Energy storage battery fault detection method

Abstract

An embodiment of the present invention discloses a method for detecting energy storage battery faults, comprising: collecting an electrical signal from an energy storage battery to construct a fault detection start signal; sequentially determining multiple first time window energies within a first time window based on the fault detection start signal; when the absolute value of at least one first time window energy is greater than a fault detection threshold, sequentially performing power transformation on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it on its left and right sides to obtain 2X+1 power transformation values; constructing a faulty battery identification signal based on the 2X+1 power transformation values; determining a second time window energy within a second time window based on the faulty battery identification signal; and outputting fault information about the energy storage battery when the second time window energy is greater than the fault identification threshold; the time window length of the first time window is less than the time window length of the second time window, where 2X+1 is the time window length of the second time window. The above method can quickly and accurately identify faulty energy storage batteries, etc.

Description

Technical Field

[0001] The present invention relates to the technical field of batteries, and in particular to a method for detecting faults in energy storage batteries. Background Art

[0002] With the development and construction of my country's power grid, in order to maintain the stable and reliable operation of the power system, general power systems are equipped with energy storage systems. With the continuous development of energy storage technology and the continuous increase in the scale of energy storage, the safe and stable operation of energy storage systems has a significant impact on the safe and stable operation of the power system. In energy storage systems, energy storage forms are divided into electrochemical energy storage and physical energy storage. Among them, electrochemical energy storage has become the mainstream of energy storage system development due to its flexible and convenient construction and short construction cycle. However, if the energy storage battery in electrochemical energy storage fails, it will affect the safe and stable operation of the power system. Therefore, when an energy storage battery fails, it is necessary to quickly and accurately detect and remove the faulty energy storage battery to ensure the safe and stable operation of the power system.

[0003] Currently, when performing fault detection on energy storage batteries, it is not possible to quickly and accurately identify the faulty battery, and there are problems such as slow detection speed and low efficiency. Summary of the Invention

[0004] Based on this, it is necessary to address the above problems and propose a method for energy storage battery fault detection, which can quickly and accurately identify faulty energy storage batteries and greatly improve the fault detection speed and efficiency of energy storage batteries to ensure the safe and stable operation of the power system.

[0005] To achieve the above object, the present invention provides a method for detecting a fault in an energy storage battery, the method comprising:

[0006] Collecting electrical signals from the energy storage battery and constructing a fault detection start signal based on the electrical signals;

[0007] sequentially determining a plurality of first time window energies within a first time window according to the fault detection start signal, and when an absolute value of at least one of the first time window energies is greater than a fault detection threshold, sequentially performing power transformation processing on any first time window energy having an absolute value greater than the fault detection threshold and each of X first time window energies adjacent to it on its left and right to obtain 2X+1 power transformation values;

[0008] constructing a faulty battery identification signal according to 2X+1 of the power transformation values;

[0009] determining a second time window energy according to the faulty battery identification signal within a second time window, and outputting fault information of the energy storage battery when the second time window energy is greater than a fault identification threshold;

[0010] The time window length of the first time window is smaller than the time window length of the second time window, and 2X+1 is the time window length of the second time window.

[0011] Optionally, constructing a fault detection start signal according to the electrical signal includes:

[0012] Performing analog-to-digital conversion on the electrical signal to obtain a digital signal, and performing discrete sampling on the digital signal to obtain a plurality of sampling signals;

[0013] A plurality of differential signals are obtained by performing differential processing on the plurality of sampling signals, and the fault detection start signal is constructed according to the plurality of differential signals.

[0014] Optionally, performing differential processing on the plurality of sampling signals to obtain a plurality of differential signals includes any one of the following:

[0015] Performing forward differential processing on the plurality of sampling signals to obtain a plurality of differential signals;

[0016] Performing backward differential processing on the plurality of sampling signals to obtain a plurality of differential signals;

[0017] Performing center difference processing on the plurality of sampling signals to obtain a plurality of differential signals.

[0018] Optionally, performing forward differential processing on the plurality of sampling signals to obtain the plurality of differential signals includes:

[0019] Determining a plurality of differential signals using the formula Δx(i)=x(i+1)-x(i);

[0020] The performing backward differential processing on the plurality of sampling signals to obtain the plurality of differential signals includes:

[0021] Determine a plurality of differential signals using the formula Δx(i)=x(i)-x(i-1);

[0022] The performing center difference processing on the plurality of sampling signals to obtain the plurality of differential signals includes:

[0023] Using the formula determining a plurality of said differential signals;

[0024] Wherein, Δx(i) is the i-th differential signal, x(i+1) is the i+1-th sampling signal, x(i) is the i-th sampling signal; x(i-1) is the i-1-th sampling signal, and Δt is the sampling time interval.

[0025] Optionally, sequentially determining a plurality of first time window energies according to the fault detection start signal within the first time window includes:

[0026] Sliding the first time window to the Mth signal of the fault detection start signal, and each time the first time window slides backward by one signal of the fault detection start signal, calculating the sum of the M signals of the fault detection start signal in the first time window, and using the sum as the first time window energy, until the first time window slides to the last signal of the fault detection start signal, thereby obtaining multiple first time window energies;

[0027] Wherein, M is the time window length of the first time window.

[0028] Optionally, calculating the sum of the M fault detection start signals within the first time window includes:

[0029] Using the formula calculating the sum;

[0030] Wherein, EI is the sum value, and a(j) is the j-th signal among the M signals of the fault detection start signal in the first time window.

[0031] Optionally, the sequentially performing power transformation processing on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it on the left and right to obtain 2X+1 power transformation values ​​includes:

[0032] Using the formula Δy(k)=[EI(k)] α Determining 2X+1 of the power transformation values;

[0033] Wherein, Δy(k) is the kth power transformation value, EI(k) is the kth first time window energy among any first time window energy and the X first time window energies adjacent to it on its left and right, whose absolute value is greater than the fault detection threshold, and α is the power exponent.

[0034] Optionally, determining the second time window energy according to the faulty battery identification signal within the second time window includes:

[0035] Slide the second time window to the 2X+1th signal of the faulty battery identification signal, calculate the sum of the absolute values ​​of the 2X+1 signals of the faulty battery identification signal in the second time window, and use the sum as the second time window energy.

[0036] Optionally, calculating the sum of the absolute values ​​of 2X+1 signals of the faulty battery identification signal within the second time window includes:

[0037] Using the formula calculating the sum;

[0038] Wherein, EII is the sum value, and |b(j)| is the absolute value of the j-th signal among the 2X+1 signals of the faulty battery identification signal in the second time window.

[0039] Optionally, the method further includes:

[0040] When the absolute values ​​of the energies in the multiple first time windows are all less than or equal to the fault detection threshold, or when the energy in the second time window is less than or equal to the fault identification threshold, the normal information of the energy storage battery is output.

[0041] The embodiment of the present invention has the following beneficial effects: collecting an electrical signal from an energy storage battery and constructing a fault detection start signal based on the electrical signal; sequentially determining multiple first time window energies based on the fault detection start signal within a first time window; when the absolute value of at least one first time window energy is greater than a fault detection threshold, sequentially performing power transformation processing on any first time window energy having an absolute value greater than the fault detection threshold and each of the X first time window energies adjacent to it on its left and right sides to obtain 2X+1 power transformation values; constructing a faulty battery identification signal based on the 2X+1 power transformation values; determining a second time window energy based on the faulty battery identification signal within a second time window; and outputting fault information of the energy storage battery when the second time window energy is greater than the fault identification threshold; wherein the time window length of the first time window is less than the time window length of the second time window, and 2X+1 is the time window length of the second time window. The above method constructs a fault detection start signal based on the collected electrical signal of the energy storage battery, and sequentially determines multiple first time window energies within a first time window based on the fault detection start signal. When the absolute value of at least one first time window energy is greater than a fault detection threshold, any first time window energy with an absolute value greater than the fault detection threshold and each of the X first time window energies adjacent to it on its left and right are sequentially subjected to power transformation to obtain 2X+1 power transformation values. A faulty battery identification signal is constructed based on the 2X+1 power transformation values. A second time window energy is determined within a second time window based on the faulty battery identification signal. When the second time window energy is greater than the fault identification threshold, it is determined that the energy storage battery has a fault, and fault information of the energy storage battery is output, thereby quickly and accurately identifying the faulty energy storage battery. This method greatly improves the fault detection speed and efficiency of the energy storage battery, thereby ensuring the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] 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.

[0043] in:

[0044] Figure 1 This is a flow chart of a method for detecting a fault in an energy storage battery according to an embodiment of the present application;

[0045] Figure 2 A schematic diagram of a curve connecting various voltage values ​​of digital signals of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application;

[0046] Figure 3 A schematic diagram of a curve connecting 2X+1 power transformation values ​​of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application;

[0047] Figure 4 Schematic diagram of the amplitude of the second time window energy of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] See also Figure 1 , is a flow chart of a method for detecting a fault in an energy storage battery according to an embodiment of the present application, the method comprising:

[0050] Step 110: Collect the electrical signal of the energy storage battery and construct a fault detection start signal according to the electrical signal.

[0051] The electrical signal may be a voltage signal or a current signal. In the embodiment of the present application, a voltage signal is selected, that is, the voltage signal of the energy storage battery is collected by the battery management unit.

[0052] It should be noted that, for constructing a fault detection start signal based on an electrical signal, the electrical signal can be first subjected to analog-to-digital conversion to obtain a digital signal, and the digital signal can be discretely sampled to obtain multiple sampling signals, and the multiple sampling signals can be differentially processed to obtain multiple differential signals, and the fault detection start signal can be constructed based on the multiple differential signals. It can be understood that when the electrical signal is a voltage signal, since the fluctuation of the curve connected by the various voltage values ​​of the digital signal of the faulty energy storage battery is different from that of the normal energy storage battery, that is, the fluctuation of the curve connected by the various voltage values ​​of the digital signal of the faulty energy storage battery is much greater than the fluctuation of the curve connected by the various voltage values ​​of the digital signal of the normal energy storage battery. For an example, please refer to Figure 2, which is a schematic diagram of a curve connecting the voltage values ​​of the mathematical signals of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application, according to Figure 2 As shown, the fluctuations of the curves (solid lines) connected by the various voltage values ​​of the digital signals of other normal energy storage batteries are basically concentrated in a certain range, while the fluctuations of the curves (dashed lines) connected by the various voltage values ​​of the digital signals of the faulty energy storage batteries show large fluctuations. Therefore, the present application can sample the various voltage values ​​of the digital signals of the faulty energy storage batteries in response to the large fluctuations of the curves connected by the various voltage values ​​of the digital signals, thereby obtaining multiple sampled signals.

[0053] It should be further explained that performing differential processing on multiple sampling signals to obtain multiple differential signals can include any one of the following three methods: performing forward differential processing on multiple sampling signals to obtain multiple differential signals; performing backward differential processing on multiple sampling signals to obtain multiple differential signals; and performing center differential processing on multiple sampling signals to obtain multiple differential signals.

[0054] Step 120: Multiple first time window energies are sequentially determined within the first time window according to the fault detection start signal. When the absolute value of at least one first time window energy is greater than the fault detection threshold, power transformation is performed on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it on its left and right to obtain 2X+1 power transformation values.

[0055] Among them, the fault detection threshold is pre-set by the operator according to actual needs. In the embodiment of the present application, the fault detection threshold is generally pre-set to 50.

[0056] In this application, the value of X is related to the time window length of the second time window, that is, 2X+1 is the time window length of the second time window. It can be understood that the time window length of the second time window is set by the operator according to actual needs. Generally, the operator will set the time window length of the second time window to 1001 (in seconds). At this time, X is 500.

[0057] It should be noted that, for determining multiple first time window energies in sequence according to the fault detection start signal within the first time window, the first time window can be slid to the Mth signal of the fault detection start signal. Each time the first time window slides back one signal of the fault detection start signal, the sum of the M signals of the fault detection start signal within the first time window is calculated, and the sum is used as the first time window energy, until the first time window slides to the last signal of the fault detection start signal, and multiple first time window energies are obtained, where M is the time window length of the first time window. It can be understood that since the fault detection start signal is constructed by multiple differential signals (since the fault detection start signal is composed of multiple differential signals), and it can be understood that the multiple differential signals are arranged in a sequence, therefore, during the sliding of the first time window, the sum of the M signals within the first time window can be calculated each time the first time window slides, and the sum is used as the first time window energy. For example, when M is 9, that is, the time window length of the first time window is 9 (in seconds), if the number of signals in the fault detection start signal is 8000, then the sum value obtained is 7992, that is, the number of energies in the first time window is 7992.

[0058] It should also be noted that when performing power transformation processing on any first time window energy and its X adjacent first time window energies on the left and right of the first time window energy whose absolute value is greater than the fault detection threshold to obtain 2X+1 power transformation values, the power exponent used is an odd number, that is, 1, 3, 5, 7, 9, etc. can be selected. In the embodiment of the present application, the power exponent is generally set to 3. It can be understood that since the first time window energy has positive and negative numbers, the use of an odd power exponent during power transformation can retain the positive and negative signs of the first time window energy. Furthermore, since the difference between the first time window energy of a faulty energy storage battery and the first time window energy of a normal energy storage battery is not so obvious, it is necessary to perform power transformation processing on the first time window energy so that the first time window energy of the faulty energy storage battery is much larger than the first time window energy of the normal energy storage battery, so as to facilitate accurate identification of the faulty energy storage battery. For example, please refer to Figure 3 , which is a schematic diagram of a curve connecting 2X+1 power transformation values ​​of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application, according to Figure 3As shown, the amplitude range of the curve connected by the 2X+1 power-transformed values ​​of other normal energy storage batteries is -0.2 to 0.2, while the amplitude range of the curve connected by the 2X+1 power-transformed values ​​of the faulty energy storage battery is -100 to 100. Therefore, the present application can obtain 2X+1 power-transformed values ​​by sequentially performing power transformation on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it on the left and right, so as to enhance the difference between the faulty energy storage battery and the normal energy storage battery, thereby facilitating the accurate identification of the faulty energy storage battery.

[0059] Step 130: Construct a faulty battery identification signal based on the 2X+1 power transformation values.

[0060] It should be noted that the faulty battery identification signal is constructed by 2X+1 power transformation values, or the faulty battery identification signal is composed of 2X+1 power transformation values. Therefore, it can be understood that the faulty battery identification signal is composed of 2X+1 power transformation values ​​arranged in a sequence.

[0061] Step 140: Determine a second time window energy according to the faulty battery identification signal within the second time window, and output fault information of the energy storage battery when the second time window energy is greater than a fault identification threshold.

[0062] Among them, the fault identification threshold is pre-set by the operator according to actual needs. In the embodiment of the present application, the fault identification threshold is generally pre-set to 100.

[0063] It should be noted that, in determining the second time window energy based on the faulty battery identification signal within the second time window, the second time window can be slid to the 2X+1th signal of the faulty battery identification signal, and the sum of the absolute values ​​of the 2X+1 signals of the faulty battery identification signal within the second time window is calculated, and the sum is used as the second time window energy. It can be understood that since the faulty battery identification signal is composed of 2X+1 power-transformed values ​​arranged in a sequence, during the sliding process of the second time window, the second time window only needs to slide once to directly calculate the sum of the absolute values ​​of the 2X+1 signals within the second time window, and use the sum as the second time window energy. For example, when the time window length of the second time window is 1001 (in seconds), that is, when 2X+1 is 1001, the number of signals in the fault detection start signal is only 1001, and the resulting sum is 1, that is, the number of the second time window energy is 1.

[0064] For examples, see Figure 4 , is a schematic diagram of the amplitude of the second time window energy of a faulty energy storage battery and a normal energy storage battery in an embodiment of the present application, according to Figure 4As shown, the amplitudes of the second time window energies of other normal energy storage batteries (1-15, 17-20) are relatively small, while the amplitude of the second time window energy of the faulty energy storage battery (16) is particularly large, that is, the amplitudes of the second time window energies of other normal energy storage batteries (1-15, 17-20) are about 5, while the amplitude of the second time window energy of the faulty energy storage battery (16) can reach about 1800. Since the amplitudes of the second time window energies of the faulty energy storage battery and the normal energy storage battery are greatly different, the faulty energy storage battery can be quickly and accurately identified by setting a fault identification threshold.

[0065] In the embodiment of the present application, the time window length of the first time window needs to be smaller than the time window length of the second time window, that is, when the time window length M of the first time window is 9 (in seconds), the time window length 2X+1 of the second time window can be 1001 (in seconds). It can be understood that by setting the time window length of the second time window to be much larger than the time window length of the first time window, the faulty energy storage battery can be quickly and accurately identified, thereby greatly improving the fault detection speed and fault detection efficiency of the energy storage battery.

[0066] It should also be noted that the present application executes the method in the embodiment of the present application on all energy storage batteries in the energy storage system at the same time, that is, fault detection is performed on all energy storage batteries at the same time in a concurrent manner; in addition, in some special cases, the operator can perform fault detection on only one energy storage battery or perform fault detection on each energy storage battery in sequence according to actual needs.

[0067] In another feasible implementation, the method in the above embodiment can also be: when the absolute value of at least one first time window energy is greater than the fault detection threshold, the Z first time window energies adjacent to the left and right of any first time window energy whose absolute value is greater than the fault detection threshold are sequentially subjected to power transformation processing to obtain 2Z power transformation values; a faulty battery identification signal is constructed based on the 2Z power transformation values; wherein 2Z is ​​the time window length of the second time window (when the time window length of the second time window is set to 1000 (in seconds), Z is 500 at this time). It can be understood that even if the first time window energy of the center point of each Z first time window energy adjacent to the left and right is removed, it will not affect the fault detection of the energy storage battery in the embodiment of the present application.

[0068] In an embodiment of the present application, a fault detection start signal is constructed based on the collected electrical signal of the energy storage battery, and multiple first time window energies are sequentially determined within a first time window based on the fault detection start signal. When the absolute value of at least one first time window energy is greater than a fault detection threshold, power transformation is sequentially performed on any first time window energy having an absolute value greater than the fault detection threshold and each of the X first time window energies adjacent to it on its left and right to obtain 2X+1 power transformation values. A faulty battery identification signal is constructed based on the 2X+1 power transformation values. A second time window energy is determined within a second time window based on the faulty battery identification signal. When the second time window energy is greater than the fault identification threshold, it is determined that the energy storage battery has a fault, and fault information of the energy storage battery is output, thereby quickly and accurately identifying the faulty energy storage battery. This method greatly improves the fault detection speed and efficiency of the energy storage battery, thereby ensuring the safe and stable operation of the power system.

[0069] In a feasible implementation, in step 110, a fault detection start signal is constructed based on the electrical signal, including: performing analog-to-digital conversion processing on the electrical signal to obtain a digital signal, and performing discrete sampling processing on the digital signal to obtain multiple sampling signals; performing differential processing on the multiple sampling signals to obtain multiple differential signals, and constructing a fault detection start signal based on the multiple differential signals.

[0070] It should be noted that, with respect to constructing a fault detection start signal based on multiple differential signals, it can be understood that the fault detection start signal is constructed by multiple differential signals, or the fault detection start signal is composed of multiple differential signals. Therefore, it can be understood that the fault detection start signal is composed of multiple differential signals arranged in a sequence.

[0071] In an embodiment of the present application, an electrical signal is subjected to analog-to-digital conversion to obtain a digital signal, the digital signal is subjected to discrete sampling to obtain a plurality of sampling signals, and the plurality of sampling signals are subjected to differential processing to obtain a plurality of differential signals. A fault detection start signal is constructed based on the plurality of differential signals, so as to quickly and accurately identify a faulty energy storage battery, thereby improving the fault detection speed and efficiency of the energy storage battery, and ensuring the safe and stable operation of the power system.

[0072] In a feasible implementation, differential processing is performed on multiple sampling signals to obtain multiple differential signals, including any of the following: forward differential processing is performed on multiple sampling signals to obtain multiple differential signals; backward differential processing is performed on multiple sampling signals to obtain multiple differential signals; and center differential processing is performed on multiple sampling signals to obtain multiple differential signals.

[0073] In an embodiment of the present application, a plurality of differential signals are obtained by differentially processing the plurality of sampling signals in a preferred manner, that is, by selecting any one of the three methods of performing forward differential processing on the plurality of sampling signals to obtain a plurality of differential signals, performing backward differential processing on the plurality of sampling signals to obtain a plurality of differential signals, and performing center differential processing on the plurality of sampling signals to obtain a plurality of differential signals. This facilitates selection by an operator, and any of the three methods can achieve rapid and accurate identification of faulty energy storage batteries, thereby improving the speed and efficiency of fault detection of energy storage batteries, thereby ensuring safe and stable operation of the power system.

[0074] In a feasible implementation, forward differential processing is performed on multiple sampling signals to obtain multiple differential signals, including: using the formula Δx(i) = x(i+1)-x(i) to determine multiple differential signals; backward differential processing is performed on multiple sampling signals to obtain multiple differential signals, including: using the formula Δx(i) = x(i)-x(i-1) to determine multiple differential signals; performing central differential processing on multiple sampling signals to obtain multiple differential signals, including: using the formula Determine multiple differential signals; where Δx(i) is the i-th differential signal, x(i+1) is the i+1-th sampling signal, x(i) is the i-th sampling signal; x(i-1) is the i-1-th sampling signal, and Δt is the sampling time interval.

[0075] In an embodiment of the present application, calculation formulas are given for three methods: performing forward differential processing on multiple sampling signals to obtain multiple differential signals, performing backward differential processing on multiple sampling signals to obtain multiple differential signals, and performing center differential processing on multiple sampling signals to obtain multiple differential signals, to ensure that multiple differential signals are obtained and to facilitate the operator's calculation of the differential signals.

[0076] In a feasible implementation, in step 120, multiple first time window energies are determined in sequence within the first time window according to the fault detection start signal, including: sliding the first time window to the Mth signal of the fault detection start signal, and each time the first time window slides back by one signal of the fault detection start signal, the sum of the M signals of the fault detection start signal within the first time window is calculated, and the sum is used as the first time window energy, until the first time window slides to the last signal of the fault detection start signal, to obtain multiple first time window energies; wherein, M is the time window length of the first time window.

[0077] The time window length of the first time window is set by the operator according to actual needs. Generally, the operator sets the time window length of the first time window to 9 (in seconds). At this time, M is also 9.

[0078] It should be noted that since the fault detection start signal is composed of multiple differential signals arranged in a sequence, during the sliding of the first time window, the sum of the M signals in the first time window can be calculated each time the first time window slides, and the sum can be used as the energy of the first time window.

[0079] In an embodiment of the present application, by sliding the first time window to the Mth signal of the fault detection start signal, each time the first time window slides back one signal of the fault detection start signal, the sum of the M signals of the fault detection start signal in the first time window is calculated, and the sum is used as the first time window energy, until the first time window slides to the last signal of the fault detection start signal, and multiple first time window energies are obtained, thereby facilitating the judgment of multiple first time window energies to achieve rapid and accurate identification of faulty energy storage batteries, thereby improving the fault detection speed and fault detection efficiency of the energy storage batteries, etc., to ensure safe and stable operation of the power system.

[0080] In a feasible implementation, calculating the sum of the M signals of the fault detection start signal in the first time window includes: using the formula Calculate the sum value; where EI is the sum value, and a(j) is the j-th signal among the M signals of the fault detection start signal in the first time window.

[0081] In an embodiment of the present application, a calculation formula is given for calculating the sum of the M signals of the fault detection start signal within the first time window to ensure that the sum of the M signals of the fault detection start signal within the first time window is obtained, and to facilitate the operator's calculation of the sum.

[0082] In a feasible implementation, in step 120, power transformation is performed on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it to the left and right to obtain 2X+1 power transformation values, including: using the formula Δy(k)=[EI(k)] α Determine 2X+1 power transformation values; where Δy(k) is the kth power transformation value, EI(k) is the kth first time window energy among any first time window energy and the X first time window energies adjacent to it, whose absolute value is greater than the fault detection threshold, and α is the power exponent.

[0083] It should be noted that the power exponent α can take an odd number greater than 0, that is, 1, 3, 5, 7, 9, etc. can be selected. It can be understood that since the energy of the first time window has positive and negative numbers, when performing the power transformation processing, using an odd power exponent can retain the positive and negative signs of the energy of the first time window.

[0084] It should be further explained that for examples, please continue to refer to Figure 3As shown, the amplitude range of the curve connected by the 2X+1 power-transformed values ​​of other normal energy storage batteries is -0.2 to 0.2, while the amplitude range of the curve connected by the 2X+1 power-transformed values ​​of the faulty energy storage battery is -100 to 100. Therefore, the present application can obtain 2X+1 power-transformed values ​​by sequentially performing power transformation on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent to it on the left and right, so as to enhance the difference between the faulty energy storage battery and the normal energy storage battery, thereby facilitating the accurate identification of the faulty energy storage battery.

[0085] In an embodiment of the present application, 2X+1 power-transformed values ​​are obtained by sequentially performing power transformation processing on any first time window energy having an absolute value greater than a fault detection threshold and each of the X first time window energies adjacent to it on both sides, thereby enhancing the distinction between a faulty energy storage battery and a normal energy storage battery, thereby facilitating accurate identification of the faulty energy storage battery. Furthermore, a calculation formula is provided for calculating the power-transformed value obtained by performing power transformation processing on any first time window energy having an absolute value greater than the fault detection threshold and each of the X first time window energies adjacent to it on both sides, thereby ensuring that the power-transformed value obtained after the power transformation processing is obtained and facilitating calculation of the power-transformed value by the operator.

[0086] In a feasible implementation, in step 140, the second time window energy is determined based on the faulty battery identification signal within the second time window, including: sliding the second time window to the 2X+1th signal of the faulty battery identification signal, calculating the sum of the absolute values ​​of the 2X+1 signals of the faulty battery identification signal within the second time window, and using the sum as the second time window energy.

[0087] When the time window length of the second time window is set to 1001 (in seconds), 2X+1 is 1001.

[0088] It should be noted that since the faulty battery identification signal is composed of 2X+1 power transformation values ​​arranged in a sequence, during the sliding of the second time window, the second time window only needs to slide once to directly calculate the sum of the absolute values ​​of the 2X+1 signals in the second time window, and use the sum as the energy of the second time window.

[0089] In an embodiment of the present application, by sliding the second time window to the 2X+1th signal of the faulty battery identification signal, calculating the sum of the absolute values ​​of the 2X+1 signals of the faulty battery identification signal within the second time window, and using the sum as the second time window energy, the second time window energy is obtained, thereby facilitating the judgment of the second time window energy. When the second time window energy is greater than the fault identification threshold, it is determined that the energy storage battery has a fault, and the fault information of the energy storage battery is output, thereby quickly and accurately identifying the faulty energy storage battery. This method greatly improves the fault detection speed and fault detection efficiency of the energy storage battery, thereby ensuring the safe and stable operation of the power system.

[0090] In a feasible implementation, calculating the sum of the absolute values ​​of 2X+1 signals of the faulty battery identification signal in the second time window includes: using the formula Calculate the sum value; where EII is the sum value, |b(j)| is the absolute value of the jth signal among the 2X+1 signals of the faulty battery identification signal in the second time window.

[0091] In an embodiment of the present application, a calculation formula is given for calculating the sum of the absolute values ​​of N signals of the faulty battery identification signal within the second time window to ensure that the sum of the absolute values ​​of the N signals of the faulty battery identification signal within the second time window is obtained, and to facilitate the operator's calculation of the sum.

[0092] In a feasible implementation, the method in the above embodiment also includes: when the absolute values ​​of multiple first time window energies are all less than or equal to the fault detection threshold, or when the second time window energy is less than or equal to the fault identification threshold, outputting normal information of the energy storage battery.

[0093] It should be noted that when the absolute values ​​of multiple first time window energies are all less than or equal to the fault detection threshold, it means that there is no possibility of failure of this energy storage battery, and there is no need to perform step 130 and subsequent judgments. Or when the second time window energy is less than or equal to the fault identification threshold, it means that there is no possibility of failure of this energy storage battery, and therefore, the normal information of the energy storage battery is directly output to facilitate the operator to understand that the energy storage battery is in a normal state.

[0094] In an embodiment of the present application, when the absolute values ​​of multiple first time window energies are all less than or equal to the fault detection threshold, or when the second time window energy is less than or equal to the fault identification threshold, normal information of the energy storage battery is output to facilitate the operator to understand that the energy storage battery is in a normal state.

[0095] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0096] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for detecting a fault in an energy storage battery, characterized in that: The method comprises: Collecting electrical signals from the energy storage battery and constructing a fault detection start signal based on the electrical signals; sequentially determining a plurality of first time window energies within a first time window according to the fault detection start signal, and when the absolute value of at least one first time window energy is greater than a fault detection threshold, sequentially performing power transformation processing on any first time window energy having an absolute value greater than the fault detection threshold and each of X first time window energies adjacent to it on its left and right to obtain 2X+1 power transformation values; constructing a faulty battery identification signal according to 2X+1 of the power transformation values; determining a second time window energy according to the faulty battery identification signal within a second time window, and outputting fault information of the energy storage battery when the second time window energy is greater than a fault identification threshold; The time window length of the first time window is less than the time window length of the second time window, and 2X+1 is the time window length of the second time window; in, The constructing a fault detection start signal according to the electrical signal comprises: Processing the electrical signal to obtain a plurality of differential signals; Arranging the plurality of differential signals in sequence to obtain the fault detection start signal; The constructing of a faulty battery identification signal according to the 2X+1 power transformation values ​​includes: Arrange the 2X+1 power transformation values ​​in sequence to obtain the faulty battery identification signal.

2. The method according to claim 1, characterized in that The processing of the electrical signal to obtain a plurality of differential signals includes: Performing analog-to-digital conversion on the electrical signal to obtain a digital signal, and performing discrete sampling on the digital signal to obtain a plurality of sampling signals; Perform differential processing on the plurality of sampling signals to obtain a plurality of differential signals.

3. The method according to claim 2, characterized in that The differential processing of the plurality of sampling signals to obtain a plurality of differential signals includes any one of the following: Performing forward differential processing on the plurality of sampling signals to obtain a plurality of differential signals; Performing backward differential processing on the plurality of sampling signals to obtain a plurality of differential signals; Performing center difference processing on the plurality of sampling signals to obtain a plurality of differential signals.

4. The method according to claim 3, characterized in that The performing forward differential processing on the plurality of sampling signals to obtain the plurality of differential signals comprises: Determining a plurality of differential signals using the formula Δx(i)=x(i+1)-x(i); The performing backward differential processing on the plurality of sampling signals to obtain the plurality of differential signals includes: Determining a plurality of the differential signals using the formula Δx(i)=x(i)-x(i-1); The performing center difference processing on the plurality of sampling signals to obtain the plurality of differential signals includes: Using the formula determining a plurality of said differential signals; Wherein, Δx(i) is the i-th differential signal, x(i+1) is the i+1-th sampling signal, x(i) is the i-th sampling signal; x(i-1) is the i-1-th sampling signal, and Δt is the sampling time interval.

5. The method according to claim 1, characterized in that The step of sequentially determining a plurality of first time window energies according to the fault detection start signal within the first time window includes: Sliding the first time window to the Mth signal of the fault detection start signal, and each time the first time window slides backward by one signal of the fault detection start signal, calculating the sum of the M signals of the fault detection start signal in the first time window, and using the sum as the first time window energy, until the first time window slides to the last signal of the fault detection start signal, thereby obtaining multiple first time window energies; Wherein, M is the time window length of the first time window.

6. The method according to claim 5, characterized in that The calculating the sum of the M signals of the fault detection start signal within the first time window includes: Using the formula calculating the sum; Wherein, EI is the sum value, and a(j) is the j-th signal among the M signals of the fault detection start signal in the first time window.

7. The method according to claim 5, characterized in that The step of sequentially performing power transformation on any first time window energy whose absolute value is greater than the fault detection threshold and each of the X first time window energies adjacent thereto to the left and right to obtain 2X+1 power transformation values ​​includes: Using the formula Δy(k)=[EI(k)] α Determining 2X+1 of the power transformation values; Wherein, Δy(k) is the kth power transformation value, EI(k) is the kth first time window energy among any first time window energy and the X first time window energies adjacent to it on its left and right, whose absolute value is greater than the fault detection threshold, and α is the power exponent.

8. The method according to claim 1, characterized in that Determining the second time window energy according to the faulty battery identification signal within the second time window includes: Slide the second time window to the 2X+1th signal of the faulty battery identification signal, calculate the sum of the absolute values ​​of the 2X+1 signals of the faulty battery identification signal in the second time window, and use the sum as the second time window energy.

9. The method according to claim 8, characterized in that Calculating the sum of the absolute values ​​of 2X+1 signals of the faulty battery identification signal within the second time window includes: Using the formula calculating the sum; Wherein, EII is the sum value, and |b(j)| is the absolute value of the j-th signal among the 2X+1 signals of the faulty battery identification signal in the second time window.

10. The method according to any one of claims 1 to 9, characterized in that The method further comprises: When the absolute values ​​of the energies in the multiple first time windows are all less than or equal to the fault detection threshold, or when the energy in the second time window is less than or equal to the fault identification threshold, the normal information of the energy storage battery is output.

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