations.

[0057] Without further limitations, in this application, the words "include", "comprise", "have" or other similar expressions used in the sentences are intended to cover non-exclusive inclusion. These expressions do not exclude the presence of additional elements in the process, method or product including the elements, so that the process, method or product including a series of elements may include not only those defined elements, but also other elements not explicitly listed, or elements inherent to such process, method or product.

[0058] In this application, expressions such as "greater than," "less than," and "exceed" are understood to exclude the number itself; expressions such as "above," "below," and "within" are understood to include the number itself. In addition, in the description of the embodiments of this application, "multiple" means two or more (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups" and "multiple times," unless otherwise specifically limited.

[0059] In the description of the embodiments of the present application, the space-related expressions used, such as "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicate the orientation or position relationship based on the orientation or position relationship shown in the specific embodiments or drawings, and are only for the convenience of describing the specific embodiments of the present application or facilitating the reader's understanding, and do not indicate or imply that the device or component referred to must have a specific position, a specific orientation, or be constructed or operated in a specific orientation. Therefore, it should not be understood as a limitation on the embodiments of the present application.

[0060] Unless otherwise expressly specified or limited, in the description of the embodiments of the present application, the terms "installed", "connected", "connected", "fixed", "set", etc. used should be understood in a broad sense. For example, the "connection" can be a fixed connection, a detachable connection, or an integrated setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection or an indirect connection through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For those skilled in the art of the present application, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0061] In view of the aforementioned deficiencies in the prior art, the applicant, drawing upon years of extensive practical experience and expertise in design and manufacturing in this field, combined with the application of scientific knowledge, has actively engaged in research and innovation, hoping to create a technology that can address these deficiencies. Through continuous research and design, and through repeated trial production and refinement, the present invention has been developed, which possesses truly practical value.

[0062] Please refer to Figure 1 , an embodiment of the present invention provides a method for detecting the charge and discharge status of a battery pack, comprising:

[0063] S1. Collect the battery pack voltage signal and cache it.

[0064] It should be noted that, in S1, the sampling frequency is 1-100 kHz, preferably 10 Hz.

[0065] The cache mechanism adopts a double-buffered ring queue, that is, it is divided into two cache areas, cache area A and cache area B. When cache area A is full, processing is started, and cache area B is continuously filled while processing cache area A to achieve parallel operation.

[0066] S2. Performing wavelet transform analysis on the collected signal to determine the charge and discharge status of the battery pack.

[0067] Please refer to Figure 2 In one implementation of this embodiment, S2 may be further refined to include the following steps:

[0068] S21. Select the Haar wavelet as the wavelet basis function.

[0069] It should be noted that in practical applications of wavelet transforms, the selection of wavelet basis functions requires a comprehensive consideration of signal characteristics and system resource constraints. Based on the implementation requirements of embedded systems, this embodiment prioritizes the Haar wavelet and selects a three-layer decomposition. This wavelet basis function, with its compact support and computational efficiency advantages (requiring only addition, subtraction, and shift operations), significantly reduces microprocessor resource usage while ensuring analysis accuracy.

[0070] S22 . Performing wavelet transform analysis on the collected signal using the Haar wavelet to determine the charge and discharge status of the battery pack.

[0071] Please refer to Figure 3 In one implementation of this embodiment, the step S22 may be further refined to include the following steps:

[0072] S221. Perform multi-level wavelet decomposition on the collected signal to extract the approximate coefficients and detail coefficients of each layer.

[0073] It's important to note that, from a time-frequency analysis perspective, the decomposition levels and frequency components exhibit an inverse order: the detail coefficient D1 of the primary decomposition (the first level) corresponds to the signal's highest frequency band (typically including measurement noise), while the corresponding frequency bandwidth decreases as the decomposition level increases (e.g., D2, D3, etc.). Notably, the frequency resolution of the approximation coefficient C increases exponentially with increasing decomposition levels. This property enables high-level approximation coefficients to effectively extract the signal's essential features.

[0074] S222. Based on the approximate coefficients and detail coefficients obtained by multi-level wavelet decomposition, noise is suppressed through layered threshold processing, and the entropy value and approximate slope are calculated using multi-scale entropy theory to extract the characteristic information of the signal.

[0075] It should be noted that during the signal decomposition process, multi-level wavelet transforms generate a hierarchical coefficient matrix. Specifically, each decomposition level produces two characteristic components: Approximation Coefficients (C), which characterize the low-frequency baseline components of the signal and reflect the macro-trend characteristics of the signal; and Detail Coefficients (D), which record the high-frequency fluctuation components of the signal, including transient characteristics and noise information.

[0076] This embodiment employs a hierarchical thresholding mechanism to implement differentiated processing strategies for coefficient matrices at different levels: strong noise suppression is applied to primary detail coefficients while preserving the effective signal components in higher-level coefficients. This physically-based hierarchical processing approach ensures effective denoising while successfully avoiding the signal distortion associated with traditional filtering methods.

[0077] S223 : Compare the entropy value and the approximate slope obtained in the feature extraction stage with the set threshold value, and judge the charge and discharge status of the battery pack according to different conditions.

[0078] In one implementation of this embodiment, the step S221 may be further refined to include the following steps:

[0079] S2211, input original sampling data array;

[0080] S2212. Check whether the length is greater than or equal to an integer power of 2 and is an even number; otherwise, report an error.

[0081] S2213, initialization process calculation array, the length of which is equal to the original data array;

[0082] S2214. For each layer:

[0083] a. Check whether the length is greater than or equal to an integer power of 2 and is an even number, otherwise an error is reported;

[0084] b. Decompose to obtain the approximate coefficient and detail coefficient of the current layer;

[0085] c. Save the approximate coefficients and detail coefficients of the current layer;

[0086] d. Store the updated coefficients in the process calculation array and update the length to half of the original length;

[0087] S2215. After three-layer decomposition, the approximate coefficient and detail coefficient are obtained.

[0088] In one implementation of this embodiment, the step S222 may be further refined to include the following steps:

[0089] S2221, performing strong noise suppression on the primary detail coefficients while retaining the effective signal components in the high-level coefficients;

[0090] S222. Using the multi-scale entropy theory, the entropy value H is calculated based on the energy distribution of the detail coefficients of each layer, and the approximate slope slope_avg is calculated using the approximate coefficient:

[0091] Entropy , , where Dj represents the detail coefficient of the jth layer, and Pj is the energy proportion of the corresponding layer;

[0092] Approximate slope , A3 is the approximate coefficient of the third layer.

[0093] In one implementation of this embodiment, the step S223 may be further refined to include the following steps:

[0094] S2231, the entropy value H and the entropy value threshold H th Compare the approximate slope slope_avg with the slope threshold S th Make comparisons;

[0095] S2232: Convert the following comparison results into the charge and discharge status of the battery pack:

[0096] When the approximate slope slope_avg> slope threshold-S th , and the approximate slope slope_avg < slope threshold S th , the battery pack is in a static state;

[0097] When the entropy value H ≥ the entropy threshold H th And the approximate slope slope_avg> slope threshold S th , the battery pack is in a charging state;

[0098] When the entropy value H ≥ the entropy threshold H thAnd the approximate slope slope_avg ≤ slope threshold - S th , the battery pack is in a discharged state.

[0099] It should be noted that the key parameters are:

[0100] Entropy threshold H th =H noise +K*σ H , H noise Obtained through laboratory calibration (wavelet entropy benchmark value at rest), σ H is the standard deviation of entropy fluctuation, K is 3 (covering 99.7% confidence interval);

[0101] Slope threshold S th =S noise +k*σ S , S th Obtained by laboratory calibration (approximate slope absolute value at rest), σ S To approximate the standard deviation of slope fluctuation, k is taken as 3 (covering 99.7% confidence interval).

[0102] It is understandable that, based on the characteristic of the state switching that the battery pack will inevitably be stationary during charging and discharging, the slope can be calculated using a wavelet algorithm or other conventional methods, and the above entropy value can be changed to the sampling voltage jump amplitude of the battery pack charging or discharging. The charging and discharging state can also be judged based on the above judgment conditions, but the use of the above wavelet algorithm is more accurate and faster.

[0103] This embodiment provides a detection method that eliminates the need for a current sensor and, for the first time, utilizes an algorithm to analyze the battery pack's charge and discharge status. The algorithm prioritizes a wavelet algorithm. This method also proposes combining wavelet entropy with approximate slope as a charge and discharge status criterion, and proposes a double-buffered real-time processing architecture based on a circular queue. By leveraging the entropy value, sampled voltage slope, sampled voltage transition amplitude, and battery pack charge and discharge state transition characteristics, the method can detect the battery pack's charge and discharge status without a current sensor, utilizing only an algorithm (preferably the Haar algorithm). Any design that utilizes this principle for system optimization and modification is also applicable to this patent.

[0104] In one implementation of this embodiment, after S2, the method further includes:

[0105] S3. Outputting the determined charge and discharge status of the battery pack.

[0106] Although terms such as battery pack and voltage signal are frequently used in this application, the possibility of using other terms is not excluded. These terms are used only to more conveniently describe and explain the essence of the present invention; interpreting them as any additional limitations is contrary to the spirit of the present invention.

[0107] An embodiment of the present invention provides a method for detecting the charge and discharge status of a battery pack. Since there is no need to install an additional current sensor to detect the current of the battery pack, only the voltage signal of the battery pack needs to be detected. Then, the charge and discharge status of the battery pack can be analyzed through an algorithm. This method reduces additional hardware, simplifies circuit design, and reduces cost and complexity.

[0108] Finally, it should be noted that although the above embodiments have been described in the specification and drawings of this application, this does not limit the scope of patent protection of this application. All technical solutions generated by replacing or modifying equivalent structures or equivalent processes based on the essential concepts of this application using the contents recorded in the specification and drawings of this application, as well as directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, are included in the scope of patent protection of this application.

Claims

1. A method for detecting the charge and discharge status of a battery pack, characterized in that: include: S1, collect battery pack voltage signals and cache them; S2. Performing wavelet transform analysis on the collected signal to determine the charge and discharge status of the battery pack.

2. The method for detecting the charge and discharge status of a battery pack according to claim 1, wherein: In the S1, the sampling frequency is 1-100 kHz.

3. The method for detecting the charge and discharge status of a battery pack according to claim 2, wherein: In the S1, the sampling frequency is 10 Hz.

4. The method for detecting the charge and discharge status of a battery pack according to claim 1, wherein: In S1, the cache mechanism adopts a double-cache ring queue, that is, it is divided into two cache areas, namely cache area A and cache area B. When cache area A is full, processing is started, and cache area B is continuously filled while processing cache area A, thereby realizing parallel operation.

5. The method for detecting the charge and discharge status of a battery pack according to claim 1, wherein: The S2 includes: S21, selecting the wavelet basis function as Haar wavelet; S22 . Performing wavelet transform analysis on the collected signal using the Haar wavelet to determine the charge and discharge status of the battery pack.

6. The method for detecting the charge and discharge status of a battery pack according to claim 5, wherein: The S22 includes: S221, performing multi-level wavelet decomposition on the collected signal to extract the approximate coefficients and detail coefficients of each layer; S222, based on the approximate coefficients and detail coefficients obtained by multi-level wavelet decomposition, suppress noise through layered threshold processing, and use multi-scale entropy theory to calculate entropy values and approximate slopes to extract characteristic information of the signal; S223 : Compare the entropy value and the approximate slope obtained in the feature extraction stage with the set threshold value, and judge the charge and discharge state of the battery pack according to different conditions.

7. The method for detecting the charge and discharge status of a battery pack according to claim 6, wherein: The S221 includes: S2211, input original sampling data array; S2212. Check whether the length is greater than or equal to an integer power of 2 and is an even number; otherwise, report an error. S2213, initialization process calculation array, the length of which is equal to the original data array; S2214. For each layer: a. Check whether the length is greater than or equal to an integer power of 2 and is an even number, otherwise an error is reported; b. Decompose to obtain the approximate coefficient and detail coefficient of the current layer; c. Save the approximate coefficients and detail coefficients of the current layer; d. Store the updated coefficients in the process calculation array and update the length to half of the original length; S2215. After three-layer decomposition, the approximate coefficient and detail coefficient are obtained.

8. The method for detecting the charge and discharge status of a battery pack according to claim 7, wherein: The S222 includes: S2221, performing strong noise suppression on the primary detail coefficients while retaining the effective signal components in the high-level coefficients; S222. Using the multi-scale entropy theory, the entropy value H is calculated based on the energy distribution of the detail coefficients of each layer, and the approximate slope slope_avg is calculated using the approximate coefficient: Entropy , , where D j represents the detail coefficient of the jth layer, P j is the energy proportion of the corresponding layer; Approximate slope , A3 is the approximate coefficient of the third layer.

9. The method for detecting the charge and discharge status of a battery pack according to claim 8, wherein: The S223 includes: S2231, the entropy value H and the entropy value threshold H th Compare the approximate slope slope_avg with the slope threshold S th Make comparisons; S2232: Convert the following comparison results into the charge and discharge status of the battery pack: When the approximate slope slope_avg> slope threshold-S th , and the approximate slope slope_avg < slope threshold S th , the battery pack is in a static state; When the entropy value H ≥ the entropy threshold H th And the approximate slope slope_avg> slope threshold S th , the battery pack is in a charging state; When the entropy value H ≥ the entropy threshold H th And the approximate slope slope_avg ≤ slope threshold - S th , the battery pack is in a discharged state.

10. The method for detecting the charge and discharge status of a battery pack according to claim 1, wherein: After S2, the method further includes: S3. Outputting the determined charge and discharge status of the battery pack.

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