Hierarchical collaborative control method and system of hybrid energy storage system with high-frequency pulse load, computer device and storage medium

Abstract

This invention discloses a hierarchical collaborative control method, system, computer equipment, and storage medium for a hybrid energy storage system with a high-frequency pulse load. The method includes: establishing a hybrid energy storage system model for the high-frequency pulse load, including constructing a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model; performing physical inertia analysis on the current response speed of a three-phase interleaved parallel converter model established based on the lithium battery model; and constructing an equivalent model of the high-frequency pulse load. The method involves power allocation of the hybrid energy storage system through a hierarchical collaborative control architecture using voltage and current dual closed-loop control of the DC bus. The hierarchical collaborative control architecture includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load demand based on a frequency domain decoupling algorithm and power adjudication mechanism using filters, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residuals. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter through dynamic feedforward overdrive, achieving rapid power compensation for the pulse load instantaneously.

Description

Technical Field

[0001] This application belongs to the technical field of hybrid energy storage systems, specifically referring to a hierarchical collaborative control method, system, computer equipment, and storage medium for a hybrid energy storage system with a high-frequency pulse load. Background Technology

[0002] With the advancement of the "dual-carbon" goal and the rapid development of electrified transportation, high-voltage direct current (HVDC) microgrids have attracted widespread attention due to their high efficiency and ease of control. In HVDC microgrids, fuel cells (FCs), as a high-energy-density clean energy source, are widely regarded as ideal main power sources. However, FCs have extremely slow dynamic response (on the order of seconds), making them unable to cope with rapid load fluctuations. To maintain stable bus voltage and ensure power quality, a hybrid energy storage system (HESS) consisting of fuel cells, lithium batteries, and supercapacitors is typically used. This architecture utilizes the complementarity of power density and energy density among the various power sources, theoretically enabling efficient system operation. Despite the theoretical advantages of the HESS architecture, in practical applications, especially when facing high-frequency, high-power pulse loads generated by radar, electromagnetic launch, or electric propulsion systems, system control faces severe challenges. On the one hand, the mismatch in source-load dynamic response speeds leads to severe bus voltage fluctuations. In particular, the DC-DC converter on the lithium battery side is limited by the physical inertia of the filter inductor, resulting in an inherent hysteresis in current response. When the load switches drastically at a frequency of 1000Hz, traditional feedback control cannot compensate for the power shortfall in time, resulting in frequent drops and recoveries of the bus voltage, which seriously affects power quality. On the other hand, without effective frequency domain isolation, high-frequency pulse components will directly impact the lithium battery, causing it to be in a severe micro-circulation condition, accelerating internal aging of the battery and shortening its service life.

[0003] To address the issue of rational power allocation in hybrid energy storage systems, various energy management systems (EMS) have been proposed in existing technologies. These can be broadly categorized into three types: rule-based, optimization algorithm-based, and filter-based. Among these, rule-based or fuzzy control methods are simple in structure and robust, but heavily reliant on expert experience, making it difficult to guarantee global optimality. While optimization algorithms such as model predictive control can achieve multi-objective optimization, they incur significant computational burdens, often failing to meet the microsecond-level real-time requirements of high-frequency pulse loads. In contrast, filter-based frequency domain decoupling methods are widely used in the real-time control of hybrid energy storage systems due to their ability to accurately match the frequency response characteristics of each energy storage component and their minimal computational cost. However, existing frequency domain decoupling strategies face a significant theoretical-physical gap in practical deployment. Although the upper-level algorithms mathematically achieve perfect allocation of high and low frequency power, most studies implicitly assume a crucial assumption: treating the underlying DC-DC converter as an ideal current response source, neglecting the physical inertial limitations of components such as filter inductors during millisecond-level transient processes. While this simplification is acceptable under normal operating conditions, it becomes unacceptable under extremely challenging high-frequency pulse conditions. This physical-layer inertial lag prevents the high-frequency decoupling commands planned at the upper level from being accurately reproduced in the lower-level actuators. The current inertia of the inductor causes the actual response to lag significantly behind the reference command, leading to a deep voltage drop at the bus. Furthermore, current technologies focus primarily on macroscopic power quality; however, in-depth mechanistic research and quantitative analysis are still lacking regarding how to overcome physical inertia under extreme pulse conditions to achieve synergistic optimization of microscopic waveform quality and system-level energy efficiency. Summary of the Invention

[0004] To overcome the shortcomings of the prior art, this application provides a hierarchical collaborative control method, system, computer equipment, and storage medium for a hybrid energy storage system with high-frequency pulse loads, which can resolve the contradiction between the theoretical optimization of the upper-level energy management algorithm and the physical lag of the lower-level actuator.

[0005] This invention provides a hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load, the hierarchical collaborative control method comprising:

[0006] A hybrid energy storage system model for high-frequency pulse load is established, including the construction of a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. The physical inertia analysis of the current response speed is performed on the three-phase interleaved parallel converter model established based on the lithium battery model, and an equivalent model of high-frequency pulse load is built. The power distribution of the hybrid energy storage system is achieved through dual closed-loop control of voltage and current of the DC bus using a hierarchical collaborative control architecture, which includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

[0007] Furthermore, according to the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment, the filter-based frequency domain decoupling algorithm includes: The DC bus voltage closed-loop controller calculates the total current reference command required to maintain voltage stability in real time based on the bus voltage deviation. ; Use a low-pass filter bank to reference the total current command. Frequency domain decomposition and allocation, including: Extracting the fuel cell's fundamental reference current using a low-pass filter. ; Extracting the lithium battery's base reference current using a two-stage low-pass filter. .

[0008] Furthermore, based on the hierarchical collaborative control method for the hybrid energy storage system with high-frequency pulse load provided in this embodiment, the basic reference current of the fuel cell is extracted. The process is as follows: ; in, Here is the transfer function of the first-order low-pass filter in the fuel cell branch; For the Laplace operator; ω is the cutoff angular frequency of the fuel cell branch.

[0009] Furthermore, based on the hierarchical collaborative control method for the hybrid energy storage system with high-frequency pulse load provided in this embodiment, the basic reference current of the lithium battery is extracted. The process is as follows: ; ; in, The transfer function of the low-pass filter in the lithium battery branch; For the Laplace operator; The cutoff frequency of a lithium battery determines its dynamic engagement.

[0010] Furthermore, according to the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment, the power adjudication mechanism includes: Limiting and differential calculations for fuel cells: First, the basic reference current of the fuel cell is... Hard limiting is applied to obtain the reference current for the fuel cell. To protect the fuel cell stack from overload and prevent reverse current: ; in, This represents the minimum current value for the fuel cell; This represents the maximum current value of the fuel cell; If the fuel cell cannot meet the filtering command due to limiting, resulting in a power deficit It will be passed to the next level: ; Lithium-ion battery compensation and state machine protection: Lithium-ion batteries not only bear their own mid-frequency components, but also need to assist in compensating for the power deficit of the fuel cell. Compensation command for lithium batteries for: ; Introducing a SOC state machine protection mechanism to prevent battery overcharging and over-discharging: ; Apply a maximum charge / discharge current limit to the output command: .

[0011] Furthermore, according to the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment, the power adjudication mechanism further includes: Using supercapacitors as a fallback: Regardless of how the preceding stage limits the output, the supercapacitor must attempt to cover the total demand. All differences between the actual outputs of each source and the actual outputs are used to maintain bus voltage balance. ; Supercapacitor voltage constraint for: .

[0012] Furthermore, according to the hierarchical cooperative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment, the dynamic feedforward overdrive includes: The current switching rate is detected by a high-pass filter with gain, and an overdrive compensation signal is generated. : ; The transfer function of the transient extraction filter is: ; in, The overdrive gain determines the strength of the compensation; The transient cutoff frequency determines the duration of the overdrive signal; For the Laplace operator; Execute the enhanced general command: Apply the current command to the inner loop of the lithium battery converter. The sum of the basic component and the overdriven component: .

[0013] This application also provides a hierarchical collaborative control system for a hybrid energy storage system with a high-frequency pulse load, the hierarchical collaborative control system comprising: The model building module establishes a hybrid energy storage system model for high-frequency pulse loads, including constructing a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. It also performs physical inertial analysis of the current response speed of a three-phase interleaved parallel converter model established based on the lithium battery model and builds an equivalent model for the high-frequency pulse load. The hierarchical collaborative control architecture module performs power distribution of the hybrid energy storage system through dual closed-loop control of DC bus voltage and current. The hierarchical collaborative control architecture includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

[0014] This application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load as described in this application.

[0015] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load as described in this application.

[0016] The beneficial effects of this invention are as follows: The hierarchical collaborative control method, system, computer equipment, and storage medium for a hybrid energy storage system with high-frequency pulse loads provided in this application achieve coordinated optimization of high dynamic bus voltage support and energy storage element health management by designing a filter-based frequency domain decoupling and power adjudication mechanism in the energy management layer and introducing dynamic feedforward overdrive technology in the bottom layer control. A frequency domain decoupling-power adjudication hierarchical architecture is constructed, reducing battery micro-circulation and achieving quasi-DC smooth operation. An anti-inertial dynamic feedforward overdrive mechanism is proposed, explicitly compensating for converter inductance physical constraints, and establishing a mapping bridge between frequency domain power allocation and time domain physical realizability. Attached Figure Description

[0017] The technical solution and other beneficial effects of this application will become apparent from the following detailed description of specific embodiments in conjunction with the accompanying drawings.

[0018] Figure 1 This is a schematic flowchart of the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment.

[0019] Figure 2 This is a schematic diagram of the hybrid energy storage system model provided in this embodiment.

[0020] Figure 3 This is a schematic diagram of the three-phase interleaved parallel converter model provided in this embodiment.

[0021] Figure 4 The equivalent structure diagram is shown for the high-frequency pulse load equivalent model constructed in this embodiment.

[0022] Figure 5 The equivalent structure diagram of the conventional DC load model provided in this embodiment.

[0023] Figure 6 This is a schematic diagram of the hierarchical collaborative control architecture provided in this embodiment.

[0024] Figure 7 This is a schematic diagram of the frequency domain decoupling algorithm provided in this embodiment.

[0025] Figure 8 This is a schematic diagram of the dynamic feedforward overdrive strategy provided in this embodiment.

[0026] Figure 9 This is a waveform diagram of the bus voltage response under normal DC load operation mode.

[0027] Figure 10 This is a power curve diagram for a high-frequency pulse load.

[0028] Figure 11Transient response diagrams for two aspects of the bus voltage: (a) magnitude aspect; (b) time aspect.

[0029] Figure 12 The macroscopic waveforms of the lithium battery output current under three strategies under load step are shown: (a) Proposed; (b) PI; (c) PI+LF.

[0030] Figure 13 The following are microscopic waveforms of the steady-state current of lithium batteries under three strategies: (a) Proposed; (b) PI; (c) PI+LF. Detailed Implementation

[0031] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0032] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0033] The following disclosure provides many different embodiments or examples for implementing different structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, various specific examples of processes and materials are provided in this application, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0034] The embodiments of this application will now be further described in conjunction with the accompanying drawings and specific implementation details.

[0035] Example 1: Figure 1 This is a schematic flowchart of the hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this embodiment.

[0036] like Figure 1 As shown, the hierarchical collaborative control method includes: A hybrid energy storage system model for high-frequency pulse load is established, including the construction of a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. The physical inertia analysis of the current response speed is performed on the three-phase interleaved parallel converter model established based on the lithium battery model, and an equivalent model of high-frequency pulse load is built. The power distribution of the hybrid energy storage system is achieved through dual closed-loop control of voltage and current of the DC bus using a hierarchical collaborative control architecture, which includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

[0037] Figure 2 This is a schematic diagram of the hybrid energy storage system model provided in this embodiment.

[0038] In this embodiment, the hybrid energy storage system model for the high-frequency pulse load adopts a fully active hybrid energy storage topology. For example... Figure 2 As shown, the hybrid energy storage system comprises three core components: source, storage, and load, coupled via a DC bus. To meet the demands of high-frequency, high-power pulse loads, this embodiment constructs a hybrid energy storage microgrid with a 960V DC bus. In the hybrid energy storage system, the fuel cell provides steady-state average power via a Boost converter; the lithium battery employs a three-phase interleaved parallel bidirectional DC-DC converter to smooth low- and medium-frequency fluctuations; and the supercapacitor absorbs high-frequency ripple via a Buck-Boost converter. These three components work together to ensure the system's energy balance and voltage stability.

[0039] The fuel cell model constructed in this embodiment includes: the output voltage of the fuel cell. It exhibits typical nonlinear polarization characteristics. Ignoring the complex details of the electrochemical reactions, its electrical output characteristics can be expressed as follows: ; in, It is the thermodynamic electromotive force; For activation polarization voltage drop; For ohmic polarization voltage drop; The concentration polarization pressure drop is represented by this model. This model indicates that fuel cells have relatively soft output characteristics, and their dynamic response is limited by the mechanical time constant of the gas supply system, making them unsuitable for handling severe load fluctuations.

[0040] The lithium battery model constructed in this embodiment includes: a second-order Thevenin equivalent circuit model is used to simulate the dynamic voltage response and polarization effect of a lithium battery under pulsed current. Its port voltage... Described as: ; in, It is the open-circuit voltage, a function of the state of charge (SOC); The internal resistance is ohmic; and These represent the time constants for electrochemical polarization and concentration polarization processes, respectively. Represents the electrochemical polarization voltage; Represents concentration polarization voltage; Represents electrochemically polarized capacitors; Represents concentration polarization capacitance; This represents the battery's operating current. This model reflects the voltage hysteresis characteristic of lithium batteries under transient current surges.

[0041] The supercapacitor model constructed in this embodiment includes: supercapacitors have extremely high cycle life and power density, and their model is simplified to an ideal capacitor. With equivalent series resistance Series combination: ; in, This represents the terminal voltage of the supercapacitor. Represents the initial voltage of the supercapacitor; It is an ideal capacitor; This represents the operating current of the supercapacitor; This is the equivalent series resistance. In this model, due to the equivalent series resistance... Extremely small, supercapacitors can provide extremely large instantaneous current throughput.

[0042] Figure 3 This is a schematic diagram of the three-phase interleaved parallel converter model provided in this embodiment.

[0043] The three-phase interleaved parallel converter model established based on the lithium battery model includes: a three-phase interleaved parallel bidirectional DC-DC converter on the lithium battery side. For example... Figure 3 As shown, compared to the traditional single-phase topology, this structure significantly reduces inductor current ripple and improves the system's power handling capability through phase shift control between the three phases.

[0044] State-space averaging modeling: Assuming the three-phase circuit parameters are symmetrical (i.e., La=Lb=Lc=L), in continuous current mode (CCM) of the inductor, taking a single phase as an example, according to Kirchhoff's voltage law (KVL), its average state equation can be derived as follows: ; in, This is the average value of the inductor current. The duty cycle for the lower tube to conduct. It is the equivalent total resistance including the inductor's equivalent resistance and the switching transistor's on-resistance. This is the inductance value; This represents the average terminal voltage of the lithium battery. This represents the average value of the bus terminal voltage.

[0045] Performing a physical inertial analysis: Rearranging the above equation, we can obtain the rate of change of the inductor current: ; Based on the three-phase interleaved parallel converter model established using the lithium battery model, it can be seen that the inductor volt-second constraint determines the physical upper limit of the current response speed of the three-phase interleaved parallel converter. This makes it difficult for traditional PI control to establish a sufficient inductor voltage difference in time during load changes, thus introducing electromagnetic inertia and causing current lag. To address this physical limitation, in this embodiment, dynamic feedforward overdrive is used to actively enhance the duty cycle adjustment during the transient phase to maximize the inductor voltage difference and improve the current change rate, thereby effectively compensating for physical inertia. During the steady-state phase, conventional closed-loop control is maintained to ensure system stability.

[0046] In this embodiment, an equivalent model of a high-frequency pulse load is constructed, and an equivalent switched resistor model is used to simulate the transient impact characteristics of the load.

[0047] Figure 4 The equivalent structure diagram is shown for the high-frequency pulse load equivalent model constructed in this embodiment.

[0048] like Figure 4 As shown, this model mainly consists of an ideal high-power resistor. It consists of a high-speed power switching device (IGBT) and a pulse control module connected in series.

[0049] The pulse control module generates a frequency of The PWM drive signal controls the gate of the IGBT. When the drive signal is high, the IGBT is turned on, and the low-resistance load... The instantaneous connection to the busbar generates a high-power surge. Based on the aforementioned switching logic, the instantaneous power consumed by the pulse load... It can be described as: ; in, It is a switching function; This is the voltage at the pulse load terminal.

[0050] This model can accurately reproduce the hard-switching impact characteristics of the load on a millisecond timescale, i.e., the instantaneous step change in current. This effectively verifies the dynamic suppression capability of the hybrid energy storage system against high-frequency disturbances.

[0051] This embodiment also constructs a conventional DC load model.

[0052] Figure 5 The equivalent structure diagram of the conventional DC load model provided in this embodiment.

[0053] This embodiment models a conventional DC load model as an RLC equivalent impedance network including parasitic parameters, such as... Figure 5 As shown, compared to the ideal constant power model, this RLC model introduces the energy storage effect of passive components. During system voltage fluctuations or at the moment of load connection, the presence of inductance and capacitance generates additional transient oscillation components. This allows for a more rigorous test of the bus voltage regulation capability of the control strategy under non-unity power factor and complex impedance conditions.

[0054] Figure 6 This is a schematic diagram of the hierarchical collaborative control architecture provided in this embodiment.

[0055] Based on the above modeling, in this embodiment, to address the source-load dynamic mismatch problem, the hierarchical collaborative control method provided in this embodiment uses a hierarchical collaborative control architecture to perform power distribution of the hybrid energy storage system through dual closed-loop control of DC bus voltage and current. The hierarchical collaborative control architecture includes an energy management layer and a dynamic compensation layer. Figure 6 As shown, in the hierarchical collaborative control architecture, the energy management layer allocates load demand based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residuals; the dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamic feedforward overdrive, and realizes rapid power compensation for pulse load instantaneous pulses; the bottom execution layer adopts voltage-current dual closed-loop control to ensure high-precision execution of commands and bus voltage regulation.

[0056] To achieve a reasonable distribution of source-load power and protect fuel cells and lithium batteries from direct impacts by high-frequency pulse loads, this embodiment provides a filter-based frequency domain decoupling algorithm, including: The DC bus voltage closed-loop controller calculates the total current reference command required to maintain voltage stability in real time based on the bus voltage deviation. ; Use a low-pass filter bank to reference the total current command. Perform frequency domain decomposition and allocation, such as Figure 7 As shown, it includes: Extracting the fuel cell's fundamental reference current using a low-pass filter. ; Extracting the lithium battery's base reference current using a two-stage low-pass filter. .

[0057] Among them, the basic reference current of the fuel cell is extracted. This includes: the extremely low-frequency components of the fuel cell that only bear the load, in order to maintain the stability of its electrochemical reaction. This component is extracted using a low-pass filter (LPF): ; in, The cutoff angular frequency of the fuel cell branch is typically set to an extremely low value. This is the transfer function of the first-order low-pass filter in the fuel cell branch. For the Laplace operator.

[0058] Extracting the basic reference current of the lithium battery This includes: lithium batteries responsible for handling low-to-medium frequency fluctuations in the load. Its basic reference instructions. Extracted through a two-stage low-pass filter, with the portion borne by the fuel cell deducted: ; ; in, The cutoff frequency of a lithium battery determines its dynamic engagement. This is the transfer function of the low-pass filter in the lithium battery branch. For the Laplace operator.

[0059] In this embodiment, to ensure the safe operation of the hybrid energy storage system, a power arbitration module is designed after the filtering layer. This module, based on rule-based logic, performs limiting, state verification, and power redistribution on the reference commands of each source. The specific arbitration logic flow includes: Limiting and differential calculations for fuel cells: First, the basic reference current of the fuel cell is... Hard limiting is applied to obtain the reference current for the fuel cell. To protect the fuel cell stack from overload and prevent reverse current: ; in, This represents the minimum current value for the fuel cell; This represents the maximum current value of the fuel cell; If the fuel cell cannot meet the filtering command due to limiting, resulting in a power deficit It will be passed to the next level: ; Lithium-ion battery compensation and state machine protection: Lithium-ion batteries not only bear their own mid-frequency components, but also need to assist in compensating for the power deficit of the fuel cell. Compensation command for lithium batteries for: ; Introducing a SOC state machine protection mechanism to prevent battery overcharging and over-discharging: ; Apply a maximum charge / discharge current limit to the output command: .

[0060] Using supercapacitors as a fallback: As the power balancing node in a hybrid energy storage system, supercapacitors undertake the "ultimate fallback" task. Regardless of how the upstream stage limits power, the supercapacitor must attempt to fill the total demand. All differences between the actual outputs of each source and the actual outputs are used to maintain bus voltage balance. ; Supercapacitor voltage constraint for: When the voltage exceeds the limit, the corresponding charging and discharging path is cut off. Through the above-mentioned adjudication mechanism, the hybrid energy storage system achieves a coordinated control strategy of fuel cell best-effort, lithium battery auxiliary compensation, and supercapacitor ultimate balance.

[0061] The three-phase interleaved parallel converter for lithium batteries is limited by the physical characteristics of its filter inductor L, and cannot respond instantaneously to the intermediate frequency commands issued by the EMS. Traditional PI control relies on error integration to accumulate the control input, inherently exhibiting phase lag. To overcome this physical inertia, this hierarchical cooperative control method proposes a dynamic feedforward overdrive mechanism, directly utilizing the lithium battery current command (…). The transient jump characteristics of the inductor generate a pulsed compensation signal to maximize the rate of change of the inductor current, thereby quickly filling the pulse power gap while maintaining steady-state accuracy.

[0062] The underlying mechanism is as follows: According to the inductor volt-second balance principle, the rate of change of the inductor current depends on the voltage difference across its terminals. ; in, The filter inductor is for a three-phase interleaved parallel converter. The rate of change of current, Where is the input voltage, and D is the duty cycle. This is the output voltage.

[0063] By simplification, we can obtain the duty cycle D and the rate of change of current. Relationship: ; in, This is the DC bus voltage.

[0064] The above formula shows that the duty cycle It consists of two parts: steady-state maintenance component ( ) and dynamic driving components ( When the load undergoes a 1000Hz step change, an extremely large [capacity / capacity] is required. This is to support the bus voltage. This behavior of applying a limit control quantity for a short period of time is defined as overdrive.

[0065] Therefore, the dynamic feedforward overdrive provided in this embodiment includes: The current switching rate is detected by a high-pass filter with gain, and an overdrive compensation signal is generated. : ; The transfer function of the transient extraction filter is: ; in, The overdrive gain determines the strength of the compensation; The transient cutoff frequency determines the duration of the overdrive signal; Execute the enhanced general command: Apply the current command to the inner loop of the lithium battery converter. The sum of the basic component and the overdriven component: .

[0066] like Figure 8As shown in the red box, this dynamic feedforward overdrive strategy actually constructs a variable structure control system. To ensure safety, the overdrive signal amplitude is hardware-limited to ensure that it does not cause overstress in the device under extreme conditions. Through this design, the control strategy provides high bandwidth and strong feedforward performance in short transients, while automatically degenerating into highly stable PI control in steady state, achieving effective decoupling between dynamic response speed and steady-state accuracy.

[0067] To ensure that the hybrid energy storage system achieves optimal dynamic performance while satisfying multi-source physical constraints, the hierarchical cooperative control method provided in this embodiment targets four key parameters in the control strategy ( , , , ) Quantitative design criteria based on physical models were developed.

[0068] The output power response of a fuel cell is limited by the mechanical delay of the air supply subsystem. If the current extraction rate exceeds the air supply rate, the excess oxygen ratio will fall below the safe threshold (OER < 1), triggering "oxygen starvation." Let the equivalent time constant of the fuel cell air supply system be... (Typically 1-2 seconds). To ensure safety, the bandwidth of the low-pass filter should be much smaller than the bandwidth of the air system: ; in, This is for the safety factor.

[0069] Pick , It can be calculated Therefore, it is possible to set for .

[0070] As a mid-frequency energy source, lithium batteries require their highest reference command frequency to be within the traceable bandwidth of the inner current loop to avoid system oscillations caused by phase lag. Let the closed-loop bandwidth of the inner current loop be... According to the stability principle of cascaded control, the outer loop command bandwidth should be limited to within 1 / 10 of the inner loop bandwidth. ; The current loop of this system is designed to have a bandwidth of approximately 100Hz ≈ 628rad / s. Substituting this into the criterion, we get... ≤62.8 rad / s. Considering the frequency division smoothness with the supercapacitor, this embodiment conservatively selects ≤62.8 rad / s. =10 rad / s, which ensures tracking accuracy while effectively isolating high-frequency ripple.

[0071] High-pass filter Its function is to extract the step characteristics of the load. The selection depends on the rise time of the pulse load. To accurately capture the rising edge of the pulse and ensure the feedforward signal decays rapidly in steady state, the time constant should be proportional to the load rise time. Within the same order of magnitude:

[0072] In this embodiment, the pulse load rise time ≈1ms. (Take) To obtain a sufficient action window, ≈3ms, corresponding = 1 / 0.003 ≈ 333.33 rad / s Gain The physical meaning is to compensate for inductance. L The resulting back electromotive force hinders the process. Its optimal value is determined according to the critical damping criterion for second-order systems. After introducing feedforward, the equivalent transfer function of the lithium battery current closed loop can be approximated as a second-order system: ; Where the damping ratio With feedforward gain They are positively correlated. To eliminate overshoot during voltage recovery and achieve the shortest settling time, the design objective is the critical damping state (…). = 1).

[0073] Through root locus analysis, when When the value is less than 10, the system is overdamped, resulting in slow response and large drops; when... When the damping value is greater than 15, the system is underdamped, resulting in overshoot and bulging. Therefore, in this embodiment, the damping point near the critical damping point is selected. = 12 is the optimal gain, achieving a fast response without overshoot.

[0074] In this embodiment, in order to fully verify the effectiveness of the proposed frequency domain hierarchical collaborative and dynamic feedforward overdrive control strategy, a high-fidelity simulation model of a high-voltage DC microgrid was built in the MATLAB / Simulink environment to verify the hierarchical collaborative control method.

[0075] The model comprises three core energy units: a fuel cell, a lithium battery, and a supercapacitor. The lithium battery side employs a three-phase interleaved parallel bidirectional DC-DC converter structure to reduce current ripple during high-power output and improve the system's power density. Key parameter settings for the system and controller are shown in Table 1.

[0076] Table 1. Key parameters of the hybrid energy storage simulation system;

[0077] To ensure the rigor of the comparative experiments, the principle of controlling variables was strictly followed in this verification experiment. The voltage outer loop of all three strategies used completely identical PI parameters (…). K p =50, K i =100). It should be noted that the current oscillation phenomenon observed in the control group (PI+LF) stems from the inherent high-frequency shoot-through defect of the direct feedforward architecture, rather than from improper parameter tuning. The difference in experimental results is entirely attributable to the improvement of the control architecture, rather than the deviation in parameter selection.

[0078] Steady-state performance analysis is performed, including: To verify the bus voltage regulation accuracy of the hierarchical collaborative control method provided in this embodiment under basic operating conditions, a steady-state characteristic test was first performed on the system. The system was initialized in a conventional DC load operating mode, and its bus voltage response waveform is as follows: Figure 9 As shown. Observation Figure 9 As can be seen, after the system completes startup and enters the stable operation phase, the DC bus voltage is tightly controlled at around 959.8V. Compared to the rated reference value of 960V, the steady-state error of the system is only 0.2V (0.02%). This indicator not only verifies the high-precision tracking capability of the voltage outer-loop PI controller, but also far exceeds the 1% regulation accuracy standard commonly used in the power electronics industry, providing a stable voltage reference for subsequent connection of high-frequency pulse loads.

[0079] This slight steady-state deviation mainly stems from the system line impedance and the physical voltage drop across the switching devices, which aligns with actual engineering characteristics. Furthermore, thanks to the underlying three-phase interleaved parallel PWM control technology, the total current ripple from the lithium battery output is significantly reduced, ensuring the smoothness of the grid-connected current and effectively improving the power quality of the high-voltage bus.

[0080] Perform dynamic performance comparison analysis, including: To fully verify the advantages of the dynamic feedforward overdrive mechanism in overcoming the inductor hysteresis of lithium battery converters and suppressing bus voltage drops, a detailed comparative experiment was designed.

[0081] The system first starts up and maintains steady-state operation. At t=2.0s, after the bus voltage has fully stabilized, a highly challenging high-power pulse load is suddenly applied. For example... Figure 10As shown in the load power curve, this operating condition exhibits severe high-frequency pulse characteristics (1000Hz), with a peak power as high as 115kW. Especially during the initial startup phase from t=2.0s to t=2.025s, the load power shows a step-like increase (soft-start characteristic), and then stabilizes in a pulse state with a 50% duty cycle. This high-frequency, high-power step-like operating condition places extremely high demands on the power supply system, especially the transient power support capability of the lithium battery branch limited by inductive inertia.

[0082] Figures 11(a) and (b) respectively show the comparison of the bus voltage transient response of the system at the moment of load step change under traditional PI control (PI), PI+load current feedforward (PI+LF) control, and the dynamic feedforward overdrive mechanism (Proposed) provided in this embodiment. Detailed quantitative data of dynamic performance indicators are summarized in Table 2.

[0083] Table 2 Comparison of dynamic performance indicators;

[0084] Traditional PI converters are limited by bandwidth and inductive inertia, resulting in significant response lag. For example... Figure 11 As shown by the black line, the current build-up was slow during the initial stage of the load change, causing the voltage to drop to 942.8 V, a drop of approximately 1.79%. The recovery process exhibited overdamped characteristics, taking 53 ms, indicating poor dynamic performance.

[0085] While the PI+LF feedforward improved the voltage drop to 944.0 V, it introduced dynamic defects. For example... Figure 11 As shown by the blue line, the system exhibits underdamped oscillations. Due to integral saturation, there is an overshoot of about 1.4 V, with a peak value of 961.4 V. Furthermore, the settling time is significantly extended to 180 ms, indicating that simple feedforward is difficult to overcome inertia and is prone to oscillation.

[0086] The dynamic feedforward overdrive mechanism provided in this embodiment benefits from the proposed dynamic feedforward overdrive mechanism. The system instantaneously generates a 261.5 A compensation current to overcome inductive inertia, limiting the voltage drop to 945.1 V, with a drop amplitude of approximately 1.55%. The recovery process exhibits critical damping characteristics, achieving a smooth steady state within 26 ms, a speed improvement of 50.9% compared to traditional PI. Although a small steady-state error is retained, this effectively avoids overshoot oscillation, verifying its strong robustness.

[0087] In order to reveal the physical basis of the improved voltage dynamic performance, Figure 12 The macroscopic dynamic trajectory of the lithium battery output current under load step was further compared.

[0088] Figure 12(b) shows that the traditional PI is limited by integral lag, resulting in slow current rise and a steady state establishment time of 33 ms, which leads to overdraft of capacitor energy and deep voltage drop. Figure 12 (c) shows that although PI + LF improves the response speed, the lack of frequency domain isolation introduces violent high-frequency oscillations, which seriously sacrifices the system stability. Figure 12 (a) The dynamic feedforward overdrive mechanism (Proposed) provided in this embodiment, through dynamic feedforward overdrive, allows the current to surge to a peak value of 261.5 A within 7.7 ms. This controlled overshoot establishes a large induced voltage (L di / dt) across the inductor, successfully overcoming physical inertia and completing power compensation before the voltage drops.

[0089] Steady-state energy efficiency optimization and micro-waveform quality improvement are performed, including: To comprehensively evaluate the economy and safety of the control strategies, this experiment verified and analyzed the impact of the three strategies on the operating conditions of lithium batteries from two dimensions: microscopic current behavior and macroscopic Joule heat loss.

[0090] Figure 13 The steady-state lithium battery current waveforms under traditional PI control, the proposed strategy, and the PI+load feedforward strategy are shown respectively.

[0091] Figure 13 (b) shows that the traditional PI exhibits DC offset and ripple; Figure 13 (c) The lack of filtering in the PI+LF causes high-frequency oscillations of 10A~210A, which seriously affects the lifespan. Figure 13 (a) The hierarchical collaborative control method (Proposed) provided in this embodiment utilizes frequency domain decoupling to achieve quasi-DC operation of the lithium battery, effectively isolating high-frequency pulse pressure.

[0092] To accurately quantify the impact of the aforementioned waveform differences on energy efficiency, cumulative Joule heat loss was used as the evaluation index in this experiment. The steady-state test window was set to T=1s, and the battery internal resistance was... =0.02Ω, loss calculated based on RMS current: ; Traditional PI control (Baseline): The main loss originates from DC drift. The measured average current deviates to 122A. The conservative loss calculation, ignoring ripple effects, is as follows: ; PI + load direct feedforward: The main losses originate from severe AC oscillations. Due to severe waveform distortion, its RMS value is much higher than the average, soaring to 148.6 A. Its losses are as high as: ; The hierarchical collaborative control method provided in this embodiment (Proposed) achieves stable current regulation around 100 A with minimal fluctuations, minimizing ohmic losses and reducing heat losses. for: ; ; Calculations show that this strategy reduces heat loss by 32.8% and 54.7% compared to traditional PI and PI+LF methods, respectively, by eliminating steady-state current drift and suppressing high-frequency oscillations. This demonstrates that it significantly improves system energy efficiency while optimizing waveform quality. Based on the above verification experiments, this embodiment proposes a frequency domain decoupling and dynamic overdrive collaborative strategy to address the dynamic mismatch caused by the physical inertia of the converter. Experimental verification shows that, at the dynamic level, the proposed strategy establishes a 261.5 A overdrive current in 7.7 ms, representing a 50.9% improvement in response speed compared to traditional PI control, and completely avoids the voltage overshoot and 180 ms oscillation convergence process caused by the PI+LF strategy. At the steady-state level, the proposed strategy eliminates the DC drift of traditional PI control and the high-frequency oscillation of PI+load feedforward, placing the current in a quasi-DC condition of 100 A. This effectively cuts off the source of thermal stress, improving steady-state efficiency by 18% with an error of only 0.02%. This strategy solves the hysteresis defects of traditional control and the oscillation risks of feedforward control in both millisecond-level transient overdrive and system-level steady-state efficiency locking, ensuring the high reliability of the microgrid.

[0093] The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load provided in this application achieves coordinated optimization of high-dynamic bus voltage support and energy storage component health management by designing a filter-based frequency domain decoupling and power adjudication mechanism in the energy management layer and introducing dynamic feedforward overdrive technology in the bottom layer control. A hierarchical architecture of frequency domain decoupling and power adjudication is constructed to reduce battery micro-circulation and achieve quasi-DC smooth operation. An anti-inertia dynamic feedforward overdrive mechanism is proposed, explicitly compensating for converter inductance physical constraints and establishing a mapping bridge between frequency domain power allocation and time domain physical realizability. The method reveals and mitigates steady-state energy redundancy caused by control lag, and by precisely anchoring the DC operating point, it avoids ineffective Joule heat dissipation caused by current drift, thus achieving optimal steady-state energy efficiency of the system.

[0094] This embodiment also provides a hierarchical collaborative control system for a hybrid energy storage system with a high-frequency pulse load, the hierarchical collaborative control system comprising: The model building module establishes a hybrid energy storage system model for high-frequency pulse loads, including constructing a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. It also performs physical inertial analysis of the current response speed of a three-phase interleaved parallel converter model established based on the lithium battery model and builds an equivalent model for the high-frequency pulse load. The hierarchical collaborative control architecture module performs power distribution of the hybrid energy storage system through dual closed-loop control of DC bus voltage and current. The hierarchical collaborative control architecture includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

[0095] Example 2: This embodiment also provides a computer terminal device for a hierarchical collaborative control method of a hybrid energy storage system with a high-frequency pulse load. The terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the embodiments of the method described in Embodiment 1 of the present invention.

[0096] Furthermore, as an executable solution, the computer terminal device for the hierarchical collaborative control method of the hybrid energy storage system with high-frequency pulse load can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer terminal device for the hierarchical collaborative control method of the hybrid energy storage system with high-frequency pulse load may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above-described composition of the computer terminal device for the hierarchical collaborative control method of the hybrid energy storage system with high-frequency pulse load is merely an example and does not constitute a limitation on the computer terminal device for the hierarchical collaborative control method of the hybrid energy storage system with high-frequency pulse load. It may include more or fewer components than described above, or combine certain components, or different components. For example, the computer terminal device for the hierarchical collaborative control method of the hybrid energy storage system with high-frequency pulse load may also include input / output devices, network access devices, buses, etc., which are not limited in this embodiment of the present invention.

[0097] Furthermore, as an executable solution, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices. The general-purpose processor can be a microprocessor or any conventional processor. This processor serves as the control center of the computer terminal equipment for the hierarchical collaborative control method of the hybrid energy storage system with the high-frequency pulse load, connecting various parts of the computer terminal equipment using various interfaces and lines.

[0098] The memory can be used to store the computer programs and / or modules. The processor, by running or executing the computer programs and / or modules stored in the memory and calling data stored in the memory, realizes various functions of the computer terminal device of the hierarchical collaborative control method for the hybrid energy storage system with high-frequency pulse load. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the mobile phone, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0099] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the embodiments of the present invention.

[0100] If the modules / units integrated into the computer terminal device of the hierarchical collaborative control method for the hybrid energy storage system with the high-frequency pulse load are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc.

[0101] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the present invention. Finally, it should be noted that in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0102] The above provides a detailed description of the hierarchical collaborative control method, system, computer equipment, and storage medium for a hybrid energy storage system with a high-frequency pulse load, as provided in the embodiments of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the technical solutions and core ideas of this application. 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 of the technical features. These 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 hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load, characterized in that, The hierarchical collaborative control method includes: A hybrid energy storage system model for high-frequency pulse load is established, including the construction of a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. The physical inertia analysis of the current response speed is performed on the three-phase interleaved parallel converter model established based on the lithium battery model, and an equivalent model of high-frequency pulse load is built. The power distribution of the hybrid energy storage system is achieved through dual closed-loop control of voltage and current of the DC bus using a hierarchical collaborative control architecture, which includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

2. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 1, characterized in that, The filter-based frequency domain decoupling algorithm includes: The DC bus voltage closed-loop controller calculates the total current reference command required to maintain voltage stability in real time based on the bus voltage deviation. ; Use a low-pass filter bank to reference the total current command. Frequency domain decomposition and allocation, including: Extracting the fuel cell's fundamental reference current using a low-pass filter. ; Extracting the lithium battery's base reference current using a two-stage low-pass filter. .

3. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 2, characterized in that, Extracting the basic reference current of the fuel cell The process is as follows: ； in, Here is the transfer function of the first-order low-pass filter in the fuel cell branch; For the Laplace operator; ω is the cutoff angular frequency of the fuel cell branch.

4. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 3, characterized in that, Extracting the basic reference current of the lithium battery The process is as follows: ； ； in, The transfer function of the low-pass filter in the lithium battery branch; For the Laplace operator; The cutoff frequency of a lithium battery determines its dynamic engagement.

5. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 4, characterized in that, The power decision mechanism includes: Limiting and differential calculations for fuel cells: First, the basic reference current of the fuel cell is... Hard limiting is applied to obtain the reference current for the fuel cell. To protect the fuel cell stack from overload and prevent reverse current: ； in, This represents the minimum current value for the fuel cell; This represents the maximum current value of the fuel cell; If the fuel cell cannot meet the filtering command due to limiting, resulting in a power deficit It will be passed to the next level: ； Lithium-ion battery compensation and state machine protection: Lithium-ion batteries not only handle their own mid-frequency components, but also need to assist in compensating for the power deficit of the fuel cell. Compensation command for lithium batteries for: ； Introducing a SOC state machine protection mechanism to prevent battery overcharging and over-discharging: ； Apply a maximum charge / discharge current limit to the output command: .

6. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 5, characterized in that, The power decision mechanism also includes: Using supercapacitors as a fallback: Regardless of how the preceding stage limits the output, the supercapacitor must attempt to cover the total demand. All differences between the actual outputs of each source and the actual outputs are used to maintain bus voltage balance. ； Supercapacitor voltage constraint for: 。 7. The hierarchical collaborative control method for a hybrid energy storage system with a high-frequency pulse load according to claim 5, characterized in that, The dynamic feedforward overdrive includes: The current switching rate is detected by a high-pass filter with gain, and an overdrive compensation signal is generated. : ； The transfer function of the transient extraction filter is: ； in, The overdrive gain determines the strength of the compensation; The transient cutoff frequency determines the duration of the overdrive signal; For the Laplace operator; Execute the enhanced general command: Apply the current command to the inner loop of the lithium battery converter. The sum of the basic component and the overdriven component: 。 8. A hierarchical collaborative control system for a hybrid energy storage system with a high-frequency pulse load, characterized in that, The hierarchical collaborative control system includes: The model building module establishes a hybrid energy storage system model for high-frequency pulse loads, including constructing a hybrid energy storage microgrid with a DC bus based on a fuel cell model, a lithium battery model, and a supercapacitor model. It also performs physical inertial analysis of the current response speed of a three-phase interleaved parallel converter model established based on the lithium battery model and builds an equivalent model for the high-frequency pulse load. The hierarchical collaborative control architecture module performs power distribution of the hybrid energy storage system through dual closed-loop control of DC bus voltage and current. The hierarchical collaborative control architecture includes an energy management layer and a dynamic compensation layer. The energy management layer allocates load requirements based on the frequency domain decoupling algorithm and power adjudication mechanism of the filter, and the supercapacitor acts as a power balancing node to absorb high-frequency ripple and power residual. The dynamic compensation layer overcomes the inductive physical inertia of the three-phase interleaved parallel converter by dynamically feedforward overdrive, and realizes rapid power compensation for pulse loads.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the hierarchical collaborative control method for the hybrid energy storage system with high-frequency pulse load as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the hierarchical collaborative control method for the hybrid energy storage system with high-frequency pulse load as described in any one of claims 1 to 7.

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