Control method, converter, controller and electric equipment

Abstract

The embodiment of the invention provides a control method, a converter, a controller and electric equipment, and is used for controlling energy storage equipment, obtaining an anti-phase compensation signal corresponding to an excitation signal, and applying the anti-phase compensation signal to energy storage equipment not to be tested when the excitation signal is applied to the energy storage equipment to be tested. Harmonic phases caused by the excitation signal and the anti-phase compensation signal are opposite and can offset each other, so that current disturbance and harmonic waves generated by a branch circuit where the energy storage equipment is located can be compensated, the influence of the disturbance and the harmonic waves can be weakened or eliminated, and stable output of a direct-current bus is ensured.

Description

Technical Field

[0001] This application relates to the field of energy storage equipment, and more particularly to a control method, converter, controller and electrical equipment. Background Technology

[0002] In energy storage systems, the health status of batteries directly affects energy storage efficiency, safety, and lifespan. Dynamic impedance sensing technology can monitor changes in the impedance characteristics of batteries in real time during charging and discharging, thereby assessing the battery's state of charge (SOC), state of health (SOH), and potential failure risks.

[0003] Existing online impedance spectroscopy measurement circuits can cause high-frequency current and voltage responses in energy storage systems, resulting in harmonics and disturbances in the branch where the measured energy storage device is located. This can lead to harmonics and disturbances on the DC bus of the energy storage system, affecting the stable output of the DC bus. Summary of the Invention

[0004] This application provides a control method, converter, controller, and electrical equipment to reduce harmonics and disturbances on the DC bus and ensure stable output of the DC bus.

[0005] In a first aspect, embodiments of this application provide a control method for controlling an energy storage device, comprising:

[0006] Obtain the inverted compensation signal corresponding to the excitation signal;

[0007] When the excitation signal is applied to the energy storage device under test, the inverting compensation signal is applied to the non-energy storage device under test.

[0008] Optionally, applying the inverted compensation signal to the non-test energy storage device includes:

[0009] The inverting compensation signal is applied to a non-energy storage device adjacent to the energy storage device under test;

[0010] And / or, the method further includes:

[0011] Obtain the excitation signal;

[0012] When the energy storage device under test meets the measurement conditions, an excitation signal is applied to the energy storage device under test.

[0013] Optionally, the number of the energy storage devices under test is multiple; the method further includes:

[0014] Acquire the excitation signal corresponding to each of the energy storage devices under test;

[0015] The excitation signal corresponding to each of the energy storage devices under test is applied to each of the energy storage devices under test in turn.

[0016] Secondly, this application provides a control method for controlling an energy storage device, comprising:

[0017] A corresponding inverse compensation signal is determined, and the inverse compensation signal is used to apply to the branch where the non-tested energy storage device is located when the excitation signal is applied to the energy storage device under test.

[0018] Optionally, determining the inverting compensation signal corresponding to the excitation signal includes:

[0019] Determine the excitation current corresponding to the excitation signal;

[0020] Based on the excitation current, determine the anti-phase compensation current that is opposite in phase to the excitation current;

[0021] The inverse compensation signal is determined based on the inverse compensation current.

[0022] Optionally, the number of non-test energy storage devices is multiple; the step of determining an anti-phase compensation signal opposite to the phase of the excitation current based on the excitation current includes:

[0023] The total compensation current is determined based on the excitation current;

[0024] Based on the total compensation current and the number of non-test energy storage devices, determine the inverse compensation signal for each non-test energy storage device.

[0025] Optionally, the method further includes:

[0026] Within the frequency measurement range, determine the measurement frequency point that has the smallest deviation from the ideal frequency point;

[0027] The amplitude and / or phase of the measured frequency point are optimized to obtain the optimized frequency point;

[0028] The excitation signal is determined based on the optimized frequency point.

[0029] Optionally, determining the measurement frequency point with the smallest deviation from the ideal frequency point within the frequency measurement range includes:

[0030] Determine the total number of ideal frequency points based on the frequency measurement range and frequency display density;

[0031] The ideal frequency point is determined based on the maximum and minimum frequency points corresponding to the frequency measurement range, and the total number of ideal frequency points.

[0032] The measurement frequency point with the smallest deviation from the ideal frequency is selected from the candidate frequency points, and the candidate frequency points are determined based on the sampling frequency;

[0033] And / or, optimize the amplitude and / or phase of the measured frequency point to obtain an optimized frequency point;

[0034] Based on minimizing the crest factor, the amplitude and phase of the measured frequency point are determined to obtain the optimized frequency point;

[0035] And / or, determining the excitation signal based on the optimized frequency point includes:

[0036] The sinusoidal signal is determined based on the optimized frequency point;

[0037] The sinusoidal signals are superimposed to obtain a superimposed signal;

[0038] The superimposed signal is periodically processed to obtain the excitation signal.

[0039] Optionally, the method further includes:

[0040] The impedance of the energy storage device under test is determined based on the response signal of the energy storage device under test to the excitation signal.

[0041] Optionally, the response signal includes a voltage signal and a current signal;

[0042] Determining the impedance of the energy storage device under test based on its response signal to the excitation signal includes:

[0043] The voltage signal and the current signal are combined into a complex signal;

[0044] Determine the spectrum of the composite signal and the spectrum of the corresponding conjugate sequence of the composite signal;

[0045] The spectrum of the current signal and the spectrum of the voltage signal are determined based on the spectrum of the composite signal and the spectrum of the conjugate sequence.

[0046] The impedance of the energy storage device is determined based on the spectrum of the voltage signal and the spectrum of the current signal.

[0047] And / or, the method further includes:

[0048] Obtain the SOC of each energy storage device;

[0049] Based on the SOC of each energy storage device, determine the SOC difference characteristics of each energy storage device;

[0050] Based on the SOC differences of each energy storage device, a balancing characteristic is determined, which is used to balance the SOC of each energy storage device.

[0051] Thirdly, this application provides a microcontroller, comprising:

[0052] Impedance excitation compensation module is used to obtain the inverting compensation signal corresponding to the excitation signal;

[0053] When the excitation signal is applied to the energy storage device under test, the inverting compensation signal is applied to the non-energy storage device under test.

[0054] Optional, also includes:

[0055] At least one of the following: excitation signal calculation module, impedance excitation injection module, compensation calculation module, control unit, impedance spectrum calculation module, data storage module, equalization module, and electrical parameter control module;

[0056] The excitation signal calculation module is used to generate the excitation signal;

[0057] The impedance excitation injection module is connected to the excitation signal calculation module and is used to output the excitation signal;

[0058] The compensation calculation module is connected to the impedance excitation compensation module and is used to generate the inverse compensation signal;

[0059] The impedance spectrum generation module is connected to the energy storage device and is used to determine the impedance of the energy storage device and generate an impedance spectrum.

[0060] The data storage module is connected to the impedance spectrum generation module and is used to record historical operating data;

[0061] The data processing module is connected to the sampling module and is used to preprocess the collected voltage, current and / or temperature data;

[0062] The balancing module is connected to the energy storage device and is used to determine the balancing characteristics based on the SOC difference characteristics of each energy storage device. The balancing characteristics are used to balance the SOC of each energy storage device.

[0063] The electrical parameter control module is connected to the energy storage device and is used to control the electrical parameters of the energy storage device;

[0064] The control unit is switched between the impedance excitation injection module, the impedance excitation compensation module, the electrical parameter control module, or the equalization module. The control unit is also connected to a DC-DC converter.

[0065] Fourthly, embodiments of this application provide a converter, including: a memory and a processor;

[0066] The memory stores computer-executed instructions;

[0067] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0068] Fifthly, embodiments of this application provide a controller, including: a memory and a processor;

[0069] The memory stores computer-executed instructions;

[0070] The processor executes computer execution instructions stored in the memory, causing the processor to perform the second aspect and / or various possible implementations of the second aspect as described above.

[0071] Sixthly, embodiments of this application provide an electrical device including the converter described in the fourth aspect and / or the controller described in the fifth aspect.

[0072] In a seventh aspect, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0073] Eighthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0074] The control method, converter, controller, and electrical equipment provided in this application are used to control energy storage devices, acquire the inverse compensation signal corresponding to the excitation signal, and apply the inverse compensation signal to the energy storage device under test when the excitation signal is applied to the energy storage device not under test. The harmonics caused by the excitation signal and the inverse compensation signal are out of phase and can cancel each other out, thereby compensating for the disturbances and harmonics of the current generated in the branch where the energy storage device is located, weakening or eliminating the influence of disturbances and harmonics, and ensuring the stable output of the DC bus. Attached Figure Description

[0075] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0076] Figure 1 Schematic diagram of the energy storage system provided in this application Figure 1 ;

[0077] Figure 2 Schematic diagram of the energy storage system provided in this application Figure 2;

[0078] Figure 3 Schematic diagram of the energy storage system provided in this application Figure 3 ;

[0079] Figure 4 Flowchart of the control method provided in this application Figure 1 ;

[0080] Figure 5 Flowchart of the control method provided in this application Figure 2 ;

[0081] Figure 6 A schematic diagram of the impedance determination provided in this application Figure 1 ;

[0082] Figure 7 A schematic diagram of the impedance determination provided in this application Figure 2 ;

[0083] Figure 8 This is a schematic diagram of the microcontroller provided in this application;

[0084] Figure 9 This is a schematic diagram of the microcontroller provided in this application;

[0085] Figure 10 The structural diagram of the electrical equipment provided in this application;

[0086] Figure 11 A schematic diagram of the structure of the electronic device provided in this application.

[0087] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0088] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0089] With the rapid development of electric vehicles, energy storage systems, and portable devices, battery management technology has become central to these applications. Traditional battery monitoring methods typically rely on parameters such as voltage, temperature, and current. While these parameters can provide some information about the battery's state, they are often insufficient to provide a comprehensive diagnosis when faced with complex battery degradation mechanisms.

[0090] Furthermore, currently used battery state estimation methods mainly rely on models or neural network techniques. The accuracy of these methods depends on the model used, and their accuracy may decrease as the battery ages, temperature changes, and environmental changes occur. In addition, these methods have high computational complexity, poor real-time performance, and cannot maintain the reliability of estimation results in complex working environments.

[0091] Battery impedance is a parasitic parameter that impedes the flow of current through the battery. When any current is applied to the battery, the impedance causes a voltage drop across its open circuit voltage. Impedance is a frequency-dependent complex number and can be expressed as follows:

[0092]

[0093] Where f is the test frequency, V(f) and I(f) are the peak values ​​(amplitudes) of the AC components of the voltage and current of the battery at frequency f, respectively, and θ(f) = θ v (f)-θ I Z'(f) is the phase angle of the impedance, representing the phase difference between the battery voltage and current; where Z'(f) is the real part of the impedance (corresponding to resistance, horizontal axis), and Z''(f) is the imaginary part of the impedance (corresponding to reactance, vertical axis). This means that the value of the complex impedance changes at different angular frequencies, reflecting the characteristics of the circuit or system at different frequencies. Impedance is usually represented in the Nyquist plane (this plane is usually called the complex plane) by the changes in the real part Z'(f) and the imaginary part Z''(f) of the impedance. The Bode plot (logarithmic amplitude spectrum) of the impedance shows the changes in the impedance magnitude |Z(f)| with frequency and the changes in the phase angle θ(f) with frequency, respectively.

[0094] Electrochemical impedance spectroscopy (EIS) of a battery involves a combined analysis of Nyquist plots and Bode plots. This is because EIS analysis allows the measurement of multiple frequency variation regions caused by different internal electrochemical phenomena within the battery.

[0095] The diffusion region at low frequencies represents the solid-state diffusion effect of lithium ions between the electrodes, which typically causes this region to exhibit a constant slope curve. The charge transfer region (2kHz-3kHz) represents the charge transfer phenomenon on the electrode surface. It typically forms one or more semicircles in the EIS of the Bode plot, which depends primarily on the battery chemistry and temperature at mid-frequency. The ohmic region in the Bode plot represents the area where the impedance intersects the real axis. In the high-frequency region (>10kHz), the inductive region can also be measured, which is caused by the inductance of the battery wires and current collectors.

[0096] Furthermore, the shape of impedance in these regions also varies with temperature, state of charge, and health. Corrosion on the electrolyte and electrodes, lithium deposition, and especially the formation of a solid electrolyte interface layer, increase impedance as the battery ages. Increased temperature accelerates chemical reactions within the battery, thereby reducing impedance. However, high temperatures also accelerate battery aging and increase impedance. Impedance also varies as a function of state of charge, particularly at extremely low and extremely high state of charge values.

[0097] Therefore, battery EIS measurement technology is a non-invasive measurement technique widely used for battery state estimation and fault diagnosis. As a direct measurement method, it does not rely on complex models, and the obtained EIS information can more accurately reflect the true state of the battery. By capturing the response of various frequencies within the battery, it provides comprehensive information about the battery's health status and can maintain stable and accurate state estimation under various operating conditions.

[0098] The basic principle of existing battery impedance spectrum testing is to apply small-amplitude AC excitation current signals (such as sine waves) of different frequencies to the energy storage battery system under test to activate the battery system to generate a voltage response, and to calculate the impedance variation within a certain frequency range by measuring the voltage and current of the system under test.

[0099] Existing measurement techniques employ successive output of excitation signals at different frequencies to cover the frequency range defined by the pseudo-impedance measurement, i.e., impedance spectroscopy (EIS). Impedance spectroscopy results display the battery's impedance values ​​at different frequencies, including ohmic resistance (related to the conductivity of the electrolyte and electrode materials), charge transfer impedance (related to the electrochemical reaction rate at the electrode-electrolyte interface), and diffusion impedance (related to the diffusion behavior of lithium ions in the electrode materials). Impedance spectroscopy results can aid in analyzing the internal physical and chemical processes of the battery, such as energy storage system health assessment, state assessment, and consistency assessment.

[0100] Through research, the inventors discovered that existing online impedance spectrum measurement circuits cause high-frequency current and voltage responses in energy storage systems, resulting in harmonics and disturbances in the branch where the measured energy storage device is located. This leads to harmonics and disturbances in the DC bus of the energy storage system, affecting the stable output of the DC bus.

[0101] Therefore, this application proposes a control method for controlling energy storage devices by applying an inverse compensation signal corresponding to the excitation signal to a non-test energy storage device not in test mode. When the excitation signal is applied to the first energy storage device, the excitation current applied to the DC bus by the measurement branch may generate a first harmonic on the DC bus; when the inverse compensation signal is applied to the branch where the non-test energy storage device is located (referred to as the compensation branch), the current applied to the DC bus by the compensation branch may also generate a second harmonic on the DC bus. Since the excitation signal and the inverse compensation signal are out of phase, the first and second harmonics are in opposite directions and can cancel each other out. This can compensate for the disturbance and harmonics of the current generated in the branch where the energy storage device is located, weaken or eliminate the influence of disturbance and harmonics, and ensure the stable output of the DC bus.

[0102] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0103] First, let me describe the energy storage system involved in this application:

[0104] Figure 1 A schematic diagram of the structure of an energy storage system provided in this application is shown, such as... Figure 1 As shown, this parallel energy storage system connects multiple energy storage devices in parallel on the DC bus, and each energy storage device is connected to the DC bus through its own converter.

[0105] The DC bus serves as the voltage collection point for the energy storage system, carrying the electrical energy output of all energy storage devices. Energy storage devices can include individual battery cells or battery clusters, with each cluster consisting of multiple individual cells. These devices provide basic energy storage functions and are modular, allowing them to operate independently.

[0106] To ensure electrical compatibility with the DC bus, each energy storage device is connected to an independent power electronic converter, which is responsible for regulating the charging and discharging current and voltage of the energy storage device.

[0107] like Figure 1As shown, the energy storage system mainly consists of n energy storage devices connected in parallel. Each energy storage device has a bidirectional DC-DC converter, meaning each energy storage device is connected to an independent bidirectional DC-DC converter. Furthermore, the n bidirectional DC-DC converters are connected in parallel to the same DC bus, where n ≥ 1. Each of these n energy storage devices includes a battery cluster, which is formed by connecting m individual battery cells in series, where m ≥ 1.

[0108] For example, the battery material can be any material, including lithium batteries, sodium batteries, etc. The bidirectional DC-DC converter controls the energy flow by adjusting the switching transistors to achieve the charging and discharging function of the battery cluster. There are many types of bidirectional DC-DC converters to choose from, such as bidirectional Buck-Boost converters and bidirectional Cuk converters.

[0109] Figure 2 A schematic diagram of another energy storage system provided in this application is shown, such as... Figure 2 As shown, each parallel system branch can be connected in series with multiple energy storage devices, and the number of energy storage devices is q≥1, where each branch is a converter.

[0110] Figure 3 A schematic diagram of another energy storage system provided in this application is shown, such as... Figure 3 As shown, in addition to the series-parallel energy storage structure with a bidirectional DC-DC converter, an energy storage system without a bidirectional DC-DC converter is also connected in parallel. For this hybrid system, the impedance detection proposed in this application can also be used.

[0111] Figure 4 Flowchart of the control method provided in this application Figure 1 ,like Figure 4 As shown, with the converter as the executing entity, the control method provided in this application embodiment is used to control an energy storage device, including:

[0112] S101. Obtain the inverse compensation signal corresponding to the excitation signal.

[0113] The excitation signal is used to entice the device under test (DUT) to generate a response signal used to determine its impedance. The DUT refers to the energy storage device whose impedance needs to be measured. The inverse compensation signal is a signal with the opposite phase to the excitation signal.

[0114] S102. When applying the excitation signal to the energy storage device under test, apply the inverting compensation signal to the non-energy storage device under test.

[0115] For example, when an excitation signal is applied to the energy storage device under test (DUT), the current acting on the DC bus in the measurement branch where the DUT is located is the excitation current; when an inverse compensation signal is applied to the DUT, the current acting on the DC bus in the compensation branch where the non-DUT is located is the compensation current. The excitation current and the compensation current are out of phase.

[0116] In this embodiment, an inverse compensation signal with the opposite phase to the excitation signal is applied to a non-test energy storage device that is not in test mode. When the excitation signal is applied to the test energy storage device, the excitation current applied to the DC bus by the measurement branch may generate a first harmonic on the DC bus; when the inverse compensation signal is applied to a non-test energy storage device, the current applied to the DC bus by the branch where the non-test energy storage device is located (referred to as the compensation branch) may also generate a second harmonic on the DC bus. Since the excitation signal and the inverse compensation signal are out of phase, the first and second harmonics are in opposite directions and can cancel each other out, thereby reducing harmonics and interference on the DC bus.

[0117] The compensation branch can be understood as being controlled to generate a compensation current that is out of phase with the detected total harmonic disturbance. Out of phase means that for two sinusoidal signals of the same frequency, when one signal reaches its peak, the other just reaches its estimated value, with a phase difference of 180°.

[0118] It should be noted that energy storage devices contain internal impedance (such as ohmic resistors and polarization resistors). When an excitation signal is applied to the energy storage device, the presence of impedance will cause a change in voltage or current; this change is the response signal.

[0119] Therefore, when an excitation signal is applied to the energy storage device under test, the device under test can be controlled to generate a response signal based on its impedance, and the response signal can be used to determine the impedance of the energy storage device under test.

[0120] For example, the excitation signal can be a voltage signal or a current signal. When the excitation signal is a voltage signal, a small-amplitude AC voltage (e.g., a sinusoidal AC voltage) is directly applied to the energy storage device, and the response current is measured simultaneously. When the excitation signal is a current signal, a constant-amplitude AC current signal is applied to the energy storage device, and the response voltage across the energy storage device is measured.

[0121] For example, to superimpose an excitation signal onto the charging and discharging current of an energy storage device, the main circuit of a DC-DC converter, such as a multi-phase boost circuit connected in parallel, can be used. A digital controller can then use sinusoidal pulse width modulation (SPWM) to superimpose an AC sinusoidal wave disturbance of a set frequency and amplitude onto the output DC current. Specifically, based on the principle of disturbance signal generation, an AC signal of a set frequency and amplitude is superimposed onto the original control output pulse width signal, thereby changing the width of the switching pulse and thus superimposing an AC sinusoidal wave disturbance onto the output DC current, achieving the application of the excitation signal.

[0122] For example, this can be achieved by superimposing the PWM gate drive signal of a synchronous switching transistor (such as a MOSFET). A small-amplitude sinusoidal AC signal is superimposed on the PWM drive signal, thereby controlling the switching transistor's on and off states. This ensures that during the DC-DC conversion process, the energy storage device actually receives a composite signal containing both DC and AC excitation signals.

[0123] For example, an excitation signal can be applied to the energy storage device under test during charging or discharging.

[0124] For example, there can be multiple energy storage devices under test (ESDs). An excitation signal can be applied to each ESD to achieve simultaneous impedance detection of multiple devices. Furthermore, when multiple ESDs are measured simultaneously, the remaining non-ESD devices can provide reverse compensation.

[0125] Optionally, an excitation signal is acquired and applied to the energy storage device under test when the measurement conditions are met, to prevent invalid measurements and improve impedance detection efficiency.

[0126] For example, it is determined whether the ambient temperature, energy storage device temperature, and the energy storage device's State of Charge (SOC) meet the measurement conditions. For instance, the SOC may change during the measurement process; therefore, the measurement is set to 10% ≤ SOC ≤ 90% to avoid overcharging and over-discharging; the energy storage device temperature is ≤ 30 degrees Celsius, and the ambient humidity is ≤ 50%. Accordingly, when the ambient temperature, energy storage device temperature, and energy storage device SOC meet the corresponding conditions, an excitation signal is applied to the energy storage device under test.

[0127] For example, based on testing requirements, the energy storage devices in a parallel energy storage system can be divided into energy storage devices under test and non-energy storage devices under test.

[0128] Optionally, in addition to using parallel multiplexing to simultaneously measure the impedance of multiple energy storage devices, the impedance of multiple energy storage devices can also be measured sequentially. Specifically, the excitation signal corresponding to each energy storage device under test is applied to each energy storage device under test sequentially, and the impedance of each energy storage device under test is measured sequentially to reduce the performance requirements of the processor.

[0129] It should be noted that parallel multi-channel measurement can significantly improve measurement efficiency. Under the control of a microcontroller, it allows for parallel measurement of the EIS of each energy storage device in a parallel system, meaning that the excitation signals of the designed L branches are simultaneously controlled. The number L of individual energy storage devices performing EIS measurements simultaneously must meet the following requirement: n–L ≥ 1. This inequality indicates that at least one energy storage device branch must operate in reverse compensation mode to compensate for the current harmonics generated during the measurement of the L energy storage devices. Alternatively, when L energy storage devices are used for EIS measurement, the other n–L energy storage devices need to operate in reverse compensation mode.

[0130] It should be noted that when performing parallel EIS measurements, the increased number of EIS computing units places higher demands on the real-time computing speed of the microcontroller.

[0131] Therefore, in addition to the parallel system measurement method, it can also be designed as a successive measurement, which means measuring L batteries in multiple steps.

[0132] Specifically, to reduce the performance requirements of the test microprocessor, the EIS of each unit in the parallel system can be measured sequentially under the control of the microcontroller. The measurement sequence can be modified to any order.

[0133] Optionally, the excitation signal corresponding to each energy storage device under test is applied to each device sequentially according to a preset time interval. That is, the measurement time between any two adjacent branches must satisfy t being less than a certain time interval to avoid excessive changes in the SOC of the energy storage device due to excessively long working time.

[0134] For example, if the SOC change threshold is 0.5%, then the stagnation time (i.e., the preset time interval) is limited as follows:

[0135]

[0136] Among them, C i This represents the energy storage capacity of the i-th branch. Furthermore, during the measurement process of the i-th branch, one of the remaining branches in n–L is selected for reverse compensation mode.

[0137] Optionally, the successive measurement compensation design measures only one battery branch at a time. An adjacent branch can be selected as the compensation branch, that is, the inverted compensation signal is applied to the branch of the non-tested energy storage device that is adjacent to the energy storage device under test. This results in strong local stability, simplified control strategy, and improved measurement accuracy.

[0138] For example, when an energy storage device branch is subjected to EIS measurement, an adjacent energy storage device branch is selected for reverse compensation. The adjacent branch generates an inverse compensation signal in real time based on the excitation current of the measured branch to cancel out its high-frequency current fluctuations.

[0139] The compensation process is synchronized with the measurement time of the measurement branch to ensure that the system output remains stable throughout the entire measurement cycle. For the i-th branch, either branch i-1 or i+1 is selected for compensation, and the operating current of that branch is also added. After the EIS measurement of the battery cluster in the i-th branch is completed, the next branch takes over the measurement, and the new adjacent branch continues to compensate.

[0140] The control method provided in this application utilizes an anti-phase compensation signal that is opposite in phase to the excitation current applied to a non-test energy storage device to cancel the harmonics caused by the excitation current, thereby reducing harmonics and interference on the DC bus.

[0141] This application also provides a control method for controlling an energy storage device, wherein a controller (also referred to as a main controller or microcontroller) is the executing entity, and the method includes:

[0142] S20. Determine the inverse compensation signal corresponding to the excitation signal. The inverse compensation signal is used to apply to the non-tested energy storage device when the excitation signal is applied to the energy storage device under test.

[0143] Among them, non-tested energy storage devices refer to energy storage devices whose impedance does not need to be measured at present. Non-tested energy storage devices are connected in parallel with tested energy storage devices.

[0144] Optionally, when applying the excitation signal to the energy storage device under test (EDT), the corresponding excitation current is determined; based on the excitation current, an anti-phase compensation current with the opposite phase to the excitation current is determined; based on the anti-phase compensation current, an anti-phase compensation signal is determined and applied to the non-EDT energy storage device. The online EIS measurement mechanism results in high-frequency current and voltage responses in the parallel energy storage system containing the EDT, generating harmonics and disturbances at the DC-DC conversion interface of the measurement branch. Consequently, harmonics and disturbances are generated on the DC bus of the entire parallel energy storage system. To maintain the output stability of the DC bus, it is necessary to compensate for the disturbances and harmonics of the current generated in the measurement branch to weaken or eliminate their impact.

[0145] For example, the inverting compensation current is set as the setpoint of the current controller, and the actual current is used as the feedback value. Based on the error between the setpoint and the feedback value, an adjustment is made and a PWM signal is generated, thereby obtaining the inverting compensation signal. Furthermore, a mapping relationship between the inverting compensation signal (PWM signal) and the inverting compensation current can be established, making it easier to determine the inverting compensation signal based on the mapping relationship.

[0146] Optionally, a total compensation current is determined based on the excitation current. The total compensation current and the instantaneous current of the excitation current are equal in magnitude but opposite in direction at any given time. Then, based on the total compensation current and the number of non-DUT devices, an anti-phase compensation current is determined for each non-DUT device. Distributing the total compensation current to these non-DUT devices helps to distribute the load, reduce SOC fluctuations, and accelerate system consistency recovery. Accordingly, an anti-phase compensation signal for each non-DUT device can be determined based on its anti-phase compensation current.

[0147] For example, when the total compensation current is close to the excitation current, the harmonic current on the DC bus can be made close to zero. For instance, without considering the operating current, if an excitation signal is applied to the energy storage device under test, such that the excitation current acting on the DC bus by the measurement branch is I... oi Accordingly, the total compensation current that the compensation branch needs to apply to the DC bus can be determined to be -I. oi This allows the harmonic current on the DC bus to be controlled to be close to zero.

[0148] It should be noted that when an excitation signal is applied to the energy storage device under test, the total current of the device is the superposition of the basic operating current and the current corresponding to the excitation signal (referred to as the excitation current). These two currents together constitute the DC and AC components of the total current. Therefore, the current acting on the DC bus of the branch containing the energy storage device under test is the superposition of the basic operating current and the total excitation current. Accordingly, the excitation current at the DC bus can be determined based on the AC component at the DC bus.

[0149] It is understandable that if there is only one energy storage device under test, the excitation current is the AC component of that energy storage device acting on the DC bus; if there are multiple energy storage devices under test, the excitation current is the sum of the AC components of each energy storage device acting on the DC bus.

[0150] If there is only one non-test energy storage device, the total compensation current is the AC component of that energy storage device acting on the DC bus; if there are multiple non-test energy storage devices, the excitation current is the sum of the AC components of each energy storage device acting on the DC bus.

[0151] For example, the weight of each non-test energy storage device can be determined based on its characteristics (SOC, etc.), and the compensation current of each non-test energy storage device can be determined based on the weight, the total compensation current, and the number of non-test energy storage devices.

[0152] For example, the total compensation current can be evenly distributed among multiple non-test energy storage devices. The reverse-phase compensation current of each non-test energy storage device is the ratio between the total compensation current and the number of non-test energy storage devices, ensuring that each compensation branch undertakes an equal compensation task.

[0153] For example, L measurement branches perform EIS measurements, while the remaining n–L compensation branches enter reverse compensation mode. Considering the transmission efficiency η of the DC-DC converter in each branch... i The charging process η i <1, discharge process η i >1, therefore satisfying

[0154]

[0155] Among them, V Bi This refers to the voltage on the i-th measuring branch; I Bi This refers to the current in the i-th measuring branch; V oi This refers to the voltage applied to the DC bus by the i-th measurement branch; I oi It refers to the current (i.e., excitation current) that the i-th measuring branch acts on the DC bus.

[0156] Accordingly, the total compensation current of n–L compensation branches can be determined based on the excitation current, and the compensation current I of each of the n–L compensation branches can be determined based on the total compensation current. oi .

[0157] For example, each compensation branch injects an appropriate amount of reverse current according to its own current state, thereby offsetting the disturbances caused by the measurement process and maintaining the overall output stability of the system.

[0158] Figure 5 A flowchart illustrating the control method provided in this application is shown below. Figure 5 As shown, based on the above embodiments, the control method further includes:

[0159] S201. Within the frequency measurement range, determine the measurement frequency point with the smallest deviation from the ideal frequency point.

[0160] For example, the minimum EIS measurement frequency f is determined based on the EIS frequency measurement range requirements. min and maximum value f maxThe unit is Hz and must be an integer. If no measurement range is provided, the default range is 0.1Hz to 1000Hz. In EIS testing, the instrument applies multiple AC signals of different frequencies to the system under test (energy storage device). The frequency range corresponding to the multiple AC signals of different frequencies is the EIS frequency measurement range.

[0161] Since the frequency axis spacing between the frequency windows of the EIS Bode plot of energy storage devices is logarithmically distributed, it is necessary to set the frequency display density parameter ρ. show This parameter, set as a requirement, is in units of 1, representing the display ρ value set within each tenfold frequency variation range. show The frequency points include the maximum frequency point every ten times the frequency. For example, 6-10 frequency points are set within every ten-fold frequency variation range to obtain the ideal frequency points.

[0162] However, the ideal frequency point may not meet the actual operating constraints of the hardware, and direct use may lead to test failure, data distortion, or inability to acquire data. For example, it may not meet the requirement of being an integer multiple of the sampling frequency. The ideal frequency point is a theoretical value generated according to a logarithmic distribution and is often a non-integer (such as 3.16Hz, 31.6Hz); it may also exceed the frequency output accuracy range of the hardware.

[0163] Therefore, it is necessary to determine the measurement frequency point with the smallest deviation from the ideal frequency point. Under the premise that the hardware constraints cannot be broken, the theoretical optimality of EIS testing should be preserved to the maximum extent, so that the test can be successfully implemented and the data quality can meet the analysis requirements.

[0164] For example, the measurement frequency point is related to the EIS measurement resolution. If no specific measurement frequency point is provided for EIS measurement, the measurement point is set by an optimization scheme. This design optimization method ensures that the EIS calculation results are distributed along the frequency logarithmic axis of the electrochemical EIS.

[0165] Optionally, the density ρ can be displayed based on the frequency measurement range and frequency. show Determine the total number N of ideal frequency points. show According to the maximum frequency point f within the frequency measurement range max and minimum frequency point f min and the total number N of ideal frequency points show Determine the ideal frequency point; at the candidate frequency point f candidate The candidate frequency point is selected based on the sampling frequency and is the measurement frequency point with the smallest deviation from the ideal frequency.

[0166] For example, the frequency measurement range is from 0.1Hz to 1000Hz, and the density is 10 points per decade. The number of decade harmonics is log10(1000) - log10(0.1) = 4, so N show ≈4×10=40 points.

[0167] For example, in log10(f min ) to log10(f min N is evenly inserted between ) show Take one value, then raise it to the power of 10 to obtain the ideal frequency point f. ideal Among them, f ideal =10^(log10(f min )+(i-1)×(log10(f max )-log10(f min )) / (N show -1)). This yields f ideal It is strictly uniformly distributed on logarithmic coordinates.

[0168] For example, during the measurement process, each measurement frequency point is limited by hardware to be an integer multiple of the sampling frequency to avoid spectral leakage and calculation errors in EIS measurements. Therefore, the sampling frequency is set to the highest frequency point f in the frequency bandwidth. max M times, where M is the frequency division number, denoted as f sample =f max / M. Therefore, the selected measurement frequency point must be the sampling frequency f. sample The values ​​must be integer multiples of the specified frequencies to ensure that data is accurately sampled at the measurement frequency points during the measurement process.

[0169] For example, candidate frequency points f are determined based on the sampling frequency. candidate All candidate frequency points are integer multiples of the sampling frequency, f candidate =k show ×f sample Among them, k show It is a positive integer, and its range extends from the point of maximum frequency f. max and minimum frequency point f min Decision, k show_min =ceil(f min / f sample ), k show_max =floor(f max / f sample ).

[0170] The following minimization problem is used to obtain the measurement frequency points, where f is the i-th measurement frequency point within the frequency measurement range. i The following optimization problem can be solved:

[0171]

[0172] Where, k show N is a positive integer. showThe optimization problem is solved to obtain i, where i takes the values ​​{1,...,N}. show};f i,target It is the ideal measurement point for the i-th frequency measurement, from low frequency to high frequency, typically f 1,target =f min To ensure that ideal measurement points are evenly distributed within the frequency measurement range, various methods exist for solving the optimization problem, such as stochastic optimization and genetic algorithms.

[0173] S202. Optimize the amplitude and / or phase of the measured frequency point to obtain the optimized frequency point.

[0174] In this embodiment, optimizing each measurement frequency point can improve the signal-to-noise ratio of the excitation signal, while also improving transmission efficiency, avoiding frequency leakage, and reducing impedance measurement errors.

[0175] Optionally, by minimizing the crest factor, the amplitude and phase at the measurement frequency point are determined to obtain the optimized frequency point. The values ​​of the remaining parameters, namely the amplitude and phase parameters, are then obtained through a crest factor optimization algorithm. Crest factor C f Defined as the ratio of the peak value to the root mean square (RMS) of the signal within one period, the optimization algorithm minimizes the difference between the peak and RMS values, resulting in a lower crest factor. A lower crest factor ensures that the energy of the synthesized excitation signal is evenly distributed across all frequencies, improving the signal-to-noise ratio and directly enhancing the accuracy of EIS measurements.

[0176] The formula for calculating the crest factor is as follows:

[0177]

[0178] Where T is the period of the synthesized multi-frequency sinusoidal excitation signal, and the measurement period T is determined based on the minimum measurement frequency f. min Determined, T = 1 / f min C f The lower the value, the more uniform the signal distribution, the smaller the peak value, and the fewer the pulses; C f The higher the value, the more peak values ​​there are, and the more significant the noise.

[0179] By definition, a sinusoidal current excitation signal x(t) can be expressed as the sum of multiple sinusoidal current signals with different parameters, as shown in the following expression:

[0180]

[0181] Among them, A i f is the amplitude of the i-th sine wave. i It is the frequency of the i-th sine wave, φ i It is the phase of the i-th sine wave, t is time, and N is the phase of the i-th sine wave. show It represents the number of sine waves.

[0182] For example, an optimization algorithm is used to optimize the phase of each frequency component in a multi-sinusoidal signal to reduce C. f The value and optimization problem are as follows:

[0183]

[0184] The optimization problem is subject to the following constraints:

[0185]

[0186] Among them, A min For the minimum amplitude, A max X represents the maximum amplitude of a single signal. max The maximum amplitude of the superimposed signal is limited by the safety range of the bidirectional DC-DC converter. A can be obtained after solving the optimization problem. i and The optimization problem can be solved using common optimization algorithms (such as genetic algorithms, particle swarm optimization, stochastic optimization, etc.) to determine the amplitude and phase of the sinusoidal signal. To simplify the calculation process, the amplitude of the sinusoidal signal at each frequency in the multi-frequency excitation signal x can be taken to have the same value.

[0187] S203. Determine the excitation signal based on the optimized frequency point.

[0188] Optionally, a sinusoidal signal is generated based on the amplitude and phase of the optimized frequency point, and the sinusoidal signals are superimposed to obtain the excitation signal.

[0189] For example, a sinusoidal signal is generated based on the amplitude and phase of the optimized frequency point; the sinusoidal signals are superimposed to obtain the excitation signal.

[0190] During normal operation of a parallel energy storage system, an excitation current can be injected into the battery under test by modulating the charging or discharging current. Based on this, after designing and optimizing the measurement frequency band, phase distribution, and amplitude of the multi-sine modulation wave, the operating current I supplied to the system by the branch containing the energy storage device is superimposed. wi and the compensation current I used to adjust the measuring current to a stable current. pi The final multi-sinusoidal modulation excitation current of the energy storage device is:

[0191]

[0192] Among them, I si I represents the total current of the energy storage device under test in the design. wi I represents the current operating current set for the branch of the parallel energy storage system at the current moment. wi A value greater than 0 indicates charging, a value less than 0 indicates discharging, and a value equal to 0 indicates resting; I piThis is the bias current, used to compensate I. wi This ensures that its operating current is within a reasonable range. EIS measurements are typically more accurate under static conditions, therefore I... pi Set to -I wi This makes the reference current 0A:

[0193]

[0194] For example, a sinusoidal signal is determined based on an optimized frequency point. Since there are multiple optimized frequency points, each with a corresponding sinusoidal signal, the sinusoidal signals can be superimposed to obtain a superimposed signal. The superimposed signal is then periodically processed to obtain an excitation signal.

[0195] During the process of injecting the excitation signal into the battery cluster under test (DUT), the DUT needs to meet certain stability requirements. Therefore, the generated superimposed signal is repeated K times, that is, the duration of the superimposed signal with the original measurement period T is increased by a factor of K, resulting in a total measurement time of KT, for example, K is set to 5. Before the stabilization measurement, the designed current excitation is continuously injected into the DUT, but no measurement or calculation is performed. Only after the stabilization period can the sampled voltage of the DUT's batteries be used to calculate the EIS of multiple battery clusters and cells, avoiding high-order harmonics generated during operating condition switching and reducing measurement accuracy.

[0196] In this embodiment, by evenly distributing the frequency points displayed in the impedance spectrum and optimizing the frequency distribution in the Bode plot (logarithmic amplitude spectrum), key features of the impedance spectrum (such as impedance changes in the low and high frequency regions) can be more clearly displayed with a limited number of frequency points. Furthermore, optimization yields a better excitation signal-to-noise ratio, suppressing noise and improving the display resolution, observation accuracy, and computational efficiency of the impedance results. Optimizing the multi-frequency sinusoidal excitation signal effectively improves injection efficiency and significantly increases the overall measurement speed.

[0197] This application also provides a control method for controlling an energy storage device. Based on the above embodiments, the control method provided in this application further includes:

[0198] S30. Determine the impedance of the energy storage device under test based on its response to the excitation signal.

[0199] Optionally, the voltage and current signals are combined into a complex signal; the spectrum of the composite signal and the spectrum of its corresponding conjugate sequence are determined; based on the spectrum of the composite signal and the spectrum of its conjugate sequence, the spectra of the current and voltage signals are determined; and based on the spectra of the voltage and current signals, the impedance of the energy storage device is determined. This is achieved by combining the current and voltage signals into a complex sequence s(t). iThe spectrum S[k] of the complex signal is obtained through a single FFT operation, and the conjugate symmetry property of the complex signal is utilized to simultaneously obtain the complex signal s(t). i ) and its conjugate sequence The spectral information of the signal s(t). i ) conjugate The spectrum can be obtained through the formula The derivation avoids performing a second FFT calculation on the conjugate sequence, thus reducing the computational cost by nearly half.

[0200] For example, based on the measurement period T and sampling frequency f sample Determine the total number of points to use, N=f sample ×T, and satisfying N is a power of 2, simultaneously obtaining the sampled current sequence and voltage sequence {V(t1),...,V(t)}. N {I(t1),...,I(t)} and {I(t)} N )}, where V(t) i ) and I(t i ) represents the complex signal corresponding to the i-th time point, which consists of current and voltage.

[0201] For example, such as Figure 6 As shown, methods for determining impedance may include:

[0202] S301, Complex Signal Construction:

[0203] Current I(t) i ) and voltage V(t) i The signal sequence is combined to form a new complex signal s(t). i )=V(t i )+jI(t i ), where j is the imaginary unit.

[0204] S302, FFT (Fast Fourier Transform) calculation:

[0205] For complex signals s(t) i Perform an FFT operation to obtain its spectrum S[k], where k is the index of the discrete frequency point, k=0,1,2,...,N / 2-1. Based on the principle of FFT calculation, it is recursively decomposed into two N / 2 subsequences. Continue the recursive decomposition until the length of the decomposed subsequence is 1. Return these values ​​directly. Then, during the return process, use the rotation factor to merge them through a butterfly operation to obtain the spectrum result S[k] calculated by FFT.

[0206] S303, Conjugate spectrum calculation:

[0207] Based on conjugate symmetry, we can deduce the following from the formula:

[0208]

[0209] That is, using S[k] and The conjugate symmetry relation can be directly obtained from S[k] to obtain the conjugate sequence. The spectral information of the sequence s(t). That is, the spectral information of the sequence s(t). i conjugate sequence The spectrum can be obtained by converting s(t) i The spectrum S[k] is obtained by taking the conjugate of the spectrum. Reverse order to obtain This utilizes the conjugate symmetry in the Fourier transform to shorten the spectrum calculation time.

[0210] S304, Spectrum and Impedance Calculation:

[0211] By using FFT and conjugate symmetry, the current I(t) can be obtained simultaneously. i ) and voltage V(t) i The spectrum of the signal:

[0212]

[0213] The above formula can reduce the computational burden by nearly half, eliminating the need for a second FFT calculation on the conjugate signal, thereby improving the computational efficiency of FFT.

[0214] The impedance Z and the displayed impedance result Zshow (the data points displayed in the EIS measurement results obtained in step (2)) at each sampling frequency point can be obtained from the above calculations:

[0215]

[0216] For example, the spectrum can also be calculated using current and voltage separately, and the EIS result can then be calculated. Figure 7 As shown, the acquired current and voltage sequences are transformed into their spectra through time-domain / frequency-domain conversion. The Fourier Transform (FT) converts the signal from the original time domain to the frequency domain, decomposing any continuously measured signal into sinusoidal signals of different frequencies and obtaining the amplitude and phase angle of these sinusoidal signals, i.e., the spectral information. Microprocessors can only process discrete, finite-length data. Therefore, the Discrete Fourier Transform (DFT), used to represent and analyze discrete time-domain signals, is widely used. The sampled finite-length discrete voltage signal V(t) is shown. i ) and current signal The DFT is defined as follows:

[0217]

[0218] Divide the response voltage at a specific frequency by the current to obtain the impedance at that frequency.

[0219] In addition to the DFT, the Fourier transform can also be achieved using faster computational methods such as the Fast Fourier Transform (FFT), Short-Time Fourier Transform, and Wavelet Transform.

[0220] Optionally, after completing the EIS measurement, since the total measurement time is (K+1)T and the operating current of each branch is inconsistent during the measurement process, the longer the measurement process, the more significant the inconsistency in the SOC of the battery clusters in each battery branch becomes, thus affecting the subsequent operational stability of the energy storage system. Therefore, after determining the impedance, the SOC of each energy storage device can be equalized. Through the SOC state recovery mechanism, each branch of the energy storage system is restored to the consistent SOC state before the measurement, and the current / power balance of each branch is maintained to ensure the stable output performance of the parallel system. This mechanism effectively reduces the inconsistency problem caused by the difference in operating conditions between branches, reduces the impact of impedance measurement on the overall performance of the energy storage system, and improves the measurement accuracy.

[0221] For example, SOC difference assessment: The microcontroller obtains the SOC information of each battery branch to determine the SOC difference between the branches. If the difference exceeds a preset threshold, an equalization mechanism is activated.

[0222] Optionally, the SOC of each energy storage device is obtained; based on the SOC of each energy storage device, the SOC difference characteristics of each energy storage device are determined. The SOC difference characteristics are used to characterize the SOC difference between energy storage devices, and may include, for example, the SOC difference between any two energy storage devices. Then, based on the SOC difference characteristics of each energy storage device, the balancing characteristics are determined. The balancing characteristics are used to balance the SOC of each energy storage device, and may include, for example, an SOC balancing value.

[0223] For example, the equalization characteristics can be sent to the converter, which then performs SOC equalization adjustment. For instance, the converter's corresponding sub-controller might perform a small-current discharge operation on branches with a high battery SOC and a small-current charging operation on branches with a low SOC. The adjustment process is executed through a bidirectional DC-DC converter, ensuring that the SOC of each battery branch gradually returns to a consistent level.

[0224] For example, after SOC equalization is completed, the system continues to maintain stable operation of the overall system by controlling the power output equalization and current equalization of each branch. The function switching process is as follows: Figure 8 As shown in the diagram. At this point, the microcontroller continuously monitors the power and current of each branch to ensure dynamic current balance while maintaining consistent output power, preventing new imbalances caused by load changes. This process continues until the system reaches a stable state.

[0225] It should be noted that the online impedance measurement system adopts a conventional parallel module circuit structure, without introducing additional disturbance (excitation) circuits or additional measurement circuits. Therefore, the system and measurement method have the advantages of simplicity, low cost, and strong scalability. The impedance detection method of this application is suitable for online measurement of energy storage systems with bidirectional DC-DC converters during operation. It is applicable not only to large battery energy storage systems but also to online impedance spectrum measurement of small battery packs.

[0226] This application also provides a microcontroller, such as Figure 8 and Figure 9 As shown, the microcontroller 10 provided in this application includes:

[0227] Impedance excitation compensation module 102 is used to acquire the inverting compensation signal corresponding to the excitation signal;

[0228] When the excitation signal is applied to the energy storage device under test, the inverting compensation signal is applied to the non-energy storage device under test.

[0229] Optionally, the microcontroller 10 may also include at least one of the following: an excitation signal calculation module 104, an impedance excitation injection module 101, a compensation calculation module 105, a control unit 50, an impedance spectrum calculation module 107, a data storage module 108, an equalization module 106, and an electrical parameter control module 105.

[0230] The excitation signal calculation module 104 is used to generate an excitation signal; the impedance excitation injection module 101 is connected to the excitation signal calculation module 104 and is used to output the excitation signal; the compensation calculation module 103 is connected to the impedance excitation compensation module 102 and is used to generate an inverse compensation signal; the impedance spectrum generation module 107 is connected to the energy storage device 20 and is used to determine the impedance of the energy storage device and generate an impedance spectrum; the data storage module 108 is connected to the impedance spectrum generation module 107 and is used to record historical operating data; the data processing module is connected to the sampling module and is used to preprocess the collected voltage, current and / or temperature data; the equalization module 106 is connected to the energy storage device 20 and is used to equalize the SOC of each energy storage device; the electrical parameter control module 105 is connected to the energy storage device 20 and is used to control the electrical parameters of the energy storage device; the control unit 50 switches between the impedance excitation injection module 101, the impedance excitation compensation module 102, the electrical parameter control module 105 or the equalization module 106, and the control unit 50 is also connected to the DC-DC converter 30.

[0231] For example, such as Figure 9 and Figure 10As shown, the parallel energy storage system sampling and control architecture provided in this application is based on the aforementioned parallel energy storage system, integrating sensors (current sensors and voltage sensors), a sub-controller 40, and a microcontroller 10, realizing rapid online EIS measurement functionality. Each energy storage device 20 corresponds to a voltage sensor, which collects the voltage of the energy storage device, totaling... Each energy storage device 20 also corresponds to a current sensor to collect the current of the energy storage unit, for a total of n. The power end of the energy storage device is connected to a bidirectional DC-DC converter 30, which is connected to the DC bus.

[0232] Since the battery impedance spectroscopy (EIS) measurement method calculates EIS results based on the acquired current and voltage signals of the energy storage device, and needs to consider the output of the parallel system sub-modules during the measurement process, it is necessary to set the correct sensor locations. Specifically, each battery cell under test (EIS) needs to be connected to a voltage sensor and a current sensor, and the voltage sensor is connected to the ADC (Analog-to-Digital Converter) port of the sub-controller. The connection method for these sensors is as follows: the voltage and current signals of the battery cell are connected to the ADC port of the sub-controller (microcontroller) through the sensor; the measured voltage and current signals at the junction of the bidirectional DC-DC converter device and the DC bus are also connected to the ADC port of the sub-controller through the sensor.

[0233] In this architecture, both the microcontroller and the sub-controllers are control units that implement the control logic for the EIS measurement process. The sub-controllers are responsible for the system stability and data processing of their respective parallel branches, including acquiring voltage and current signals for their branch, performing preliminary data filtering and processing, executing local control strategies, and ensuring the stable operation of their branch. The microcontroller is responsible for the overall system coordination and control, including receiving impedance data and operating status information uploaded by each sub-controller, performing comprehensive analysis, formulating a global control strategy, and issuing control commands to each sub-controller; additionally, the microcontroller completes the EIS result calculation and output.

[0234] The microcontroller's communication port is connected to the communication port of the bidirectional DC-DC converter, with communication methods including CAN and fiber optics. The system establishes a reliable data communication network through stable communication methods, ensuring information exchange between sensors, converters, sub-controllers, and the microcontroller, thus providing a foundation for collaborative EIS testing of the system.

[0235] The measurement algorithm solution provided in this application enables rapid EIS measurement of battery cells in parallel systems based on hardware. The entire measurement logic algorithm is set in a microcontroller, including task instructions allocated to each sub-controller, measurement storage, and communication functions. The sub-controllers are used to cooperate with the microcontroller instructions to implement functions, such as... Figure 8 As shown.

[0236] For example, such as Figure 9 As shown, its algorithm logic is concentrated in the microcontroller, which realizes all algorithm functions independently of the main controller. Each module independently calculates and realizes the excitation signal generation and measurement process based on the measurement requirements. The other modules that do not measure perform output compensation functions to maintain the stability of the external characteristics of the entire system.

[0237] Figure 11 A schematic diagram of the structure of the electronic device provided in this application. Figure 11 As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus 504.

[0238] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0239] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0240] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0241] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0242] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0243] For example, the electronic device may be a converter or a controller. The converter is a DC-DC converter, and correspondingly, the controller may include a DC-DC controller.

[0244] This application also provides an electrical appliance, including the controller and / or converter described above.

[0245] For example, the electrical equipment includes a vehicle, but may also include other electrical-consuming devices. The converter is a DC-DC converter, and correspondingly, the controller may include a DC-DC controller.

[0246] For example, the electrical equipment may also include an energy storage device, which includes a battery.

[0247] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0248] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0249] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0250] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0251] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0252] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0253] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0254] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0255] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0256] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A control method for controlling an energy storage device, characterized in that, include: Obtain the inverted compensation signal corresponding to the excitation signal; When the excitation signal is applied to the energy storage device under test, the inverting compensation signal is applied to the non-energy storage device under test.

2. The method according to claim 1, characterized in that, Applying the inverted compensation signal to the non-test energy storage device includes: The inverting compensation signal is applied to a non-energy storage device adjacent to the energy storage device under test; And / or, the method further includes: Obtain the excitation signal; When the energy storage device under test meets the measurement conditions, an excitation signal is applied to the energy storage device under test.

3. The method according to claim 1 or 2, characterized in that, The number of energy storage devices to be tested is multiple; the method further includes: Acquire the excitation signal corresponding to each of the energy storage devices under test; The excitation signal corresponding to each of the energy storage devices under test is applied to each of the energy storage devices under test in turn.

4. A control method for controlling an energy storage device, characterized in that, include: A corresponding inverse compensation signal is determined, and the inverse compensation signal is used to apply to a non-tested energy storage device when the excitation signal is applied to the energy storage device under test.

5. The method according to claim 4, characterized in that, The determination of the inverse compensation signal corresponding to the excitation signal includes: Determine the excitation current corresponding to the excitation signal; Based on the excitation current, determine the anti-phase compensation current that is opposite in phase to the excitation current; The inverse compensation signal is determined based on the inverse compensation current.

6. The method according to claim 5, characterized in that, The number of non-test energy storage devices is multiple; the step of determining an anti-phase compensation signal with the opposite phase to the excitation current based on the excitation current includes: The total compensation current is determined based on the excitation current; Based on the total compensation current and the number of non-test energy storage devices, determine the reverse-phase compensation current for each non-test energy storage device.

7. The method according to any one of claims 4-6, characterized in that, The method further includes: Within the frequency measurement range, determine the measurement frequency point that has the smallest deviation from the ideal frequency point; The amplitude and / or phase of the measured frequency point are optimized to obtain the optimized frequency point; The excitation signal is determined based on the optimized frequency point.

8. The method according to claim 7, characterized in that, The step of determining the measurement frequency point with the smallest deviation from the ideal frequency point within the frequency measurement range includes: Determine the total number of ideal frequency points based on the frequency measurement range and frequency display density; The ideal frequency point is determined based on the maximum and minimum frequency points corresponding to the frequency measurement range, and the total number of ideal frequency points. The measurement frequency point with the smallest deviation from the ideal frequency is selected from the candidate frequency points, and the candidate frequency points are determined based on the sampling frequency; And / or, optimize the amplitude and / or phase of the measured frequency point to obtain an optimized frequency point; Based on minimizing the crest factor, the amplitude and phase of the measured frequency point are determined to obtain the optimized frequency point; And / or, determining the excitation signal based on the optimized frequency point includes: The sinusoidal signal is determined based on the optimized frequency point; The sinusoidal signals are superimposed to obtain a superimposed signal; The superimposed signal is periodically processed to obtain the excitation signal.

9. The method according to any one of claims 4-6, characterized in that, The method further includes: The impedance of the energy storage device under test is determined based on the response signal of the energy storage device under test to the excitation signal.

10. The method according to claim 9, characterized in that, The response signal includes a voltage signal and a current signal; Determining the impedance of the energy storage device under test based on its response signal to the excitation signal includes: The voltage signal and the current signal are combined into a complex signal; Determine the spectrum of the composite signal and the spectrum of the corresponding conjugate sequence of the composite signal; The spectrum of the current signal and the spectrum of the voltage signal are determined based on the spectrum of the composite signal and the spectrum of the conjugate sequence. The impedance of the energy storage device is determined based on the spectrum of the voltage signal and the spectrum of the current signal. And / or, the method further includes: Obtain the SOC of each energy storage device; Based on the SOC of each energy storage device, determine the SOC difference characteristics of each energy storage device; Based on the SOC differences of each energy storage device, a balancing characteristic is determined, which is used to balance the SOC of each energy storage device.

11. A converter, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-3.

12. A controller, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 4-10.

13. An electrical appliance, characterized in that, include: The converter of claim 11 and / or the controller of claim 12.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-10.

15. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-10.

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