Method, device and equipment for controlling battery current ripple of energy storage inverter and medium

Abstract

This application provides a method, apparatus, device, and medium for controlling battery current ripple in an energy storage inverter, relating to the field of energy storage system technology. The method acquires system state information including battery current ripple, resonant converter component temperature, and load power, and dynamically obtains a matching target control strategy based on a preset control strategy. This allows for frequency control of the resonant converter, effectively solving the problem that existing fixed-parameter resonant converter control strategies cannot dynamically adjust according to real-time system conditions. It can accurately suppress battery current ripple and keep it within a safe range even when system load power changes frequently and component temperature fluctuates, reducing battery stress loss, improving overall system efficiency, preventing the resonant converter from operating in an unstable region, ensuring stable system operation, and extending battery life.

Description

Technical Field

[0001] This application relates to the field of energy storage system technology, and in particular to a method, apparatus, equipment and medium for controlling battery current ripple in energy storage inverters. Background Technology

[0002] Currently, single-phase energy storage inverters are widely used in distributed photovoltaic power generation, energy storage systems, and energy management systems. Their main function is to convert the DC power stored in the battery into single-phase AC power and feed it into the grid, or conversely, to convert the AC power from the grid into DC power to charge the battery. In single-phase energy storage inverter systems, precise control of battery current ripple is a key technical issue for ensuring stable system operation and extending battery life.

[0003] Existing single-phase energy storage inverters typically employ a fixed-parameter resonant converter control strategy, meaning that fixed resonant frequency and control parameters are pre-set during the design phase. However, in actual operation, this fixed-parameter control strategy often fails to effectively suppress battery current ripple, causing the ripple amplitude to exceed the safe range. This not only increases battery stress and reduces overall system efficiency but may also cause the resonant converter to operate in an unstable region, potentially even triggering system protection shutdown. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for controlling battery current ripple in an energy storage inverter, in order to solve the technical problems existing in the prior art.

[0005] In a first aspect, this application provides a method for controlling battery current ripple in an energy storage inverter, comprising: acquiring system state information of the energy storage inverter; wherein the system state information includes one or more of battery current ripple information, component temperature information of the resonant converter, and load power information; acquiring a target control strategy matching the system state information from a preset control strategy based on the system state information; wherein the preset control strategy is used to indicate the mapping relationship between the system state information and the control parameters of the resonant converter, the control parameters including frequency parameters, integral compensation parameters, and frequency range parameters of multiple parallel proportional resonant controllers; and performing frequency control on the resonant converter according to the target control strategy to control the battery current ripple within the target range.

[0006] In one possible design, obtaining a matching target control strategy from a preset control strategy based on the system state information includes: determining the quality factor of the resonant converter based on the load power information; determining an appropriate frequency combination from the frequency parameters of multiple parallel proportional resonant controllers based on the quality factor; and generating the fundamental driving frequency of the resonant converter through a nonlinear fitting algorithm.

[0007] In one possible design, the frequency control of the resonant converter according to the target control strategy includes: real-time monitoring of the ripple amplitude in the battery current ripple information; outputting a frequency compensation amount through an integral compensator when the ripple amplitude exceeds a preset safety threshold; and superimposing the frequency compensation amount with the basic drive frequency.

[0008] In one possible design, the step of frequency control of the resonant converter according to the target control strategy further includes: acquiring real-time efficiency information of the resonant converter; determining the target frequency range corresponding to the current operating condition based on the real-time efficiency information, the component temperature information, and a preset efficiency-temperature-ripple correlation model; and narrowing the target frequency range if the component temperature exceeds a preset temperature threshold or the real-time efficiency is lower than a preset efficiency threshold.

[0009] In one possible design, before acquiring the system state information of the energy storage inverter, the process further includes: determining the frequency parameters of multiple parallel proportional resonant controllers based on the current grid frequency; determining the initial operating center frequency and initial frequency range of the resonant converter based on the rated operating conditions; loading a preset efficiency-temperature-ripple correlation model; and initializing the parameters of the integral compensator.

[0010] In one possible design, determining the frequency parameters of multiple parallel proportional resonant controllers based on the current power grid frequency includes: obtaining the actual value of the current power grid frequency; and generating the frequency parameters of multiple parallel proportional resonant controllers based on integer multiples of the actual value.

[0011] In one possible design, after frequency control of the resonant converter according to the target control strategy, the method further includes: continuously collecting real-time system state information of the energy storage inverter to generate a closed-loop feedback dataset; and iteratively optimizing the mapping relationship in the preset control strategy and the control parameters based on the closed-loop feedback dataset to stabilize the battery current ripple within the target range.

[0012] Secondly, this application provides a control device for battery current ripple in an energy storage inverter, comprising: an acquisition module for acquiring system state information of the energy storage inverter; wherein the system state information includes one or more of battery current ripple information, component temperature information of the resonant converter, and load power information; a determination module for acquiring a target control strategy matching the system state information from a preset control strategy based on the system state information; wherein the preset control strategy indicates the mapping relationship between the system state information and the control parameters of the resonant converter, the control parameters including frequency parameters, integral compensation parameters, and frequency range parameters of multiple parallel proportional resonant controllers; and a control module for performing frequency control on the resonant converter according to the target control strategy to control the battery current ripple within a target range.

[0013] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method as described in any of the first aspects.

[0014] Fourthly, 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 method as described in any of the first aspects.

[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the first aspects.

[0016] The method provided in this application acquires system state information including battery current ripple, resonant converter component temperature, and load power, and dynamically acquires a matching target control strategy based on a preset control strategy. This allows for frequency control of the resonant converter, effectively solving the problem that existing fixed-parameter resonant converter control strategies cannot be dynamically adjusted according to real-time system conditions. It can accurately suppress battery current ripple and keep it within a safe range when system load power changes frequently or component temperature fluctuates, reducing battery stress loss, improving overall system efficiency, preventing the resonant converter from operating in an unstable region, ensuring stable system operation, and extending battery life. Attached Figure Description

[0017] 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.

[0018] Figure 1This is an application scenario diagram corresponding to the control method for battery current ripple of an energy storage inverter provided in an embodiment of this application. Figure 2 A schematic flowchart illustrating a method for controlling battery current ripple in an energy storage inverter according to an embodiment of this application; Figure 3 A flowchart illustrating a method for controlling battery current ripple in an energy storage inverter, as provided in another embodiment of this application; Figure 4 A schematic diagram of the structure of a control device for battery current ripple in an energy storage inverter provided in an embodiment of this application; Figure 5 This is a structural example diagram of an electronic device provided in an embodiment of this application.

[0019] 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

[0020] 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 represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0021] To clearly understand the technical solution of this application, the existing technology solutions are first described in detail. Currently, single-phase energy storage inverters are widely used in distributed photovoltaic power generation, home energy storage systems, and small-scale commercial energy management systems. Their main function is to convert the DC power stored in the battery into single-phase AC power and feed it into the grid, or conversely, to convert the AC power from the grid into DC power to charge the battery. In single-phase energy storage inverter systems, precise control of battery current ripple is a key technical issue to ensure stable system operation and extend battery life. Existing single-phase energy storage inverters typically employ a fixed-parameter resonant converter control strategy, that is, fixed resonant frequency parameters and control parameters are preset during the design phase, which cannot be dynamically adjusted according to the real-time operating conditions of the system. However, in actual operation, the system load power changes frequently, and the component temperature of the resonant converter fluctuates with the operating time, thereby affecting the amplitude and frequency characteristics of the battery current ripple. When the load power changes abruptly or the temperature rises, the fixed parameter control strategy often fails to effectively suppress the battery current ripple, causing the ripple amplitude to exceed the safe range. This not only increases the stress loss of the battery and reduces the overall system efficiency, but may also cause the resonant converter to operate in an unstable region, or even cause the system protection shutdown.

[0022] Figure 1 This is an application scenario diagram corresponding to the battery current ripple control method for an energy storage inverter provided in an embodiment of this application, such as... Figure 1 As shown, the application scenario provided in this embodiment includes: a single-phase energy storage inverter system 10 and a ripple controller 11. The ripple controller 11 is connected to each core component of the single-phase energy storage inverter system 10 via a sensor link. The single-phase energy storage inverter system 10 includes an energy storage battery, a parallel resonant converter, an inverter bridge, and a grid connection unit.

[0023] Specifically, firstly, the ripple controller 11 acquires the system status information of the single-phase energy storage inverter system 10 in real time, including battery current ripple information, component temperature information of the resonant converter, and load power information. Subsequently, based on the acquired system status information, the ripple controller 11 matches the corresponding target control strategy from the preset control strategy library. This preset strategy clarifies the mapping relationship between the system status information and the control parameters of the resonant converter. The control parameters include multiple sets of parallel resonant frequency parameters, integral compensation parameters, and frequency range parameters. Finally, the ripple controller 11 performs dynamic frequency adjustment on the resonant converter according to the target control strategy, accurately controlling the battery current ripple within the target safe range, and ensuring the stable and efficient operation of the energy storage inverter system under all operating conditions.

[0024] 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.

[0025] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules 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 modules, and may be electrical, mechanical, or other forms.

[0026] Figure 2 A flowchart illustrating a method for controlling battery current ripple in an energy storage inverter according to an embodiment of this application is shown below. Figure 2 As shown, the execution subject of this embodiment is a control device for the battery current ripple of the energy storage inverter. This device can be implemented by a computer program, or by a medium storing the relevant computer program; or it can be implemented by a physical device that integrates or installs the relevant computer program, such as a chip, electronic device, etc.

[0027] Specifically, the battery current ripple control method for energy storage inverters provided in this application is applied to a single-phase energy storage inverter system. The single-phase energy storage inverter system includes at least a battery pack, a resonant converter, a DC / AC inverter unit, a power grid, and a load. The output terminal of the battery pack is electrically connected to the low-voltage side of the resonant converter, the high-voltage side of the resonant converter is electrically connected to the DC bus side of the DC / AC inverter unit, and the AC side of the DC / AC inverter unit is electrically connected to the power grid and the load.

[0028] This application provides a method for controlling battery current ripple in an energy storage inverter, including: S201, acquiring system status information of the energy storage inverter; wherein, the system status information includes one or more of battery current ripple information, component temperature information of the resonant converter, and load power information.

[0029] The system status information includes one or more of the following: battery current ripple information, component temperature information of the resonant converter, and load power information. A combination acquisition scheme of the three is preferred to achieve full-dimensional coverage of feedback quantity, drift characterization quantity, and feedforward quantity.

[0030] The battery current ripple information serves as the direct closed-loop feedback for ripple control, specifically including the real-time ripple amplitude, ripple frequency, and ripple harmonic content of the battery current. Optionally, the real-time total battery current can be acquired by a current sampling unit (e.g., a Hall current sensor or a high-precision shunt resistor in conjunction with a sampling circuit) located at the battery pack output port. The DC component is then stripped using digital filtering algorithms (e.g., bandpass filtering, moving average filtering) to extract the AC ripple component, thereby calculating the ripple amplitude, frequency, and harmonic characteristics. This battery current ripple information is used to directly determine whether the current ripple exceeds the target range.

[0031] Among these, the component temperature information of the resonant converter serves as a crucial indicator of resonant cavity parameter drift. Specifically, this includes the core temperature of the resonant inductor, the body temperature of the resonant capacitor, and the junction temperature of the power switching transistors (MOSFETs / IGBTs). Optionally, surface-mount thermistors or digital temperature chips can be attached to the heating surfaces of the corresponding power devices to collect temperature data in real time. Since the permeability of the resonant inductor and the capacitance of the resonant capacitor both drift significantly with temperature, directly causing the inherent resonant frequency of the resonant cavity to deviate from the design value, this is a contributing factor to the failure of fixed-parameter control strategies. Therefore, these parameters are considered key input quantities for control strategy matching.

[0032] Load power information serves as a feedforward input for changes in operating conditions, specifically including the system's real-time load active power, power change rate, and power flow direction (battery charging / discharging direction). Optionally, real-time electrical quantities from the grid / load side can be collected through AC-side voltage and current sampling units, and real-time active power can be obtained through a power calculation unit. Combined with DC-side power acquisition data, the power change rate and power flow direction can be calculated. Changes in load power directly cause the resonant converter's operating point to deviate from the optimal resonant point, while sudden load changes bring dynamic ripple impacts. This load power information enables proactive ripple control, solving the lag problem of single feedback control.

[0033] S202. Based on the system state information, obtain the target control strategy that matches the system state information from the preset control strategy; wherein, the preset control strategy is used to indicate the mapping relationship between the system state information and the control parameters of the resonant converter, and the control parameters include multiple parallel resonant frequency parameters, integral compensation parameters and frequency range parameters.

[0034] Among them, the preset control strategy is a pre-established mapping relationship library between system state information and resonant converter control parameters, which is a set of control parameters covering the entire operating range of the system.

[0035] Optionally, offline simulation calibration and full-condition prototype testing can be used to calibrate control parameter combinations that stably control the battery current ripple within the target range for different load power ranges, component temperature ranges, and battery current ripple ranges, forming a one-to-one mapping relationship between system state ranges and control parameter combinations. Alternatively, intelligent matching of the mapping relationship can be achieved using machine learning models (such as neural networks or decision tree models) trained on full-condition sample data. The mapping relationship library covers the entire load power range, the entire operating temperature range, and the entire ripple condition range of the system, ensuring that there are corresponding control parameters for any operating condition.

[0036] The frequency parameters of the multi-parallel proportional resonant controller refer to the multiple target resonant frequency values ​​set in the multi-parallel proportional resonant (PR) control unit to achieve targeted suppression of different frequency harmonic components in the battery current ripple. Each set of frequency parameters corresponds to an independent PR control channel. After each control channel completes closed-loop calculation based on the corresponding frequency parameter, they jointly generate the frequency compensation amount of the resonant converter and participate in the closed-loop control of the final drive frequency. Through multiple sets of parallel PR control channels, precise suppression of harmonic ripple components of the battery current ripple with zero steady-state error can be achieved. It can adapt in real time to the ripple frequency shift caused by grid frequency fluctuations and resonant cavity parameter drift, so that the resonant converter always operates in the soft-switching range near the resonant point. This is different from the existing technology of fixing a single resonant frequency and being unable to target and suppress specific frequency ripples.

[0037] The integral compensation parameter is the integral coefficient of the proportional-integral regulator in the frequency closed-loop control loop of the resonant converter, and can be dynamically adjusted in conjunction with the proportional coefficient. This integral compensation parameter is used to regulate the dynamic response speed and steady-state accuracy of the frequency control loop. It is set differently for different operating conditions. When there are sudden changes in load power or rapid exceedances of ripple amplitude, a large integral compensation parameter is used to improve the loop response speed and quickly suppress ripple impacts. When the system is operating in steady state and the ripple is within the target range, a small integral compensation parameter is used to improve loop stability, avoid frequency oscillations, and prevent the problem of fixed parameters failing to balance dynamic response and steady-state stability.

[0038] The frequency range parameter refers to the upper and lower thresholds of the resonant converter's operating frequency, i.e., the allowable fluctuation range of the switching frequency. This frequency range parameter is used to limit the operating range of the resonant converter, preventing it from operating in unstable regions such as the capacitive region. Furthermore, the upper and lower limits can be dynamically adjusted for different temperatures and load conditions. When the component temperature rises, causing the inherent resonant frequency to decrease, the lower frequency limit is lowered accordingly; when the load power decreases, the frequency range is narrowed to improve control accuracy, maximizing the adjustable range of frequency control while ensuring system stability.

[0039] Specifically, during real-time system operation, the system status information collected by S201 is matched with the status intervals in the mapping relationship library of the preset control strategy, and the control parameter combination corresponding to the current operating condition is quickly retrieved, which is the target control strategy.

[0040] S203. According to the target control strategy, the frequency of the resonant converter is controlled to keep the battery current ripple within the target range.

[0041] This step achieves precise ripple suppression through multi-parameter coordinated frequency closed-loop control. Specifically, based on the target control parameters matched in S202, PWM (Pulse Width Modulation) drive signals are generated for each power switch of the resonant converter. By adjusting the switching frequency of the PWM drive signals, frequency closed-loop control of the resonant converter is achieved. Furthermore, battery current ripple information can be collected in real time as feedback to dynamically fine-tune the switching frequency, forming a closed-loop control circuit of state acquisition, strategy matching, frequency control, and ripple feedback. Ultimately, the amplitude and harmonic content of the battery current ripple are stably controlled within the preset target safety range.

[0042] Optionally, the integral parameters of the proportional-integral regulator in the frequency closed-loop control loop can be adjusted in real time according to the target integral compensation parameters to optimize the loop's dynamic response and steady-state characteristics. Optionally, the upper and lower thresholds of the switching frequency can be limited according to the target frequency range parameters to prevent the resonant converter from operating in the capacitively unstable region and ensure system safety.

[0043] The battery current ripple control method for energy storage inverters provided in this application obtains system state information including battery current ripple, resonant converter component temperature, and load power, and dynamically obtains a matching target control strategy based on a preset control strategy. This allows for frequency control of the resonant converter, effectively solving the problem that existing fixed-parameter resonant converter control strategies cannot be dynamically adjusted according to real-time system conditions. It can accurately suppress battery current ripple and keep it within a safe range when system load power changes frequently and component temperature fluctuates, reducing battery stress loss, improving overall system efficiency, preventing the resonant converter from operating in an unstable region, ensuring stable system operation, and extending battery life.

[0044] As an optional implementation, based on any of the above embodiments, a matching target control strategy is obtained from a preset control strategy according to the system state information, including the following steps: First, the quality factor of the resonant converter is determined according to the load power information.

[0045] The quality factor (Q value) is a dimensionless parameter that characterizes the load characteristics of the resonant network of a resonant converter, determines its voltage gain characteristics, soft-switching operating range, and ripple propagation characteristics. For the bidirectional LLC resonant converter applicable to this scheme, the quality factor directly reflects the damping effect of the current load on the resonant cavity. Its value is strongly correlated with the load power and is a variable that determines the relationship between the resonant cavity's natural resonant frequency and the optimal operating switching frequency.

[0046] Optionally, the quality factor can be calculated in real time based on the load power information collected by S201 (including real-time load active power, power flow direction (charging / discharging mode), DC bus voltage, and battery side voltage) and combined with the inherent topology parameters of the resonant converter, and is fully adapted to the bidirectional operation of the energy storage inverter.

[0047] Specifically, the calculation logic for the quality factor is as follows: In discharge mode (battery supplies power to the grid / load, forward operation), the energy flow of the resonant converter is sequentially: battery side, resonant cavity, DC bus, inverter unit, grid / load. The equivalent load impedance is determined by the load power on the DC bus side. The formula for calculating the quality factor Q is: .in, This is the inherent series resonant frequency of the resonant cavity. Lr is the nominal value of the resonant inductance, Cr is the nominal value of the resonant capacitance, and Rac is the equivalent AC load impedance.

[0048] When in charging mode (grid charging battery, reverse operation), the energy flow of the resonant converter is sequentially grid, inverter unit, DC bus, resonant cavity, and battery. The equivalent load impedance is determined by the charging power on the battery side. The calculation formula is adapted to the topology characteristics of reverse operation. The equivalent load impedance is calculated based on the real-time charging power and battery terminal voltage, and finally the real-time quality factor Q under reverse operation is obtained.

[0049] It should be noted that one of the shortcomings of existing fixed-parameter control strategies is that they only design a fixed resonant frequency for the rated Q value corresponding to the rated power, ignoring the large-scale changes in Q value caused by frequent fluctuations in load power during actual operation. The frequency and gain curves of the resonant converter will shift globally with changes in Q value. When the load power decreases (light load), the Q value decreases, the peak value of the gain curve shifts upward, and the optimal operating frequency shifts to a higher frequency; when the load power increases (heavy load), the Q value increases, the peak value of the gain curve shifts downward, and the optimal operating frequency shifts to a lower frequency. If a fixed frequency is always used, the converter will directly operate in a detuned state, the isolation capability of the resonant cavity from the DC bus second harmonic ripple will decrease sharply, switching losses will increase, and ultimately, the battery current ripple will exceed the standard. This application calculates the Q value in real time, accurately capturing the characteristic changes of the resonant cavity under the current load condition, providing a direct and accurate basis for subsequent frequency matching, and solving the detuning problem caused by load changes.

[0050] Secondly, based on the quality factor, a suitable frequency combination is determined from the frequency parameters of multiple parallel proportional resonant controllers, and the fundamental driving frequency of the resonant converter is generated through a nonlinear fitting algorithm.

[0051] Among them, the frequency parameters of the multi-parallel proportional resonant controller are the set of frequency parameters of each PR control channel that are pre-calibrated in the preset control strategy and correspond to different quality factor ranges; the frequency combination is the set of target resonant frequencies corresponding to each parallel PR control channel that matches the current real-time Q value.

[0052] Optionally, during the system design phase, through offline simulation and full-condition prototype experiments, the optimal target resonant frequency of each branch of the multi-parallel PR controller is calibrated one by one for the Q value range covering the entire range from light load to full load, forming a one-to-one mapping relationship between the Q value range and the resonant frequency combination, and storing it in the mapping relationship library of the preset control strategy.

[0053] Optionally, the calibration principle for each frequency combination can be that, while ensuring the Q value, the corresponding frequency allows the resonant converter of that branch to operate in the zero-voltage switching (ZVS) soft-switching range, minimizing switching losses. At this frequency, the resonant cavity has the strongest isolation capability against the DC bus second harmonic ripple, and the ripple transfer coefficient is minimized.

[0054] Optionally, during system operation, the calculated real-time Q value is matched with the Q value range in the preset mapping relationship library, and the optimal frequency combination corresponding to the current Q value is retrieved to complete the matching of control parameters.

[0055] It should be noted that the Q-value of the resonant converter and its optimal operating frequency have a strongly nonlinear relationship, which is essentially determined by the nonlinear frequency gain characteristics of the LLC resonant topology. If traditional linear interpolation or piecewise gear control is used, frequency matching errors will occur under non-calibrated Q-value conditions, leading to a decrease in ripple suppression. Furthermore, gear switching will cause frequency jumps, triggering control loop oscillations. Therefore, this solution employs a nonlinear fitting algorithm to achieve continuous and precise control across the entire range.

[0056] Optionally, during the system design phase, based on multiple sets of calibrated discrete Q-value and resonant frequency sample data, a nonlinear polynomial fitting method can be used to generate a nonlinear fitting function for the Q-value and the resonant frequency of each branch. After fitting, this nonlinear fitting function is stored in the preset control strategy. During system operation, the calculated real-time Q-value is substituted into the aforementioned nonlinear fitting function to directly calculate the continuous and accurate basic drive frequency of each parallel branch, without the need for discrete gear switching, resulting in a smooth and shock-free control process.

[0057] It should be noted that the quality factor of the resonant converter is determined based on the load power information in the system status information. Then, based on this, a suitable frequency combination is precisely determined from the frequency parameters of multiple parallel proportional resonant controllers, and a nonlinear fitting algorithm is used to generate the fundamental drive frequency. This allows for flexible adjustment of the key parameters of the resonant converter according to real-time changes in load power. Compared to traditional fixed-parameter control, this approach can more accurately adapt to different operating conditions, effectively optimize the working state of the resonant converter, more precisely control battery current ripple, reduce system losses, and improve system stability and efficiency.

[0058] Figure 3 A flowchart illustrating a method for controlling battery current ripple in an energy storage inverter according to another embodiment of this application; as shown Figure 3 As shown, as an optional implementation, based on any of the above embodiments, frequency control of the resonant converter is performed according to the target control strategy, including the following steps: S301, real-time monitoring of the ripple amplitude in the battery current ripple information.

[0059] The real-time monitored ripple amplitude refers to the peak or effective value of the AC ripple component after removing the DC charging and discharging components from the total battery output current. The total ripple amplitude across the entire frequency band is prioritized as the monitoring subject, allowing for targeted monitoring of the disturbance source in single-phase energy storage inverters, namely, the ripple amplitude at twice the power frequency (100Hz). The full-frequency ripple coverage includes switching frequency ripple, the fundamental ripple at twice the power frequency, and higher harmonic ripple, comprehensively reflecting the true level of battery current ripple. The targeted monitoring of the ripple at twice the power frequency can accurately locate the ripple component caused by the inherent power fluctuations of the single-phase inverter, improving the targeting of compensation control.

[0060] Optionally, a current sampling unit (Hall current sensor or milliohm-level high-precision shunt resistor in conjunction with differential sampling circuit) located at the battery pack output port can synchronously sample the real-time total battery current at a sampling rate no less than 10 times the switching frequency of the resonant converter, ensuring distortion-free acquisition of the ripple signal. The sampled total current signal is then filtered and separated using digital signal processing algorithms. First, a low-pass filter removes high-frequency switching noise and spurious interference; then, a high-pass or band-pass filter removes the DC charging and discharging components of the battery, extracting the pure AC ripple component. Finally, a peak detection algorithm and a true RMS calculation algorithm are used to perform real-time calculations on the extracted AC ripple component to obtain the ripple amplitude for the current control cycle. The calculation cycle is completely synchronized with the frequency control loop cycle of the resonant converter, ensuring the real-time nature of the monitoring data and the synchronization of the closed-loop control.

[0061] It should be noted that existing control strategies often use intermediate quantities such as DC bus voltage and output current as feedback, which cannot directly reflect the true state of ripple on the battery side, resulting in a disconnect between the control target and the feedback quantity. This step, however, directly uses the battery current ripple amplitude as the monitoring object, achieving a direct correspondence between the control target and the feedback signal, and avoiding control deviations caused by intermediate quantity feedback.

[0062] S302. When the ripple amplitude exceeds the preset safety threshold, the frequency compensation amount is output through the integral compensator.

[0063] The purpose of this step is to generate a precise frequency compensation amount through the integral compensator when the ripple exceeds the limit, perform closed-loop correction on the basic drive frequency, eliminate the ripple error that cannot be covered by the feedforward control, and achieve zero-error control of the ripple.

[0064] Among them, the preset safety threshold is the maximum allowable amplitude of battery current ripple that has been pre-calibrated. It serves as the benchmark for determining whether compensation control is triggered. The calibration basis may include: the cell specifications provided by the battery manufacturer, the battery cycle life decay model, the system electromagnetic compatibility requirements, and the overall safety operation specifications.

[0065] Optionally, to balance steady-state control accuracy and dynamic anti-interference capability, the preset safety threshold is divided into a steady-state safety threshold and a dynamic impact threshold. The steady-state safety threshold can be selected as 0.5% to 2% of the battery's rated charge and discharge current to constrain the ripple level during long-term steady-state operation and avoid cyclic degradation caused by long-term low-amplitude ripple. The dynamic impact threshold can be 3% to 5% of the battery's rated charge and discharge current to respond to ripple impacts under dynamic operating conditions such as load changes and grid fluctuations, and avoid system risks caused by short-term ripple exceeding the standard.

[0066] Optionally, the preset safety threshold can be adaptively adjusted according to the battery type, battery state of charge, and battery temperature. For example, when the battery state of charge is extremely low / high or the battery temperature is too low / high, the range of the preset safety threshold can be appropriately narrowed to further reduce battery stress and improve the safety of the battery throughout its entire life cycle.

[0067] Optionally, to avoid false triggering caused by sampling noise and transient interference, the ripple amplitude of the current control cycle is compared with a preset safety threshold in real time. When the ripple amplitude continuously exceeds the preset safety threshold for a preset anti-jitter duration (e.g., 2 to 5 control cycles), it is determined that the ripple is continuously exceeding the standard, and the integral compensator is officially triggered to work. After the integral compensator works, if the ripple amplitude falls back to within the preset safety threshold and remains stable for a preset exit duration (e.g., 10 to 20 control cycles), it is determined that the ripple control meets the standard, the integral compensator stops integral accumulation, maintains the current compensation amount or slowly returns to zero, to avoid ripple rebound caused by sudden changes in the compensation amount.

[0068] The integral compensator is the computational unit that realizes ripple error-free control in this step. Its function is to generate a compensation amount to correct the drive frequency based on the ripple amplitude error, thereby eliminating the ripple steady-state error.

[0069] The input to the integral compensator is the ripple amplitude error, which is the difference between the real-time monitored ripple amplitude and the preset safety threshold; the output is the frequency compensation, used to correct the base drive frequency in either the forward or reverse direction. Optionally, the integral compensator can be a proportional-integral (PI) controller, or a pure integral controller or a PID controller, depending on the control requirements.

[0070] The proportional and integral coefficients of the integral compensator are mapped to the system state information in the preset control strategy. Different load power ranges, quality factor ranges, and component temperature ranges correspond to different regulator parameters, which are pre-calibrated and stored in the preset control strategy library. For example, under heavy load conditions, the resonant converter loop gain is high, so a smaller proportional and integral coefficient is used to avoid loop oscillation; under light load conditions, the loop gain is low, so a larger proportional and integral coefficient is used to improve the compensation response speed, achieving the optimal match between loop stability and response speed under all operating conditions.

[0071] S303. The frequency compensation amount is superimposed on the basic drive frequency.

[0072] The purpose of this step is to superimpose the basic driving frequency of the feedforward control with the frequency compensation amount of the closed-loop feedback to generate the final driving frequency, complete the closed-loop frequency control of the resonant converter, and simultaneously achieve smooth integration and safety constraints of feedforward and feedback control.

[0073] Among them, the base drive frequency is the feedforward control quantity, which is the current operating condition reference frequency generated by quality factor matching and nonlinear fitting. It undertakes the main operating condition adaptation function, covering more than 90% of the frequency adjustment needs brought about by calibrable operating conditions such as load and temperature, and ensuring the speed of control. The frequency compensation quantity is the closed-loop feedback correction quantity, which is used to correct the residual errors that cannot be covered by the feedforward control, including ripple exceeding the standard caused by unforeseen factors such as component parameter dispersion, long-term aging drift, grid voltage distortion, and unmodeled nonlinear disturbances, so as to achieve ripple error-free control.

[0074] Optionally, the frequency superposition operation is completed synchronously within each control cycle. First, the feedforward calculation of the basic drive frequency is completed, then the closed-loop update of the frequency compensation is performed, and finally, the superposition operation is performed. This ensures the synchronization of feedforward and feedback control, avoiding control errors caused by timing deviations. Furthermore, to avoid sudden changes in the drive frequency caused by abrupt changes in the frequency compensation, a slope constraint is added during the superposition process. Within each control cycle, the maximum change in the final drive frequency does not exceed a preset threshold (e.g., a maximum change of 0.5kHz to 1kHz per cycle), ensuring a smooth and shock-free frequency adjustment process and avoiding sudden stress changes in the power switch and control loop oscillations. The final drive frequency after superposition must be limited to the upper and lower limits of the frequency range parameter in the target control strategy. If the superimposed frequency exceeds the allowable range, the final drive frequency is directly clamped to the corresponding upper or lower threshold, ensuring that the resonant converter always operates in the inductive soft-switching range, completely eliminating device damage, system oscillations, and protection shutdowns caused by capacitive conduction. After obtaining the final drive frequency through superposition calculation, a PWM (Pulse Width Modulation) drive signal with a corresponding duty cycle (fixed 50% duty cycle, adapted to the control characteristics of LLC resonant converter) is generated based on the drive frequency. After setting the dead time, the signal is output to the drive terminals of each power switch of the resonant converter to complete the real-time frequency closed-loop control of the resonant converter and finally stabilize the battery current ripple within the target range.

[0075] It should be noted that the solution in this application can detect abnormal ripple in a timely manner by monitoring the battery current ripple amplitude in real time. When it exceeds the preset safety threshold, the integral compensator accurately outputs the frequency compensation amount and superimposes it with the basic drive frequency. This can quickly and effectively adjust the frequency of the resonant converter, thereby accurately suppressing excessive battery current ripple and avoiding problems such as battery performance degradation, system efficiency reduction, and unstable operation caused by excessive ripple.

[0076] As an optional implementation, based on any of the above embodiments, frequency control of the resonant converter according to the target control strategy further includes the following steps: First, obtaining the real-time efficiency information of the resonant converter.

[0077] The purpose of this step is to accurately obtain the true operating efficiency of the resonant converter under the current operating conditions, so as to provide a basis for judgment for subsequent dynamic adjustment of the frequency range.

[0078] The real-time efficiency information of the resonant converter refers to the ratio of the output active power to the input active power of the bidirectional LLC resonant converter under the current operating conditions. It is an indicator for quantifying the energy conversion loss of the converter and judging whether it is operating in the optimal efficiency range. Since this scheme is applied to a bidirectional energy storage inverter, the efficiency calculation needs to fully cover both charging and discharging bidirectional operating modes: the real-time efficiency in discharging mode is the ratio of the output active power on the high-voltage side to the input active power on the low-voltage side battery side; the real-time efficiency in charging mode is the ratio of the output active power on the low-voltage side battery side to the input active power on the high-voltage side bus side.

[0079] Optionally, the real-time voltage and current values ​​of the input and output sides of the resonant converter are collected through voltage and current sampling units, and the active power is calculated in real time through power calculation units to obtain the real-time efficiency.

[0080] It should be noted that the operating efficiency of an LLC resonant converter is strongly correlated with the switching frequency. When the converter operates near its inherent resonant frequency, it can achieve full-range zero-voltage switching (ZVS) soft-switching, minimizing switching losses and reaching peak efficiency. When the switching frequency deviates from the resonant frequency, the soft-switching effect deteriorates, switching losses and magnetic losses increase significantly, and efficiency decreases accordingly. This step obtains efficiency information in real time, providing a direct basis for subsequent dynamic adjustment of the frequency range.

[0081] Secondly, based on real-time efficiency information, component temperature information, and a preset efficiency-temperature-ripple correlation model, the target frequency range corresponding to the current operating condition is determined.

[0082] This step uses a pre-defined efficiency-temperature-ripple correlation model to achieve coupled calculation of the three control objectives, determine the reference range of the frequency range under the current operating conditions, and provide a benchmark for subsequent dynamic adjustments.

[0083] Among them, the preset efficiency-temperature-ripple correlation model is the preset control model of this scheme. It can be built in advance through offline simulation calibration and full-condition prototype test, and stored in the system preset control strategy library. It is used to characterize the coupling mapping relationship between the switching frequency, operating efficiency, component temperature and battery current ripple of the LLC resonant converter.

[0084] Specifically, the preset efficiency-temperature-ripple correlation model is based on the physical characteristics of LLC resonant converters, and clarifies the coupling law of the four factors.

[0085] Regarding the relationship between frequency and ripple: Within the ZVS safe operating region to the right of the resonant point, the higher the switching frequency, the greater the input impedance of the LLC resonant cavity, the stronger the isolation and suppression capability for the 100Hz double power frequency ripple on the DC bus side, and the smaller the amplitude of the battery side current ripple. Regarding the relationship between frequency and efficiency: The closer the switching frequency is to the inherent resonant frequency, the better the soft-switching effect, the smaller the switching loss and magnetic loss, and the higher the converter operating efficiency. The further the switching frequency deviates from the resonant point (especially in the high-frequency range), the lower the efficiency. Regarding the relationship between temperature, parameters, and efficiency: Increased component temperature leads to drift in the permeability of the resonant inductor and the capacitance of the resonant capacitor, a shift in the inherent resonant frequency of the resonant cavity, and an increase in the on-resistance of the power devices, increasing switching losses, further leading to decreased efficiency and deterioration of ripple suppression capability. Furthermore, if the component temperature exceeds the rated threshold, it can cause power device failure, core demagnetization, and even system failure, which is a safety constraint for frequency range control.

[0086] Optionally, during the system design phase, a full-condition traversal test of the prototype can be conducted, covering the full power range from light load to full load, the full operating temperature range, and the full frequency range from resonant frequency to maximum allowable frequency. Efficiency, temperature, ripple, and frequency data corresponding to each set of operating conditions can be collected to construct a three-dimensional mapping table or a nonlinear fitting function model. Optionally, using load power and component temperature as input dimensions, corresponding efficiency and ripple characteristic values ​​under different frequency ranges can form a one-to-one mapping relationship between operating condition input, frequency range, and performance output. Based on the calibrated full-condition sample data, a frequency range solution function constrained by efficiency, temperature, and ripple can be generated through polynomial fitting and neural network fitting, enabling continuous solution across all operating conditions.

[0087] Among them, the target frequency range, that is, the allowable upper and lower operating thresholds of the resonant converter's switching frequency, is a parameter that constrains the operating area of ​​the resonant converter, ensures that it always operates within the ZVS safe range, and balances ripple and efficiency.

[0088] In this step, the efficiency information and component temperature information collected in real time are input into the preset correlation model. By looking up tables or solving functions, the reference target frequency range that balances ripple suppression capability, operating efficiency and temperature safety under the current operating conditions can be obtained. This range is limited to the ZVS operating region to the right of the LLC resonant point to avoid the switching frequency from entering the ZCS (Zero Current Switching) region to the left of the resonant point.

[0089] Specifically, if the component temperature exceeds a preset temperature threshold or the real-time efficiency is lower than a preset efficiency threshold, the target frequency range is narrowed. If the battery current ripple exceeds a preset safety threshold, the upper frequency limit of the target frequency range is increased.

[0090] This step addresses abnormal operating conditions such as overheating and low efficiency in the resonant converter by narrowing the frequency range, confining the switching frequency to a high-efficiency, low-loss range close to the resonant point, thereby curbing the continuous rise in temperature.

[0091] The preset temperature threshold is the maximum allowable operating temperature of the core components of the resonant converter, pre-calibrated. It represents a safety boundary for narrowing the trigger frequency range. Its calibration is based on the rated operating temperatures of the power switching transistor, resonant inductor, and resonant capacitor, with a safety derating margin. For example, for a MOSFET power transistor with a rated junction temperature of 150°C, the preset temperature threshold is calibrated to be 85°C to 105°C; when the Curie temperature of the resonant inductor core is 200°C, the preset temperature threshold is calibrated to be 120°C.

[0092] The preset efficiency threshold is the minimum allowable operating efficiency of the converter under the current operating conditions, pre-calibrated. It serves as the energy efficiency boundary for narrowing the trigger frequency range. Its calibration is based on the energy efficiency target of the system design and is set in stages according to different load power ranges. For example, the preset efficiency threshold is calibrated to 96% under rated load conditions; 95% under half-load conditions; and 93% under light load conditions, ensuring that the system energy efficiency remains within the design target range under all operating conditions.

[0093] Specifically, the current component temperature is compared with the preset temperature threshold and the real-time efficiency is compared with the preset efficiency threshold in real time. When any of the following conditions are met, the frequency range reduction operation is immediately triggered: First, the real-time temperature of any core component continuously exceeds the preset temperature threshold and the duration reaches the preset anti-shake cycle (e.g., 2 to 5 control cycles) to avoid false triggering caused by instantaneous temperature spikes; Second, the real-time efficiency continuously falls below the preset efficiency threshold under the corresponding operating condition and the duration reaches the preset anti-shake cycle to eliminate misjudgment caused by sampling noise.

[0094] Specifically, the allowable operating range of the switching frequency is narrowed towards the resonant frequency, limiting significant frequency shifts to higher frequencies. This confines the resonant converter to a high-efficiency range with optimal soft-switching performance and minimal losses. Furthermore, since high frequencies are a major cause of increased losses, decreased efficiency, and heightened heat generation, the narrowing operation prioritizes lowering the upper limit of the frequency range while maintaining the lower limit unchanged. This prevents excessive frequency shifts towards lower frequencies, avoiding proximity to the resonant point and preventing entry into the capacitive instability region to the left of the resonant point. A graded, gradual adjustment approach can be adopted: the larger the temperature overshoot and efficiency deviation, the greater the frequency range reduction ratio, avoiding control loop oscillations caused by a single large adjustment. For example, for temperature overshoots within 5°C, the upper limit is reduced by 10%; for overshoots between 5 and 10°C, the upper limit is reduced by 20%; and for overshoots above 10°C, the upper limit is reduced by 30%. The reduced lower limit of the frequency range always remains above the LLC inherent resonant frequency, ensuring the resonant converter operates in the ZVS inductive region to the right of the resonant point and mitigating the risk of positive feedback runaway.

[0095] It should be noted that when component temperatures exceed limits or efficiency is too low, the underlying cause is that the switching frequency deviates excessively from the resonant frequency, causing the converter to operate in a high-loss range. By narrowing the frequency range, the switching frequency is forced to be constrained to a high-efficiency range near the resonant point, rapidly reducing component losses and heat generation, restoring efficient system operation. Furthermore, a narrower frequency range can reduce frequency fluctuation amplitude, improve the stability of the control loop, and prevent system oscillations caused by large frequency jumps.

[0096] Optionally, when the real-time monitored battery current ripple amplitude continuously exceeds the preset safety threshold for a duration of 2 to 3 control cycles, the frequency upper limit value is immediately increased. It should be noted that, based on the inherent characteristic of LLC topology that "the higher the frequency, the stronger the ripple suppression capability," by increasing the upper limit of the frequency range, the high-frequency adjustment space of the switching frequency is expanded. This allows the frequency compensation output of the integral compensation stage to drive the switching frequency to a higher range, further enhancing the resonant cavity's isolation capability against twice the power frequency ripple and quickly suppressing excessive ripple.

[0097] Optionally, a tiered increase method matching the ripple overshoot amplitude can be adopted. The larger the ripple overshoot amplitude, the higher the upper limit value is increased, avoiding a sudden drop in efficiency and heat generation caused by a single large adjustment. For example, if the ripple overshoot is within 20%, the upper limit value is increased by 10%; if the ripple overshoot is 20% to 50%, the upper limit value is increased by 20%; if the ripple overshoot is above 50%, the upper limit value is increased by 30% to 50%.

[0098] It should be noted that the increased upper limit of frequency does not exceed the maximum allowable switching frequency preset by the system. This maximum frequency is calibrated based on the ZVS critical frequency of the LLC topology, the highest switching frequency of the power devices, and the highest operating frequency of the magnetic core. This ensures that even if the upper limit is increased, the resonant converter will still operate in the ZVS region and will not enter the ZCS high-loss region, thus avoiding device damage.

[0099] It should be noted that existing control schemes with fixed frequency ranges typically set a low upper frequency limit to ensure efficiency under rated operating conditions. When sudden load changes, parameter drift, or other conditions cause ripple to exceed the limit significantly, the frequency adjustment space is limited, making it impossible to effectively suppress ripple by increasing the frequency, ultimately leading to uncontrolled ripple. This step dynamically expands the upper frequency limit through a ripple exceeding the limit trigger mechanism, breaking the constraints of the fixed range and prioritizing battery ripple safety under extreme operating conditions.

[0100] As an optional implementation, based on any of the above embodiments, before obtaining the system status information of the energy storage inverter, the method further includes: determining the frequency parameters of multiple parallel proportional resonant controllers according to the current grid frequency; determining the initial operating center frequency and initial frequency range of the resonant converter according to the rated operating conditions; loading a preset efficiency-temperature-ripple correlation model and initializing the integral compensator parameters.

[0101] Among them, the frequency parameters of multiple parallel proportional resonant controllers are the basic parameters of multi-parallel resonant control, corresponding to the target resonant frequencies of multiple virtual resonant branches. Through software algorithms, precise impedance matching and suppression of ripple components at different frequencies are achieved, which is different from the limitation of traditional single resonant topologies that can only be optimized for a single frequency.

[0102] Specifically, multiple parallel resonant frequency parameters are determined based on the current power grid frequency, including obtaining the actual value of the current power grid frequency.

[0103] The actual value of the current grid frequency refers to the real-time operating frequency of the AC voltage connected to the grid during the system's power-on initialization phase. The core source of battery current ripple in single-phase energy storage inverters is the inherent power frequency fluctuation of twice the AC power frequency on the AC side: when the grid frequency is 50Hz, the core ripple fundamental frequency is 100Hz; when the grid frequency is 60Hz, the core ripple fundamental frequency is 120Hz, accompanied by higher harmonic ripples of 4, 6, and 8 times the power frequency. In actual grid operation, frequency fluctuations exist within an allowable range (e.g., the grid allows a deviation of ±0.2Hz, while fluctuations in weak grid / microgrid scenarios can reach ±0.5Hz or more). If a fixed rated frequency is used to generate the resonant frequency point, it will lead to a mismatch between the resonant control frequency and the actual ripple frequency, directly causing a sharp drop in ripple suppression effect and an increased risk of positive feedback runaway.

[0104] Optionally, after the system is powered on, the phase voltage on the grid side is synchronously sampled by the AC side voltage sampling unit at a sampling rate of not less than 10kHz. A digital low-pass filter is used to filter out harmonic interference and noise in the grid voltage, ensuring the purity of the sampled signal. A zero-crossing detection algorithm combined with software phase-locked loop technology is used to perform frequency calculation on the filtered grid voltage signal, accurately identifying the actual value of the current grid frequency. The frequency identification accuracy is controlled within ±0.1Hz, meeting the accuracy requirements for subsequent doubling point generation. Consistency verification is performed on the frequency identification results for multiple consecutive grid cycles. When the frequency value deviation for more than three consecutive cycles is within ±0.1Hz, this value is locked as the actual value of the current grid frequency, avoiding frequency identification errors caused by instantaneous grid disturbances and ensuring the stability of the reference value.

[0105] Specifically, frequency parameters of multiple parallel proportional resonant controllers are generated based on integer multiples of the actual values.

[0106] Among them, the integer multiples of the actual value frequency point refer to the even multiples of the actual power grid frequency point selected as the core reference, with priority given to 2 times, 4 times, 6 times, and 8 times the power frequency point.

[0107] It should be noted that the instantaneous power fluctuation on the AC side of the single-phase inverter topology only includes even-numbered multiples of the power frequency component. More than 95% of the battery current ripple energy is concentrated at even-numbered multiples of the power frequency, such as 2, 4, and 6. Selecting even-numbered multiples of the power frequency as the center can achieve precise suppression of the core ripple component. The number of parallel PR control channels is preferably 2 to 4 sets, which ensures full-band ripple coverage while avoiding excessive main control computing power consumption due to too many frequency points.

[0108] The initial operating center frequency, which is the midpoint frequency of the initial frequency range, is the initial switching operating frequency of the LLC resonant converter after the system is powered on, and also serves as the reference center for subsequent dynamic frequency adjustments. By adjusting the center frequency while keeping the overall frequency range constant, the overall frequency range can be shifted, preventing the operating frequency from entering the capacitively unstable region to the left of the resonant point.

[0109] The initial frequency range, which is the initial allowable upper and lower limit threshold of the switching frequency after the system is powered on, is determined by the fluctuation of the initial center frequency. It is the safe operating boundary of the frequency in the early stage of system power-on and is limited to the ZVS inductive operating region to the right of the LLC resonant point.

[0110] The rated operating conditions in this step are the standard operating conditions calibrated during the system design phase, including: rated input / output voltage (battery rated voltage, DC bus rated voltage), rated charge / discharge power, inherent nominal parameters of the resonant cavity (resonant inductance, resonant capacitance), rated operating temperature, and rated grid frequency. These rated operating conditions serve as the benchmark for LLC resonant converter design and are also the basis for initial parameter calibration.

[0111] Optionally, firstly, based on the nominal parameters of the resonant cavity, the inherent series resonant frequency fr of the LLC resonant converter is calculated. This inherent series resonant frequency is the efficiency peak point of the LLC topology. Secondly, the initial center frequency is set to be higher than the inherent resonant frequency fr, within the ZVS linear operating region to the right of the resonant point. For example, when the inherent resonant frequency is 30kHz, the initial center frequency is set to 35kHz. This ensures that the initial operation is near the optimal efficiency range upon power-on, while also reserving sufficient safety margin to prevent frequency fluctuations from entering the left side of the resonant point. The initial center frequency needs to be verified through rated operating condition prototype testing to ensure that ZVS soft switching can be achieved across the entire power range within the rated operating conditions at this initial center frequency, and that the battery current ripple is within the target range.

[0112] The initial frequency range is set symmetrically or asymmetrically above and below the initial center frequency, following the principles of safety priority and coverage of rated operating condition fluctuations. Specifically, the lower frequency limit is always no lower than the inherent resonant frequency, preventing the operating frequency from entering the capacitive region to the left of the resonant point from the initial boundary, thus avoiding the risk of positive feedback runaway. The upper frequency limit is set based on the maximum load fluctuation range and maximum ripple suppression requirements under rated operating conditions, ensuring that ripple can be effectively suppressed through frequency adjustment across the entire rated power range, while not exceeding the maximum allowable switching frequency and ZVS critical frequency of the power devices. For example, when the resonant point is 30kHz and the initial center frequency is 35kHz, the initial frequency range is set to 30kHz~40kHz, which covers the frequency adjustment requirements under rated operating conditions and defines the safe operating boundary.

[0113] Specifically, the determined initial operating center frequency and initial frequency range will serve as the initial frequency control parameters after the system is powered on. The main control unit will generate an initial PWM drive signal based on these initial frequency control parameters to drive the LLC resonant converter to start running and store it in the preset control strategy library as the initial reference for subsequent dynamic frequency range adjustment.

[0114] The preset efficiency-temperature-ripple correlation model is the core computational model for dynamic frequency control. During the system design phase, it is calibrated through offline simulation and full-condition prototype testing. It is pre-stored in the main control unit's non-volatile memory (such as Flash or EEPROM) in the form of a discrete mapping table and a nonlinear fitting function. Upon system power-on initialization, the main control unit loads this model from the non-volatile memory into its internal high-speed RAM, ensuring rapid model lookup and function calculation during subsequent real-time control. This meets the real-time requirements of the control loop and avoids control lag caused by storage read / write delays.

[0115] Among them, the integral compensator is the core closed-loop unit for achieving ripple error-free control and avoiding the risk of positive feedback on the left side of the resonance point. Its parameter initialization directly determines the stability, response speed and control accuracy of the closed-loop control circuit.

[0116] Optionally, the initial proportional coefficient and initial integral coefficient of the integral compensator can be pre-calibrated. These initial parameters are based on loop stability simulation and prototype testing under rated operating conditions to ensure that the closed loop has optimal dynamic response speed and steady-state stability under rated operating conditions, with no overshoot and no oscillation. During system power-on initialization, the regulator parameters are assigned these initial calibration values, and the parameters are simultaneously stored in the operation register of the control loop.

[0117] Optionally, the operational state of the integral compensator can be cleared and reset, including: clearing the cumulative integral value to avoid integral saturation and output offset caused by historical data before power-on; and clearing the output value of the frequency compensation to ensure that there is no additional frequency compensation at the beginning of power-on and that the system starts up entirely based on the initial center frequency.

[0118] Optionally, the integral compensator is initialized to standby mode. In the initial stage of system power-on, only parameter and state initialization is completed, and integral compensation calculation is not triggered. After the system completes startup and enters steady-state operation, the working mode is automatically switched to start when the ripple exceeds the standard through ripple amplitude monitoring, and closed-loop compensation calculation is started to avoid malfunction of the integral compensator caused by transient disturbances during the power-on startup process.

[0119] As an optional implementation, based on any of the above embodiments, after frequency control of the resonant converter according to the target control strategy, the following steps are also included: First, continuously collect the real-time system status information of the energy storage inverter to generate a closed-loop feedback dataset.

[0120] This step continuously collects real-time system status information covering three major categories of data: operating condition characteristics, control input, and control output. The operating condition characteristic dimension data consists of the external input conditions for system operation, including battery current ripple information (ripple amplitude, spectral characteristics, harmonic ratio), resonant converter component temperature information (switch junction temperature, resonant inductor core temperature, resonant capacitor body temperature), load power information (real-time active power, power flow direction, power change rate), actual grid frequency, battery state of charge / health status, DC bus voltage, and real-time efficiency information. This data serves as the basis for constructing operating condition characteristics and dividing operating condition intervals. The control input dimension data consists of the control execution parameters output by the preset control strategy, including the frequency combination of the currently matched multi-parallel resonant controllers, basic drive frequency, frequency compensation amount, final drive frequency, target frequency range, and integral compensator operating parameters. The control output dimension data consists of the actual effect data after the control strategy is executed, including the ripple suppression effect, efficiency change, temperature change, loop stability data (frequency fluctuation amplitude, ripple convergence time), and whether the system triggers protection, etc. This data serves as the basis for evaluating the quality of control parameters and optimizing strategies.

[0121] Optionally, a data acquisition cycle synchronized with the frequency control (e.g., 10kHz to 50kHz) is adopted to ensure that the timestamps of operating condition data, control input data, and control output data within the same control cycle are completely aligned, avoiding distortion of the correspondence caused by timing misalignment. A configurable sliding time window can be used to cache the acquired data, preferably 1 to 24 hours, which can be flexibly adjusted according to the storage resources of the main control chip. This ensures that the dataset covers the full range of operating conditions from light load to full load and from charging to discharging, while avoiding excessive data volume that consumes too many storage resources. Next, the raw acquired data is standardized and cleaned to remove invalid and abnormal data. The cleaned valid data is then used to generate a closed-loop feedback dataset according to a structured format of "operating condition feature set, control parameter set, and effect evaluation set," and stored in the non-volatile storage unit of the main control chip to provide standardized data input for subsequent iterative optimization.

[0122] Secondly, the mapping relationship and control parameters in the preset control strategy are iteratively optimized based on the closed-loop feedback dataset to stabilize the battery current ripple within the target range.

[0123] This step uses a real-world closed-loop feedback dataset to iteratively optimize the pre-calibrated control strategy before delivery, ensuring that the control strategy always adapts to the current real-world operating characteristics of the system. This addresses the shortcomings of fixed pre-calibrated strategies that cannot adapt to long-term component aging, parameter drift, and performance degradation.

[0124] The mapping relationships can include a library of mapping relationships between system state information and resonant converter control parameters, a mapping relationship between quality factor and resonant frequency combination, a mapping relationship between load power / temperature and target frequency range, and an efficiency-temperature-ripple correlation model.

[0125] The control parameters may include the proportional coefficient, integral coefficient, preset thresholds (such as preset safety threshold, preset temperature threshold, preset efficiency threshold), and upper and lower limit calibration parameters of the frequency range for different operating conditions.

[0126] Optionally, a fixed optimization cycle can be set, such as 24 hours / 7 days. After the system's cumulative runtime reaches the set cycle, a full iteration optimization will be automatically started to adapt to the slow parameter drift during long-term system operation.

[0127] Optionally, iterative optimization can take "stable battery current ripple within the target range" as the core objective, while also taking into account the balance of multiple objectives such as "maximizing system operating efficiency, minimizing component temperature fluctuations, and optimizing control loop stability". A quantitative evaluation function can be established to evaluate the quality of the optimized control parameters. The evaluation function logic can be: ripple suppression effect weight ratio greater than 60%, operating efficiency weight ratio greater than 20%, and stability and temperature safety weight ratio less than 20%.

[0128] Optionally, based on the closed-loop feedback dataset, the operating condition interval-control parameter mapping table in the preset control strategy is incrementally optimized. For each operating condition interval, the dataset is traversed to select the control parameter combination with the best ripple suppression effect and highest efficiency within that interval, replacing the calibration parameters in the original mapping table to achieve precise iteration of the mapping relationship. Based on real operating data, the coefficients of the three-dimensional mapping relationship of the efficiency-temperature-ripple correlation model are corrected to adapt to changes in loss characteristics caused by component aging and resonant cavity parameter drift, so that the model accurately reflects the current real coupling characteristics of the system. The integral compensator parameters, frequency range thresholds, and thresholds for different operating condition intervals are finely optimized. For example, to address the problem of slower ripple convergence under heavy load conditions after long-term operation, the integral coefficients under this condition are optimized to improve the closed-loop response speed; to address the problem of narrowing ZVS interval caused by resonant cavity parameter drift, the upper and lower limits of the frequency range are optimized to avoid entering the unstable region.

[0129] Optionally, after the parameters are updated, the system's operating status is continuously monitored. If abnormalities such as excessive ripple, sudden drop in efficiency, or oscillation occur, the system is immediately reverted to the control strategy before optimization to ensure safe system operation.

[0130] Figure 4 A schematic diagram of the structure of a control device for battery current ripple in an energy storage inverter provided in an embodiment of this application is shown below. Figure 4As shown, the control device for the battery current ripple of the energy storage inverter provided in this embodiment is located in the electronic device. The control device 40 for the battery current ripple of the energy storage inverter provided in this embodiment includes: an acquisition module 41, a determination module 42, and a control module 43.

[0131] Specifically, the acquisition module 41 is used to acquire system status information of the energy storage inverter; wherein, the system status information includes one or more of the following: battery current ripple information, component temperature information of the resonant converter, and load power information; the determination module 42 is used to acquire a target control strategy that matches the system status information from a preset control strategy based on the system status information; wherein, the preset control strategy is used to indicate the mapping relationship between the system status information and the control parameters of the resonant converter, and the control parameters include the frequency parameters, integral compensation parameters, and frequency range parameters of multiple parallel proportional resonant controllers; the control module 43 is used to perform frequency control on the resonant converter according to the target control strategy to control the battery current ripple within the target range.

[0132] Optionally, when determining the target control strategy that matches the system status information from the preset control strategy, the determining module 42 is specifically used to: determine the quality factor of the resonant converter based on the load power information; determine the appropriate frequency combination from the frequency parameters of multiple parallel proportional resonant controllers based on the quality factor, and generate the basic driving frequency of the resonant converter through a nonlinear fitting algorithm.

[0133] Optionally, when the control module 43 performs frequency control on the resonant converter according to the target control strategy, it is specifically used to: monitor the ripple amplitude in the battery current ripple information in real time; when the ripple amplitude exceeds the preset safety threshold, output the frequency compensation amount through the integral compensator; and superimpose the frequency compensation amount with the basic drive frequency.

[0134] Optionally, the control module 43 is also used to: acquire real-time efficiency information of the resonant converter; determine the target frequency range corresponding to the current operating condition based on the real-time efficiency information, component temperature information and a preset efficiency-temperature-ripple correlation model; and narrow the target frequency range if the component temperature exceeds a preset temperature threshold or the real-time efficiency is lower than a preset efficiency threshold.

[0135] Optionally, the control device for battery current ripple of the energy storage inverter provided in this embodiment further includes an initialization module and an optimization module.

[0136] Optionally, before acquiring the system status information of the energy storage inverter, an initialization module is used to: determine the frequency parameters of multiple parallel proportional resonant controllers based on the current grid frequency; determine the initial operating center frequency and initial frequency range of the resonant converter based on the rated operating conditions; load a preset efficiency-temperature-ripple correlation model; and initialize the integral compensator parameters.

[0137] Optionally, the initialization module, when determining the frequency parameters of multiple parallel proportional resonant controllers based on the current power grid frequency, is specifically used to: obtain the actual value of the current power grid frequency; and generate the frequency parameters of multiple parallel proportional resonant controllers based on integer multiples of the actual value.

[0138] Optionally, after frequency control of the resonant converter according to the target control strategy, the optimization module is used to: continuously collect real-time system state information of the energy storage inverter to generate a closed-loop feedback dataset; and iteratively optimize the mapping relationship and control parameters in the preset control strategy based on the closed-loop feedback dataset to stabilize the battery current ripple within the target range.

[0139] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, as shown below. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: a processor 51 and a memory 52 communicatively connected to the processor 51.

[0140] The memory 52 stores computer-executable instructions; the processor 51 executes the computer-executable instructions stored in the memory 52 to implement the method provided in any of the above embodiments.

[0141] The program may include program code, which includes computer-executable instructions. Memory 52 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0142] In this embodiment, the memory 52 and the processor 51 are connected via a bus. 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. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single straight line, but this does not mean that there is only one bus or one type of bus.

[0143] This application also provides a computer-readable storage medium, including computer-executable instructions stored in the computer-readable storage medium, which, when executed by a processor, are used to implement the method provided in any of the above embodiments.

[0144] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the method provided in any of the above embodiments.

[0145] The modules described as separate components may or may not be physically separate. The components shown as modules 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 modules can be selected to implement the solution of this embodiment according to actual needs.

[0146] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit composed of the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0147] The integrated modules described above, implemented as software functional modules, can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods of the various embodiments of this application.

[0148] It should be understood that the aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0149] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage device, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0150] The aforementioned 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 storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0151] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of the processor. The processor and storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and storage medium can exist as discrete components in an electronic control unit or main control device.

[0152] 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.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling battery current ripple in an energy storage inverter, characterized in that, include: Acquire system status information of the energy storage inverter; wherein, the system status information includes one or more of the following: battery current ripple information, component temperature information of the resonant converter, and load power information; Based on the system state information, a target control strategy matching the system state information is obtained from a preset control strategy; wherein, the preset control strategy is used to indicate the mapping relationship between the system state information and the control parameters of the resonant converter, and the control parameters include frequency parameters, integral compensation parameters and frequency range parameters of multiple parallel proportional resonant controllers; According to the target control strategy, the resonant converter is frequency controlled to keep the battery current ripple within the target range.

2. The method according to claim 1, characterized in that, The step of obtaining a matching target control strategy from a preset control strategy based on the system state information includes: The quality factor of the resonant converter is determined based on the load power information; Based on the quality factor, a suitable frequency combination is determined from the frequency parameters of the multiple parallel proportional resonant controllers, and the fundamental driving frequency of the resonant converter is generated by a nonlinear fitting algorithm.

3. The method according to claim 2, characterized in that, The step of frequency control of the resonant converter according to the target control strategy includes: Real-time monitoring of the ripple amplitude in the battery current ripple information; If the ripple amplitude exceeds a preset safety threshold, the frequency compensation amount is output through the integral compensator. The frequency compensation amount is superimposed on the basic driving frequency.

4. The method according to claim 1, characterized in that, The step of frequency control of the resonant converter according to the target control strategy further includes: Obtain the real-time efficiency information of the resonant converter; Based on the real-time efficiency information, the component temperature information, and the preset efficiency-temperature-ripple correlation model, the target frequency range corresponding to the current operating condition is determined. If the component temperature exceeds a preset temperature threshold or the real-time efficiency is lower than a preset efficiency threshold, the target frequency range is reduced.

5. The method according to any one of claims 1-4, characterized in that, Before obtaining the system status information of the energy storage inverter, the process also includes: The frequency parameters of multiple parallel proportional resonant controllers are determined based on the current power grid frequency; the initial operating center frequency and initial frequency range of the resonant converter are determined based on the rated operating conditions; a preset efficiency-temperature-ripple correlation model is loaded and the parameters of the integral compensator are initialized.

6. The method according to claim 5, characterized in that, The process of determining the frequency parameters of multiple parallel proportional resonant controllers based on the current power grid frequency includes: Obtain the actual value of the current power grid frequency; Frequency parameters of multiple parallel proportional resonant controllers are generated based on integer multiples of the actual values.

7. The method according to any one of claims 1-4, characterized in that, After performing frequency control on the resonant converter according to the target control strategy, the method further includes: The real-time system status information of the energy storage inverter is continuously collected to generate a closed-loop feedback dataset; Based on the closed-loop feedback dataset, the mapping relationship in the preset control strategy and the control parameters are iteratively optimized to stabilize the battery current ripple within the target range.

8. A control device for battery current ripple in an energy storage inverter, characterized in that, include: The acquisition module is used to acquire system status information of the energy storage inverter; wherein, the system status information includes one or more of the following: battery current ripple information, component temperature information of the resonant converter, and load power information; The determination module is used to obtain a target control strategy that matches the system state information from a preset control strategy based on the system state information; wherein, the preset control strategy is used to indicate the mapping relationship between the system state information and the control parameters of the resonant converter, and the control parameters include frequency parameters, integral compensation parameters and frequency range parameters of multiple parallel proportional resonant controllers; The control module is used to perform frequency control on the resonant converter according to the target control strategy, so as to control the battery current ripple within the target range.

9. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.

10. 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 1-7.

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