An energy storage and conversion integrated energy management system for a ship integrated power system

Abstract

This invention belongs to the field of power system energy management technology, specifically relating to an integrated energy management system for shipboard integrated power systems. It includes a power input interface for connecting to the ship's power generation system, and an energy storage conversion unit connected to the power input interface. The energy storage conversion unit includes a DAB converter and an energy storage device. The energy storage conversion unit is connected to an energy management controller, which monitors the shipboard integrated power system status in real time and controls the operating mode of the energy storage conversion unit. This invention can improve the operating efficiency of the DAB converter and control voltage and current stress by constructing a refined mathematical model of the DAB converter based on time-domain analysis and frequency-domain Fourier series expansion, combined with state machine management of complex operating mode switching, determining soft-switching boundary conditions and optimizing the return current power operating point. This improves the stability and energy utilization efficiency of the shipboard power system.

Description

Technical Field

[0001] This invention belongs to the field of power system energy management technology, specifically relating to an integrated energy management system for energy storage and conversion for ship integrated power systems. Background Technology

[0002] The integrated power system of ships is a core component of modern warships, responsible for power generation, distribution, and load supply. With increasing electrification of ships, higher demands are placed on the stability, reliability, and efficiency of the power system. Energy storage and conversion technology, as a key link in the power system, achieves bidirectional energy flow and efficient conversion through DAB (Dual Active Bridge) converters. Due to their high efficiency, high power density, and bidirectional energy transfer capabilities, DAB converters are widely used in shipboard power systems.

[0003] Problems with existing technology: In actual operation, DAB converters are subject to the coupling effects of multiple physical fields such as electricity, magnetism, heat, and force. Their parasitic parameters have a significant impact on system performance, requiring precise mathematical models and control strategies to optimize their operating characteristics. First, traditional DAB converter mathematical models are mostly based on ideal conditions and fail to fully consider the influence of parasitic parameters under the coupling effects of multiple physical fields, resulting in insufficient model accuracy. Second, existing control systems lack the ability to determine the soft-switching boundary conditions and the optimized operating point for return current power, making it difficult to achieve optimal control under complex operating conditions. Third, the operating mode switching strategy is simplistic and cannot be dynamically adjusted according to different ship navigation states and the degree of power grid disturbance, leading to reduced system efficiency. Finally, insufficient voltage and current stress control affects system reliability and lifespan, failing to meet the stringent requirements of high reliability and high efficiency for ship power systems. Summary of the Invention

[0004] The purpose of this invention is to provide an integrated energy management system for energy storage and conversion in shipboard power systems. This system can improve the operating efficiency of the DAB converter and control voltage and current stress by constructing a refined mathematical model of the DAB converter based on time-domain analysis and frequency-domain Fourier series expansion, combined with state machine management of complex operating mode switching, determining soft-switching boundary conditions and optimized operating points for return current power, thereby improving the stability and energy utilization efficiency of the shipboard power system.

[0005] The specific technical solution adopted by this invention is as follows: An integrated energy management system for energy storage and conversion for shipboard integrated power systems includes: A power input interface is used to connect to the ship's power generation system, and an energy storage conversion unit is set up to connect to the power input interface. The energy storage conversion unit includes a DAB converter and an energy storage device. The energy storage conversion unit is connected to an energy management controller, which is used to monitor the status of the ship's integrated power system in real time and control the working mode of the energy storage conversion unit. The energy storage conversion unit is connected to a multi-functional output interface for connecting various loads on the ship. The energy management controller employs a state machine to manage the switching between complex operating modes. This state machine is based on a refined mathematical model of the DAB converter constructed using time-domain analysis and frequency-domain Fourier series expansion. It dynamically adjusts the operating mode according to ship operating conditions, power grid conditions, and load demands. This refined mathematical model establishes a simplified multi-parameter coupling model by offline analysis of the parasitic parameter characteristics of switching devices, magnetic components, and wiring structures in the DAB converter, combined with a time-domain equivalent circuit model and frequency-domain harmonic analysis. This model generates soft-switching boundary conditions and optimized return current power operating points to improve the operating efficiency and control voltage and current stress of the DAB converter.

[0006] The refined mathematical model of the DAB converter includes a time-domain model and a frequency-domain model. The time-domain model is established based on the circuit topology changes in the on and off states of the switching transistor and is used to generate the transient response characteristics of the DAB converter. The frequency domain model decomposes the periodic waveform into harmonic components using the Fourier series expansion method to generate the steady-state characteristics of the DAB converter. The energy management controller dynamically switches between the time domain model and the frequency domain model according to the real-time operating conditions of the ship's integrated power system to control the operating characteristics of the DAB converter. The energy management controller includes a status monitoring module, a mode decision module, and a control execution module. The status monitoring module collects the ship's power grid voltage, frequency, load power, and energy storage device state of charge parameters in real time. The mode decision module adopts a fuzzy adaptive control algorithm based on a refined mathematical model. It dynamically adjusts the mode switching threshold according to different ship navigation states and the degree of power grid disturbance. The input variables of the fuzzy adaptive control algorithm include power grid frequency deviation, voltage deviation and load mutation rate. Through fuzzy inference and defuzzification processing, the output is the adjustment amount of the power grid frequency deviation switching threshold, voltage deviation switching threshold and load mutation rate switching threshold. The energy storage device includes a lithium-ion battery pack and a supercapacitor pack, which are connected in parallel via an internally integrated DAB converter. The lithium-ion battery pack provides continuous energy, while the supercapacitor pack provides instantaneous power compensation.

[0007] The state machine includes a normal operation state, a power grid disturbance state, a load change state, and an emergency state, and the states are switched through preset switching conditions. The switching conditions include ship power grid frequency deviation, voltage deviation, and load mutation rate. The energy management controller dynamically adjusts the switching threshold between each state based on the soft switching boundary conditions generated by the refined mathematical model. The energy management controller also dynamically adjusts the modulation strategy of the DAB converter based on the voltage and current stress generated by the refined mathematical model. The modulation strategies include phase-shift modulation, pulse width modulation, and hybrid modulation. The energy management controller switches between different modulation strategies according to the real-time operating conditions of the ship's integrated power system.

[0008] An integrated energy management method for energy storage and conversion in shipboard integrated power systems includes the following steps: A refined mathematical model of the DAB converter is constructed based on time-domain analysis and frequency-domain Fourier series expansion. Based on a refined mathematical model, a state machine is applied to manage the switching between complex operating modes of the ship's integrated power system; Real-time monitoring of shipboard power grid parameters, energy storage device status, and load demand; Based on real-time monitoring data and refined mathematical models, power grid stability indicators and load demand change rates are calculated. Based on power grid stability indicators and load demand change rate, the optimal working mode is determined by state machine. Adjust the modulation strategy and operating parameters of the DAB converter according to the determined operating mode; When a ship's electrical grid failure or load change is detected, the system switches to the corresponding operating mode via a state machine to maintain a stable power supply to the ship's critical loads.

[0009] The construction of the refined mathematical model of the DAB converter includes the following steps: The parasitic parameter characteristics of switching devices, magnetic components and wiring structures in DAB converters are analyzed through offline experiments and finite element simulation. A parameterized model is established based on the analysis results. A time-domain model considering the influence of parasitic parameters is established, wherein the time-domain model is a time-domain equivalent circuit model; The periodic waveform is decomposed into harmonic components using the Fourier series expansion method, and a frequency domain model is established. By combining the time-domain model and the frequency-domain model, the soft-switching boundary of the DAB converter under different operating conditions is generated; Based on the calculation results, the optimized operating point for return power and the optimized parameters for voltage and current stress are generated. Parameter reduction processing includes the following steps: The multiphysics coupling model is decomposed into multiple single-physics sub-models; Sensitivity analysis was performed on each sub-model to identify key parameters that significantly affect system performance; Based on experimental data, key parameters are fitted to establish a mapping relationship between parameters and system performance; The mapping relationship is transformed into a simplified lookup table or polynomial expression for use in real-time control systems.

[0010] The state machine switching conditions are determined through the following steps: The soft-switching boundary conditions under different operating conditions are calculated based on the refined mathematical model described above. Analyze the impact of grid frequency deviation, voltage deviation and load mutation rate on the operating characteristics of DAB converter; Determine the optimal switching threshold between each state so that the DAB converter can maintain high efficiency in different operating modes; The switching threshold is dynamically adjusted based on the power demand characteristics of the ship at different mission stages.

[0011] The steps for adjusting the modulation strategy and operating parameters of the DAB converter include: Based on the voltage and current stress generated by the refined mathematical model, the optimal modulation strategy is selected; Intelligent switching between phase-shift modulation, pulse-width modulation, and hybrid modulation; Adjust the modulation parameters to optimize the return power of the DAB converter under soft-switching conditions; The modulation parameters are dynamically optimized based on the real-time operating conditions of the ship's integrated power system to ensure maximum efficiency.

[0012] The technical effects achieved by this invention are as follows: This invention achieves efficient operation of the DAB converter and reduces switching losses by accurately determining soft-switching boundary conditions; reduces energy waste and improves overall system efficiency by optimizing the operating point through return current power; achieves intelligent switching of operating modes through the coordinated work of state machine and refined mathematical model, improving the system's adaptability under complex operating conditions; and extends equipment lifespan and improves system reliability through effective control of voltage and current stress.

[0013] This invention constructs and coordinates time-domain and frequency-domain models, allowing the two models to work together in state machine switching and modulation strategy adjustment. The transient response characteristics are analyzed through the time-domain model, and the steady-state characteristics are analyzed through the frequency-domain model. The energy management controller dynamically switches between the two models according to real-time operating conditions to ensure control accuracy.

[0014] This invention utilizes a refined mathematical model to generate soft-switching boundary conditions and optimized return power operating points. The energy management controller can dynamically adjust the modulation strategy of the DAB converter, enabling it to operate under soft-switching conditions with optimized return power. Furthermore, by using a refined mathematical model to generate voltage and current stresses, the energy management controller can dynamically adjust the modulation strategy to ensure that the DAB converter operates within a safe range under various operating conditions.

[0015] This invention addresses the challenges of shipboard power systems, which, compared to land-based power systems, have smaller capacity, lower inertia, and more frequent load fluctuations, thus placing higher demands on their stability and reliability. By employing a state machine and a refined mathematical model in synergy, this invention improves the stability and energy efficiency of shipboard power systems, providing reliable technical support for the efficient operation of integrated shipboard power systems.

[0016] This invention, through the collaborative work of a state machine and a refined mathematical model, enables the system to quickly switch to the corresponding operating mode when a power grid fault or load change is detected, maintaining a stable power supply to the ship's critical loads. In the event of a power grid fault, the system can quickly provide emergency power to ensure that critical loads are not affected, thereby improving the system's response speed.

[0017] This invention, based on ship navigation status and grid load curves, can predict future power demand and optimize the charging and discharging strategy of energy storage devices. It can more accurately adjust the state of charge of energy storage devices, enabling them to adjust to the optimal range in advance before high load demand is predicted, thereby improving the overall system efficiency. Through the soft-switching boundary conditions and return power optimization operating point generated by the refined mathematical model, the modulation strategy of the DAB converter can be dynamically adjusted, enabling the DAB converter to operate under soft-switching conditions with optimized return power. This allows for more precise control of the DAB converter's operating state and significantly reduces system losses. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the energy management system structure of the present invention; Figure 2 This is a flowchart of the energy management method in this invention; Figure 3 These are the steps for constructing the refined mathematical model of the DAB converter in this invention; Figure 4 This is the step of determining the state machine switching conditions in this invention; Figure 5 These are the steps in this invention for adjusting the modulation strategy and operating parameters of the DAB converter; Figure 6 This is a schematic diagram of the integrated power system structure of the ship in this invention. Detailed Implementation

[0019] To make the objectives and advantages of this invention clearer, the invention will be specifically described below with reference to embodiments. It should be understood that the following text is merely used to describe one or more specific embodiments of the invention and does not strictly limit the scope of protection specifically claimed by the invention.

[0020] It should be noted that the terms "first," "second," etc., used in this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] According to an embodiment of the present invention, a method embodiment of an integrated energy management method for energy storage and conversion for ship integrated power systems is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0022] like Figure 1 As shown, an integrated energy management system for energy storage and conversion for shipboard integrated power systems includes: The power input interface is used to connect to the ship's power generation system, and an energy storage conversion unit is set up to connect to the power input interface. The energy storage conversion unit includes a DAB converter and an energy storage device. The energy storage conversion unit is connected to the energy management controller, which is used to monitor the status of the ship's integrated power system in real time and control the working mode of the energy storage conversion unit. The energy storage conversion unit is connected to the multi-functional output interface for connecting various loads on the ship. The energy management controller employs a state machine to manage the switching between complex operating modes. The state machine is based on a refined mathematical model of the DAB converter constructed using time-domain analysis and frequency-domain Fourier series expansion. It dynamically adjusts the operating mode according to the ship's operating conditions, power grid conditions, and load requirements. The refined mathematical model establishes a simplified multi-parameter coupling model by offline analysis of the parasitic parameter characteristics of switching devices, magnetic components, and wiring structures in the DAB converter, combined with time-domain equivalent circuit models and frequency-domain harmonic analysis. This model generates soft-switching boundary conditions and return power optimization operating points to improve the operating efficiency of the DAB converter and control voltage and current stress. The simplified multi-parameter coupling model ensures that the model complexity is suitable for real-time control system applications through experimental data fitting and parameter order reduction.

[0023] Furthermore, the parameter reduction process includes the following steps: S501. Decompose the multiphysics coupling model into multiple single-physics sub-models; S502. Perform sensitivity analysis on each sub-model to identify key parameters that have a significant impact on system performance; S503. Fit key parameters based on experimental data and establish a mapping relationship between parameters and system performance; S504: Transforms mapping relationships into simplified lookup tables or polynomial expressions for use in real-time control systems.

[0024] For example, in thermal field analysis, by experimentally measuring the on-resistance and switching characteristics of power devices at different temperatures, a mapping relationship between temperature, on-resistance, and switching characteristics is established, which is then simplified into a quadratic polynomial expression: Where T is temperature. Let be the on-resistance, and a, b, and c be parameters obtained through experimental fitting. By reducing the order of these parameters, the complexity of the model can be significantly reduced, enabling the refined mathematical model to be applied to real-time control systems.

[0025] Based on the above, the state machine management mechanism adopted by the energy management controller is based on the refined mathematical model of the DAB converter. This model analyzes the generation mechanism of parasitic parameters under the coupling of multiple physical fields such as electricity, magnetism, heat and force in the DAB converter, and realizes the accurate generation of soft switching boundary conditions and return power optimization operating points. The refined mathematical model is constructed by combining the time domain analysis method and the frequency domain Fourier series expansion method, which can describe the dynamic characteristics of the DAB converter under different operating conditions.

[0026] Furthermore, when the ship's power system is under different operating conditions, the energy management controller monitors the grid status and load demand in real time, and calculates the soft-switching boundary conditions and return power optimization operating point under the current operating conditions through a refined mathematical model. For example, when the ship's grid frequency fluctuates, the model can quickly calculate the soft-switching boundary of the DAB converter at this time, and the energy management controller adjusts the operating mode and modulation strategy accordingly to ensure that the system always operates in the high-efficiency region.

[0027] This implementation method, by analyzing the coupling effects of electric field, magnetic field, thermal field and force field, can effectively predict the behavior characteristics of DAB converter under various operating conditions, providing an accurate basis for switching operating modes.

[0028] When switching operating modes, the state machine dynamically adjusts the operating mode according to the ship's operating conditions, the power grid status, and the load demand. When the power grid frequency deviation is detected to exceed the threshold, the system automatically switches from the energy buffer mode to the power compensation mode. When the power grid voltage drops sharply to exceed the threshold, the system automatically switches to the emergency power supply mode. The above switching process is based on soft-switching boundary conditions generated by a refined mathematical model to ensure a smooth switching process and avoid system oscillations caused by mode switching.

[0029] It should be noted that multiphysics coupling analysis of DAB converters is usually computationally intensive and difficult to apply directly to real-time control systems. Therefore, a strategy combining offline analysis and online application is adopted. Through offline experiments and finite element simulation, the parasitic parameter characteristics of switching devices, magnetic components and wiring structures in DAB converters are comprehensively analyzed. Then, a parameterized model is established based on the analysis results, and through parameter reduction processing, the complex multiphysics coupling model is simplified into an expression form suitable for real-time control.

[0030] Based on the above: By accurately determining the soft-switching boundary conditions, the DAB converter achieves high-efficiency operation and reduces switching losses; by optimizing the operating point through return current power, energy waste is reduced and the overall system efficiency is improved; through the coordinated operation of the state machine and the refined mathematical model, intelligent switching of the operating mode is achieved, improving the system's adaptability under complex operating conditions; and through effective control of voltage and current stress, the service life of the equipment is extended and the system reliability is improved.

[0031] As an optional embodiment, the refined mathematical model of the DAB converter includes a time-domain model and a frequency-domain model. The time-domain model is established based on the circuit topology changes in the on and off states of the switching transistors and is used to generate the transient response characteristics of the DAB converter.

[0032] Furthermore, the frequency domain model decomposes the periodic waveform into harmonic components using the Fourier series expansion method to generate the steady-state characteristics of the DAB converter. The energy management controller dynamically switches between the time domain model and the frequency domain model according to the real-time operating conditions of the ship's integrated power system to control the operating characteristics of the DAB converter. The energy management controller includes a state monitoring module, a mode decision module, and a control execution module. The state monitoring module collects the ship's power grid voltage, frequency, load power, and energy storage device state-of-charge parameters in real time.

[0033] Furthermore, the mode decision module employs a fuzzy adaptive control algorithm based on a refined mathematical model. It dynamically adjusts the mode switching threshold according to different ship navigation states and the degree of power grid disturbance. The input variables of the fuzzy adaptive control algorithm include power grid frequency deviation, voltage deviation, and load mutation rate. Through fuzzy inference and defuzzification processing, the output is the adjustment amount of the power grid frequency deviation switching threshold, voltage deviation switching threshold, and load mutation rate switching threshold. For example, the output power grid frequency deviation switching threshold adjustment amount is equal to -0.1Hz, which means that the original threshold is adjusted from ±0.5Hz to ±0.4Hz.

[0034] The method for constructing a fuzzy rule base includes the following steps: S601. Based on historical operating data of ship power systems, analyze the statistical characteristics of power grid frequency deviation, voltage deviation and load mutation rate, and determine the fuzzy set partitioning boundary. S602. Establish an initial rule set based on expert experience, divide the power grid frequency deviation into seven fuzzy sets: {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, divide the voltage deviation into five fuzzy sets: {low, medium low, normal, medium high, high}, and divide the load change rate into three fuzzy sets: {slow, medium, fast}. S603. Using a shipboard power system simulation platform, simulate different navigation states and power grid disturbance conditions to verify and optimize the initial rule set. S604. Adopt rule reduction technology to remove redundant rules and retain the core rules that have the greatest impact on system stability. S605. Establish a mapping between the rule base and the ship's mission phases so that the rule base can adapt to different mission requirements.

[0035] Furthermore, the parameter adaptive adjustment mechanism of the fuzzy adaptive control algorithm includes the following steps: S701, the ship mission status identification module receives mission instructions sent by the ship integrated monitoring system in real time and identifies the current mission stage; S702. Based on the characteristics of the task stage, dynamically adjust the output of the fuzzy rule base, for example: Operational mission phase: Reduce the emergency state switching threshold and improve the system's response capability to power grid disturbances; Cruise mission phase: Improve the stability threshold of normal operation mode and optimize overall system efficiency; During the berthing mission phase: Adjust the relevant thresholds for energy storage device charging, prioritizing charging efficiency; S703. Based on the online evaluation of the DAB converter's operating status, the efficiency, voltage and current stress, and soft-switching implementation of the DAB converter are recorded periodically. The control effect is evaluated through a multi-objective optimization algorithm. When the system performance is lower than the preset threshold, the rule base parameter adjustment is initiated. The rule base parameters are updated using the gradient descent method to gradually optimize the system performance. S704. During the parameter adjustment process, system stability is considered, and minimum adjustment intervals and maximum adjustment amplitude limits are set to avoid control oscillations caused by frequent adjustments.

[0036] Furthermore, the energy storage device includes a lithium-ion battery pack and a supercapacitor pack, which are connected in parallel via an internally integrated DAB converter. The lithium-ion battery pack provides continuous energy, while the supercapacitor pack provides instantaneous power compensation. The DAB converter optimizes PCB layout to reduce parasitic inductance and capacitance, suppress electromagnetic interference, and improve conversion efficiency. This includes: using planar magnetic integration technology to reduce leakage inductance and distributed capacitance; optimizing the layout and routing of power switches; employing a multi-layer PCB design to rationally arrange ground planes; and adding buffer circuits at critical nodes to suppress voltage and current spikes during switching.

[0037] Based on the above, the time-domain model in the refined mathematical model of the DAB converter is based on the accurate analysis of the DAB converter under different switching states. Specifically, the working cycle of the DAB converter is divided into four key intervals: primary-side lead, primary-side lag, secondary-side lead, and secondary-side lag. Within each interval, the corresponding equivalent circuit model is established by considering the influence of parasitic parameters such as the on-resistance of the switching transistor, parasitic capacitance, and wiring inductance. By solving the state equations, the voltage and current waveforms of the key nodes are obtained. Based on the above piecewise linearization method, the behavior characteristics of the DAB converter in the transient process can be accurately described, especially the response characteristics under the conditions of power grid change or load change.

[0038] Furthermore, the frequency domain model is implemented based on the Fourier series expansion method, which decomposes the periodic waveform of the DAB converter into harmonic components and represents the input voltage, output voltage, and current waveforms of the DAB converter in Fourier series form. By analyzing the amplitude and phase of each harmonic, the frequency domain characteristics of the DAB converter are obtained. This is particularly suitable for analyzing the operating characteristics of the DAB converter under steady-state conditions and can accurately predict the efficiency and power factor of the system at different operating points.

[0039] Furthermore, the energy management controller dynamically switches between the time-domain model and the frequency-domain model based on the real-time operating conditions of the ship's integrated power system. This switching mechanism is based on real-time assessment of the power grid status. When the system detects a sudden change in the power grid (such as frequency fluctuations exceeding ±0.5Hz or voltage drops exceeding 10%), it automatically switches to the time-domain model for precise control. When the system is in steady-state operation (frequency fluctuations less than ±0.2Hz and voltage fluctuations less than ±5%), it switches to the frequency-domain model for efficient control. Based on this dynamic switching mechanism, the system can maintain optimal control performance under various operating conditions.

[0040] Furthermore, the mode decision module in the energy management controller adopts a fuzzy adaptive control algorithm based on a refined mathematical model. Its working principle is to use grid frequency deviation, voltage deviation, and load mutation rate as input variables, and output the weight coefficients of each working mode through a fuzzy rule base and inference mechanism. According to the different navigation states of the ship (such as sailing, anchoring, combat, etc.) and the degree of grid disturbance, the parameters in the fuzzy rule base are dynamically adjusted so that the mode switching threshold can adapt to changes in the grid. For example, when the ship is in combat mode, the system automatically reduces the switching threshold of the power compensation mode to improve the system's response speed to grid disturbances; when the ship is in cruise mode, the system automatically increases the weight coefficient of the energy optimization mode to optimize the energy allocation strategy.

[0041] As one optional embodiment, the fuzzy adaptive control algorithm is implemented on an FPGA, specifically including the following steps: S801. The collected power grid frequency deviation, voltage deviation and load change rate are converted into digital signals by ADC and then normalized. S802. Perform rule evaluation and use the Mamdani inference method to calculate the activation strength of each rule; S803. Use the maximum-product synthesis method to aggregate the outputs of all rules; S804. The centroid method is used to calculate the final switching threshold adjustment amount to achieve defuzzification; S805: Periodically perform parameter optimization, update rule base parameters based on historical operation data, and thus achieve adaptive adjustment.

[0042] Furthermore, as an optional embodiment, the effectiveness of the fuzzy adaptive control algorithm is verified by the following method: S901. Construct a ship power system model on the RT-LAB real-time simulation platform to simulate different navigation states and power grid disturbance conditions. S902. Compared with the traditional fixed threshold control method, measure the number of mode switching times, system efficiency, and voltage fluctuation rate. S903. Through experimental data analysis, the effectiveness of the fuzzy adaptive control algorithm in improving system stability, reducing switching losses, and optimizing energy distribution is verified.

[0043] Furthermore, in the energy storage device, lithium-ion battery packs and supercapacitor packs are connected in parallel via an internally integrated DAB converter to form a hybrid energy storage structure. This connection is based on the principle of energy-power complementarity: lithium-ion battery packs have high energy density, making them suitable for providing continuous energy support; supercapacitor packs have high power density and fast charging and discharging capabilities, making them suitable for providing instantaneous power compensation. The energy management controller dynamically allocates the output ratio of the two energy storage media according to load demand. When the load demand is stable, the lithium-ion battery pack mainly provides energy; when the load changes abruptly, the supercapacitor pack responds quickly, providing instantaneous power compensation, reducing the burden on the lithium-ion battery pack, and extending its service life.

[0044] As an optional embodiment, the DAB converter optimizes PCB layout, reduces parasitic inductance and capacitance, suppresses electromagnetic interference, and improves conversion efficiency, specifically including: S101. Planar magnetic integration is used to integrate the magnetic core of the high-frequency transformer with the PCB winding, reducing leakage inductance and distributed capacitance. S102. Optimize the layout and wiring of power switching transistors to reduce parasitic inductance and parasitic capacitance; S103. Employs a multi-layer PCB design, with reasonable arrangement of ground and power planes to reduce electromagnetic interference; S104. Add a buffer circuit at critical nodes to suppress voltage and current spikes during the switching process.

[0045] Based on the above, the fuzzy adaptive control algorithm can dynamically adjust the mode switching threshold according to different ship navigation states and the degree of power grid disturbance, so that the system can maintain efficient operation under various operating conditions. Under complex operating conditions such as ship acceleration or turning, the system can reduce the impact on the main power generation system through rapid response.

[0046] Furthermore, by working together with the lithium-ion battery pack and the supercapacitor pack, the energy-power distribution can be optimized, reducing the burden on the lithium-ion battery pack and extending its cycle life. By controlling the distribution of parasitic parameters, electromagnetic interference generated during the operation of the DAB converter can be suppressed, thereby reducing electromagnetic interference and meeting the electromagnetic compatibility requirements of ships.

[0047] Furthermore, based on the special needs of shipboard power systems, which are characterized by smaller capacity, lower inertia, and more frequent load changes compared to land-based power systems, the energy management controller enables the system to maintain high efficiency under complex operating conditions through dynamic switching between time-domain and frequency-domain models and the application of fuzzy adaptive control algorithms.

[0048] As an optional embodiment, the state machine includes a normal operation state, a power grid disturbance state, a load mutation state, and an emergency state. The states are switched through preset switching conditions, including ship power grid frequency deviation, voltage deviation, and load mutation rate. The energy management controller dynamically adjusts the switching threshold between the states based on the soft switching boundary conditions generated by the refined mathematical model.

[0049] The energy management controller also dynamically adjusts the modulation strategy of the DAB converter based on the voltage and current stress generated by the refined mathematical model. The modulation strategies include phase shift modulation, pulse width modulation and hybrid modulation. The energy management controller switches between different modulation strategies according to the real-time operating conditions of the ship's integrated power system.

[0050] Based on the above, the state machine achieves accurate identification and response to complex operating conditions of the ship's integrated electric power system through a refined mathematical model. The switching between the four operating states includes the following: It should be noted that the switching conditions include the ship's power grid frequency deviation, voltage deviation, and load change rate, which can be defined as: Normal operating conditions: Grid frequency deviation is less than ±0.2Hz, voltage deviation is less than ±5%, and load change rate is less than 5% / s; Power grid disturbance status: 0.2Hz less than or equal to the power grid frequency deviation less than 0.5Hz or 5% less than or equal to the voltage deviation less than 10%; Load mutation state: Load mutation rate greater than or equal to 10% / s; Emergency state: The power grid frequency deviation is greater than or equal to 0.5 Hz or the voltage deviation is greater than or equal to 10% or a short circuit fault is detected.

[0051] The proposed values ​​are only used to illustrate the definition of switching conditions and do not represent the actual values ​​in operation, as actual operation is affected by a variety of factors.

[0052] Normal operating state: When the ship's power grid is in a stable operating state, the system is in normal operating state. In this state, the system operates in energy optimization mode. The energy management controller predicts future power demand based on the ship's navigation status and the power grid load curve, and optimizes the charging and discharging strategy of the energy storage device to achieve the best overall system efficiency. At this time, the energy management controller mainly adopts the phase shift modulation strategy. Based on the soft switching boundary conditions generated by the refined mathematical model, it adjusts the phase shift angle to make the DAB converter operate under soft switching conditions and dynamically adjusts the operating parameters to achieve local optimization of return power.

[0053] Grid Disturbance State: When a slight disturbance is detected in the grid, the system automatically switches to the grid disturbance state. In this state, the system operates in power compensation mode, the supercapacitor bank responds quickly, provides instantaneous power support, and reduces the burden on the main power generation system. The energy management controller dynamically adjusts the state switching threshold based on the soft switching boundary conditions generated by the refined mathematical model, so that the system can adapt to different degrees of grid disturbance. At this time, the energy management controller adopts a hybrid modulation strategy, combining phase shift modulation and pulse width modulation to achieve precise control of power flow.

[0054] The state transitions of the state machine follow these rules: (1) The state transition must meet the condition that the duration is greater than or equal to 100ms to avoid false switching caused by instantaneous interference; (2) State transition priority: Emergency state > Load change state > Power grid disturbance state > Normal operation state; (3) Normal operating conditions can be directly switched to grid disturbance conditions or load change conditions; (4) The power grid disturbance state can be switched to normal operation state or emergency state; (5) The load change state can be switched to normal operation state or emergency state; (6) Emergency status can only be transitioned to normal operation status (after the system has been fully restored).

[0055] Load Sudden Change State: When a sudden change in load is detected, the system automatically switches to the load sudden change state. In this state, the system operates in energy buffer mode, and the lithium-ion battery pack and supercapacitor pack work together to smooth out grid fluctuations caused by load sudden changes. The energy management controller dynamically adjusts the modulation strategy based on the voltage and current stress generated by the refined mathematical model to ensure that the DAB converter maintains high efficiency during load sudden changes. At this time, the energy management controller mainly adopts the pulse width modulation strategy, and achieves a fast response to power transmission by adjusting the conduction time of the switching transistor.

[0056] Emergency State: When a serious grid fault or drastic load change is detected, the system automatically switches to emergency state. In this state, the system operates in emergency power supply mode, prioritizing the stable power supply to critical loads. The energy management controller quickly switches modes via a state machine to ensure the system completes mode switching within a short time, maintaining a stable power supply to the ship's critical loads. At this time, the energy management controller adopts a special hybrid modulation strategy. In emergency state, the energy management controller prioritizes the power supply to critical loads while trying to keep the DAB converter operating close to soft-switching conditions to reduce switching losses. When grid parameters exceed the feasible range of soft switching, the system automatically switches to hard-switching protection mode to ensure equipment safety.

[0057] It should be noted that the state machine switching threshold is not a fixed value, but is dynamically adjusted according to the power demand characteristics of different mission phases of the ship. For example, when the ship is in a high-priority mission phase, the system automatically lowers the emergency state switching threshold to improve the system's response speed to power grid disturbances; when the ship is in cruise mode, the system automatically increases the weight coefficient of the energy optimization mode to optimize the energy allocation strategy; when the ship is in berthing mode, the system prioritizes using shore power to charge the energy storage device, while reducing the sensitivity of state switching.

[0058] For example, the energy management controller can be set to dynamically adjust the switching thresholds between different states according to the ship's mission phase. These thresholds can be set to different values ​​depending on the power of the ship's electrical equipment, for example: High-priority task phase: Emergency state switching threshold reduced by 20%, power grid disturbance state switching threshold reduced by 15%; Cruise mode: The threshold for switching between grid disturbance states is increased by 10%, and the threshold for switching between load change states is increased by 5%. Parking mode: All state switching thresholds are increased by 30%, and the state confirmation time is extended to 200ms.

[0059] Furthermore, the dynamic adjustment mechanism of the DAB converter's modulation strategy is based on the voltage and current stress generated by a refined mathematical model. Specifically, the energy management controller monitors the voltage and current waveforms of the key nodes of the DAB converter in real time. Based on the analysis results of the time-domain model and the frequency-domain model, it calculates the voltage and current stress under the current operating conditions. When the voltage and current stress exceeds the safety threshold, the energy management controller automatically adjusts the modulation strategy to ensure that the DAB converter operates within a safe range.

[0060] The modulation strategy is based on the following under different operating conditions: When the transmission power is low, phase shift modulation strategy is mainly used to simplify control complexity; When the transmission power is moderate, a hybrid modulation strategy is adopted to balance efficiency and performance; When the transmission power is high, a pulse width modulation strategy is adopted to improve the power transmission capability; When the system is in an emergency, a special hybrid modulation strategy is employed to ensure rapid response and high reliability.

[0061] By constructing and coordinating time-domain and frequency-domain models, the two models work together in state machine switching and modulation strategy adjustment. The transient response characteristics are analyzed through the time-domain model, and the steady-state characteristics are analyzed through the frequency-domain model. The energy management controller dynamically switches between the two models according to the real-time operating conditions to ensure control accuracy.

[0062] Based on the above, by managing the switching between complex working modes through a state machine, the system can dynamically adjust the working mode according to different navigation states of the ship and the degree of power grid disturbance, thereby improving the system's adaptability under complex working conditions, especially improving the system's response speed during dynamic processes such as ship acceleration or turning.

[0063] Furthermore, by generating soft-switching boundary conditions and optimized return power operating points through refined mathematical models, the energy management controller can dynamically adjust the modulation strategy of the DAB converter, enabling the DAB converter to operate under soft-switching conditions with optimized return power. By generating voltage and current stresses through refined mathematical models, the energy management controller can dynamically adjust the modulation strategy to ensure that the DAB converter operates within a safe range under various operating conditions.

[0064] Furthermore, based on the energy demand characteristics under different operating modes, the system can optimize the energy distribution strategy of lithium-ion battery packs and supercapacitor packs, thereby extending the service life of the energy storage device.

[0065] It is worth noting that, compared with land-based power systems, shipboard power systems have characteristics such as smaller capacity, lower inertia, and more frequent load changes, which places higher demands on the stability and reliability of the power system. By working in concert with state machines and refined mathematical models, the stability and energy efficiency of shipboard power systems can be improved, providing reliable technical support for the efficient operation of integrated shipboard power systems.

[0066] An integrated energy management method for energy storage and conversion in shipboard integrated power systems, referring to Appendix Figure 2 It includes the following steps: S1. A refined mathematical model of the DAB converter is constructed based on time-domain analysis and frequency-domain Fourier series expansion. S2. Based on a refined mathematical model, a state machine is applied to manage the switching between complex operating modes of the ship's integrated power system. S3. Real-time monitoring of shipboard power grid parameters, energy storage device status, and load demand; S4. Calculate the power grid stability index and load demand change rate based on real-time monitoring data and refined mathematical models; S5. Based on the power grid stability index and the load demand change rate, the optimal working mode is determined by a state machine. S6. Adjust the modulation strategy and operating parameters of the DAB converter according to the determined working mode; S7. When a ship's power grid fault or load change is detected, the state machine switches to the corresponding working mode to maintain a stable power supply to the ship's critical loads.

[0067] Based on the above steps, the energy management method is implemented on the basis of the energy management system. It combines the refined mathematical model of the DAB converter with the state machine control strategy to realize intelligent energy management of the ship's integrated power system. First, the refined mathematical model of the DAB converter, constructed by the time domain analysis method and the frequency domain Fourier series expansion method, provides a precise control basis for the state machine. The refined mathematical model is based on the generation mechanism of parasitic parameters under the coupling of multiple physical fields such as electricity, magnetism, heat and force in the DAB converter, and can accurately predict the behavior characteristics of the DAB converter under different operating conditions.

[0068] Furthermore, the energy management method monitors the ship's power grid parameters, energy storage device status, and load demand in real time through the energy management controller. In addition to collecting basic electrical parameters, it also obtains power grid stability indicators and load demand change rate. The power grid stability indicators are calculated by analyzing the fluctuation characteristics of power grid frequency and voltage, while the load demand change rate is determined by analyzing the trend of load power change. By utilizing the theoretical support provided by the refined mathematical model, the calculation results are made more accurate and reliable.

[0069] Furthermore, based on the calculated grid stability index and load demand change rate, the state machine dynamically determines the optimal operating mode. The state machine can dynamically adjust the threshold for switching operating modes according to the power demand characteristics of different mission stages of the ship. For example, when the ship is in a high-priority mission stage, the state machine automatically lowers the emergency state switching threshold to improve the system's response speed to grid disturbances; when the ship is in cruise mode, the state machine automatically optimizes the energy allocation strategy; when the ship is in berthing mode, the state machine prioritizes the charging efficiency of energy storage devices.

[0070] Based on the determined operating mode, the energy management method dynamically adjusts the modulation strategy and operating parameters of the DAB converter. Under normal operating conditions, a phase-shift modulation strategy is mainly adopted to simplify control complexity. Under grid disturbance conditions, a hybrid modulation strategy is adopted to balance efficiency and performance. Under load change conditions, a pulse width modulation strategy is mainly adopted to improve power transmission capability. Under emergency conditions, a special hybrid modulation strategy is adopted to ensure fast response and high reliability.

[0071] When a ship's power grid fault or load change is detected, the energy management method quickly switches to the corresponding operating mode through a state machine to maintain a stable power supply to the ship's critical loads. Based on the soft-switching boundary conditions generated by the refined mathematical model, it ensures a smooth switching process and avoids system oscillations caused by mode switching. At the same time, based on the voltage and current stress generated by the refined mathematical model, the modulation parameters are dynamically adjusted to ensure that the DAB converter operates within a safe range during the switching process.

[0072] Based on the above, through the collaborative work of state machine and refined mathematical model, the system can quickly switch to the corresponding working mode when it detects power grid failure or load change, maintain stable power supply to the ship's critical loads, and provide emergency power supply in the event of power grid failure, ensuring that critical loads are not affected and improving system response speed.

[0073] Furthermore, based on the ship's navigation status and the grid load curve, future power demand can be predicted, and the charging and discharging strategies of energy storage devices can be optimized. The state of charge of energy storage devices can be adjusted more precisely, so that the state of charge is adjusted to the optimal range in advance before high load demand is predicted, thereby improving the overall system efficiency. Through the soft-switching boundary conditions and return power optimization operating points generated by the refined mathematical model, the modulation strategy of the DAB converter can be dynamically adjusted, so that the DAB converter operates under soft-switching conditions with optimized return power. This allows for more precise control of the operating state of the DAB converter and a significant reduction in system losses.

[0074] Furthermore, by managing the switching between complex working modes through a state machine, the system can maintain high efficiency under various operating conditions. It can dynamically adjust the working mode according to different ship navigation states and the degree of power grid disturbance, thus significantly improving the system's adaptability under complex operating conditions.

[0075] As an optional embodiment, refer to the appendix Figure 3 The construction of a refined mathematical model for the DAB converter includes the following steps: S201. Analyze the parasitic parameter characteristics of switching devices, magnetic components and wiring structures in the DAB converter through offline experiments and finite element simulation, and establish a parameterized model based on the analysis results. S202. Establish a time-domain model that considers the influence of parasitic parameters. The time-domain model is a time-domain equivalent circuit model. S203. The periodic waveform is decomposed into harmonic components by Fourier series expansion and a frequency domain model is established. S204. Combining the time-domain model and the frequency-domain model, generate the soft-switching boundary of the DAB converter under different operating conditions. S205. Based on the calculation results, generate the optimized operating point for return power and the optimized parameters for voltage and current stress.

[0076] Based on the above steps, in the process of constructing a refined mathematical model of the DAB converter, the generation mechanism of parasitic parameters of switching devices, magnetic components, and wiring structures in the DAB converter is first analyzed. The influence of the coupling effect of multiple physical fields such as electricity, magnetism, heat, and force on parasitic parameters is taken into account, including the on-resistance of the switching transistor, parasitic capacitance, leakage inductance and distributed capacitance of magnetic components, as well as the parasitic inductance and parasitic capacitance of the wiring structure. Through a combination of finite element analysis and experimental measurement, the variation law of each parasitic parameter under different operating conditions is determined.

[0077] When establishing the time-domain model, based on the circuit topology changes in the on and off states of the switching transistor, a time-domain equivalent circuit model considering the influence of parasitic parameters is constructed. The working cycle of the DAB converter is divided into multiple switching state intervals, and a corresponding equivalent circuit is established in each interval. By solving the state equations, the voltage and current waveforms of key nodes are obtained. The time-domain equivalent circuit model can accurately describe the behavior characteristics of the DAB converter in transient processes, especially the response characteristics under the conditions of power grid change or load change.

[0078] The frequency domain model is established by decomposing the periodic waveform of the DAB converter into harmonic components using the Fourier series expansion method. The input voltage, output voltage, and current waveforms of the DAB converter are expressed in Fourier series form. By analyzing the amplitude and phase of each harmonic, the frequency domain characteristics of the DAB converter are obtained. The frequency domain model can accurately describe the operating characteristics of the DAB converter under steady-state conditions.

[0079] By combining time-domain and frequency-domain models, soft-switching boundaries of the DAB converter under different operating conditions are generated. The soft-switching boundary refers to the conditional boundary for the DAB converter to achieve zero-voltage switching (ZVS) or zero-current switching (ZCS), which is determined by analyzing the phase relationship between the voltage across the switching transistor and the current flowing through it.

[0080] Based on the above, the optimized operating point for return current power and the optimized parameters for voltage and current stress are generated. The optimized operating point for return current power refers to the operating point that minimizes the return current power inside the DAB converter while meeting the power transmission requirements. It is determined by analyzing the power transmission characteristics of the DAB converter. The optimized parameters for voltage and current stress refer to the operating parameters that minimize the voltage and current stress on the power devices while ensuring the safe operation of the system.

[0081] As an optional embodiment, refer to the appendix Figure 4 The state machine transition conditions are determined through the following steps: S301. Calculate the soft-switching boundary conditions under different operating conditions based on the refined mathematical model; S302. Analyze the impact of grid frequency deviation, voltage deviation and load mutation rate on the operating characteristics of DAB converter; S303. Determine the optimal switching threshold between each state so that the DAB converter can maintain high efficiency in different working modes. S304. Dynamically adjust the switching threshold according to the power demand characteristics of the ship at different mission stages.

[0082] According to the above steps, in step S301, based on the constructed refined mathematical model of the DAB converter, the soft-switching boundary conditions under different operating conditions are calculated. The transient process of the DAB converter in the on and off states of the switching transistor is analyzed through the time domain model, taking into account the influence of parasitic parameters on the switching process. The steady-state characteristics of the DAB converter are analyzed through the frequency domain model to determine the boundary conditions for achieving zero-voltage switching (ZVS) or zero-current switching (ZCS). The calculation of the soft-switching boundary conditions takes into account factors such as switching frequency, transmission power and load characteristics, making the calculation results more accurate and reliable.

[0083] In step S302, the system analyzes the impact of grid frequency deviation, voltage deviation, and load mutation rate on the operating characteristics of the DAB converter. By establishing the mapping relationship between grid parameters and key performance indicators of the DAB converter (such as efficiency, return power, voltage and current stress), the system quantifies the impact of these parameter changes on system performance. For example, when the grid frequency deviation increases, the soft switching conditions of the DAB converter will change; when the load mutation rate increases, the transient response characteristics of the DAB converter will be affected, providing a basis for determining the optimal switching threshold.

[0084] In step S303, the system determines the optimal switching threshold between each state. Based on the analysis results of steps S301 and S302, a multi-objective optimization algorithm is used to determine the optimal switching threshold so that the DAB converter can maintain high efficiency in different operating modes. The efficiency, return power, and voltage and current stress of the DAB converter are used as optimization objectives. The optimal switching threshold between each state is determined through the Pareto optimal solution set. For example, between the normal operating state and the grid disturbance state, the system determines a switching threshold that maximizes the efficiency of the DAB converter to ensure that the system does not cause a decrease in efficiency when switching between the two states.

[0085] In step S304, the system dynamically adjusts the switching threshold according to the power demand characteristics of different mission phases of the ship. The system receives mission instructions sent by the ship's integrated monitoring system, identifies the current mission phase (such as combat, cruise, berthing, etc.), and dynamically adjusts the switching threshold according to the mission characteristics. For example, in high-priority mission phases, the system automatically lowers the switching threshold for emergency states to improve the system's response speed to power grid failures; in cruise mode, the system automatically increases the weight coefficient of the energy optimization mode to optimize the energy allocation strategy; in berthing mode, the system prioritizes the charging efficiency of energy storage devices and adjusts the sensitivity of state switching.

[0086] As an optional embodiment, refer to the appendix Figure 5 The steps for adjusting the modulation strategy and operating parameters of the DAB converter include: S401. Select the optimal modulation strategy based on the voltage and current stress generated by the refined mathematical model; S402, intelligent switching between phase-shift modulation, pulse-width modulation and hybrid modulation; S403. Adjust the modulation parameters to optimize the return power of the DAB converter under soft-switching conditions. S404. Dynamically optimize modulation parameters based on the real-time operating conditions of the ship's integrated power system to ensure maximum efficiency.

[0087] According to the above steps, in step S401, the system selects the optimal modulation strategy based on the voltage and current stress data generated by the constructed refined mathematical model. The voltage and current stress of the DAB converter is compared with the preset safety threshold. When the voltage and current stress is low, a phase shift modulation strategy with lower computational complexity is selected; when the voltage and current stress is moderate, a hybrid modulation strategy that balances efficiency and performance is selected; when the voltage and current stress is high, a pulse width modulation strategy that can provide better control performance is selected. This modulation strategy selection mechanism based on voltage and current stress ensures that the DAB converter can operate within a safe range under various operating conditions.

[0088] In step S402, the system intelligently switches between phase-shift modulation, pulse width modulation, and hybrid modulation. The intelligent switching mechanism is based on a determined optimal switching threshold. When the system detects a change in the power grid state or load demand, it automatically switches between different modulation strategies. For example, when a ship switches from cruise mode to combat mode, the system automatically switches from phase-shift modulation to hybrid modulation to improve the system's response speed to power grid disturbances. When a ship switches from high load mode to low load mode, the system automatically switches from pulse width modulation to phase-shift modulation to reduce control complexity and avoid the efficiency degradation problem caused by traditional fixed modulation strategies.

[0089] In step S403, the system adjusts the modulation parameters to optimize the return current power of the DAB converter under soft-switching conditions. Based on the generated soft-switching boundary conditions and the optimized return current power operating point, the system dynamically adjusts modulation parameters such as the phase shift angle, switching frequency, and duty cycle. For example, in phase-shift modulation mode, the system adjusts the phase shift angle to make the DAB converter operate within the soft-switching boundary; in pulse-width modulation mode, the system adjusts the duty cycle to make the DAB converter operate under soft-switching conditions with optimized return current power. By adjusting the modulation parameters based on the soft-switching boundary and the optimized return current power operating point, the switching losses of the DAB converter are effectively reduced while meeting the soft-switching conditions, and the return current power is optimized within an acceptable range, thereby improving the overall system efficiency.

[0090] In step S404, the system dynamically optimizes the modulation parameters based on the real-time operating conditions of the ship's integrated power system to ensure maximum efficiency. The system monitors parameters such as grid voltage, frequency, and load power in real time, and calculates the optimal modulation parameters under the current operating conditions by combining the constructed refined mathematical model. For example, when the grid voltage increases, the system automatically reduces the phase shift angle to avoid excessive transmission power; when the load power increases, the system automatically increases the switching frequency to improve the power transmission capacity. This dynamic optimization mechanism enables the DAB converter to operate in the high-efficiency region under various operating conditions.

[0091] like Figure 6 As shown, a shipboard integrated power system includes a power generation system, a power distribution system, a load system, and an energy management system. The energy management system, which integrates energy storage and conversion, is integrated into the shipboard power distribution system and connected to the power generation system and the load system. It is used to smooth out fluctuations in the shipboard power grid, provide emergency power supply, and optimize energy distribution.

[0092] Among them, the integrated energy management system for energy storage and conversion uses the refined mathematical model and state machine of the DAB converter to predict future power demand based on the ship's navigation status and the power grid load curve, generate charging and discharging strategies for the energy storage device, realize the overall efficiency adjustment of the ship's integrated power system, and adjust the state of charge of the energy storage device to the optimal range in advance before predicting high load demand.

[0093] The above predictions are made using methods such as big data, human experience, and large models.

[0094] As an optional embodiment, the integrated energy management system for energy storage and conversion is communicatively connected to the ship's integrated monitoring system, receives navigation status information and mission instructions, and dynamically adjusts the energy management strategy according to the power demand of the ship at different mission stages. This enables the ship's integrated power system to prioritize power supply to critical systems during high-priority mission stages, prioritize improving system efficiency during cruise mode, and prioritize using shore power to charge energy storage devices during berthing mode.

[0095] As an optional embodiment, the integrated energy management system for energy storage and conversion works in conjunction with the ship's propulsion system to provide instantaneous power support when the ship accelerates or turns, thereby reducing the impact on the main power generation system; When a ship decelerates or brakes, braking energy is recovered to improve energy utilization efficiency and enable energy recovery from the ship's propulsion system.

[0096] Based on the above, during system operation, the integrated energy management system for energy storage and conversion analyzes the ship's navigation status and grid load curves based on the refined mathematical model and state machine of the DAB converter to predict future power demand. This prediction process not only considers the current operating conditions but also incorporates factors such as the ship's mission plan and equipment start-up and shutdown plans, making the prediction results more accurate and reliable. Based on the prediction results, the system generates charging and discharging strategies for the energy storage devices. Under normal operating conditions, the charging and discharging strategies are dynamically adjusted through an energy optimization mode to optimize the overall system efficiency. When a high load demand is predicted to occur, the system adjusts the state of charge of the energy storage devices to the optimal range in advance to ensure that sufficient power support can be provided immediately when the high load demand arrives, while avoiding overcharging or over-discharging of the energy storage devices.

[0097] As an optional implementation, the integrated energy management system for energy storage and conversion establishes a communication connection with the ship's comprehensive monitoring system to receive navigation status information and mission instructions in real time. When the system identifies that the ship is in a high-priority mission phase, it automatically adjusts the energy management strategy to prioritize power supply to critical systems. When the ship is in cruise mode, the system automatically optimizes the energy allocation strategy to improve system efficiency. When the ship is in berthing mode, the system prioritizes using shore power to charge the energy storage devices. This dynamic energy management strategy based on mission phase enables the system to adapt to the power demand characteristics of the ship under different mission scenarios, significantly improving the system's adaptability and flexibility.

[0098] As another optional embodiment, the integrated energy storage and conversion energy management system establishes a collaborative working mechanism with the ship's propulsion system. When the ship accelerates or turns, the system quickly switches to power compensation mode through a state machine to provide instantaneous power support and reduce the impact on the main power generation system. When the ship decelerates or brakes, the system automatically switches to energy recovery mode to recover braking energy and improve energy utilization efficiency. By establishing a collaborative working mechanism between the integrated energy storage and conversion energy management system and the ship's propulsion system, not only can energy utilization efficiency be improved, but the burden on the main power generation system can also be reduced, and the service life of the equipment can be extended.

[0099] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0100] According to another aspect of the present invention, an electronic device is also provided, the electronic device including a memory and a processor; the memory is used to store a program; the processor executes the program to implement the method of any of the foregoing.

[0101] According to another aspect of the present invention, a computer-readable storage medium is also provided, the storage medium storing a computer program that, when executed by a processor, implements the method of any of the foregoing.

[0102] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the method described in any of the foregoing.

[0103] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. An integrated energy management system for energy storage and conversion in shipboard integrated power systems, characterized in that, include: A power input interface is used to connect to the ship's power generation system, and an energy storage conversion unit is set up to connect to the power input interface. The energy storage conversion unit includes a DAB converter and an energy storage device. The energy storage conversion unit is connected to an energy management controller, which is used to monitor the status of the ship's integrated power system in real time and control the working mode of the energy storage conversion unit. The energy storage conversion unit is connected to a multi-functional output interface for connecting various loads on the ship. The energy management controller employs a state machine to manage the switching between complex operating modes. The state machine is based on a refined mathematical model of the DAB converter constructed using time-domain analysis and frequency-domain Fourier series expansion. It dynamically adjusts the operating mode according to ship operating conditions, power grid conditions, and load requirements. The refined mathematical model establishes a simplified multi-parameter coupling model by offline analysis of the parasitic parameter characteristics of switching devices, magnetic components, and wiring structures in the DAB converter, combined with time-domain equivalent circuit model and frequency-domain harmonic analysis. This model generates soft-switching boundary conditions and return power optimization operating points to improve the operating efficiency and control voltage and current stress of the DAB converter. The simplified multi-parameter coupling model is designed to ensure that its complexity is suitable for real-time control system applications through experimental data fitting and parameter reduction.

2. The integrated energy management system for energy storage and conversion for shipboard integrated power systems according to claim 1, characterized in that: The refined mathematical model of the DAB converter includes a time-domain model and a frequency-domain model. The time-domain model is established based on the circuit topology changes in the on and off states of the switching transistor and is used to generate the transient response characteristics of the DAB converter. The frequency domain model decomposes the periodic waveform into harmonic components using the Fourier series expansion method to generate the steady-state characteristics of the DAB converter. The energy management controller dynamically switches between the time domain model and the frequency domain model according to the real-time operating conditions of the ship's integrated power system to control the operating characteristics of the DAB converter.

3. The integrated energy management system for energy storage and conversion for shipboard integrated power systems according to claim 1, characterized in that: The energy management controller includes a status monitoring module, a mode decision module, and a control execution module. The status monitoring module collects the ship's power grid voltage, frequency, load power, and energy storage device state of charge parameters in real time.

4. The integrated energy management system for energy storage and conversion for shipboard integrated power systems according to claim 1, characterized in that: The mode decision module adopts a fuzzy adaptive control algorithm based on a refined mathematical model. It dynamically adjusts the mode switching threshold according to different ship navigation states and the degree of power grid disturbance. The fuzzy adaptive control algorithm outputs the adjustment amount of the power grid frequency deviation switching threshold, voltage deviation switching threshold and load mutation rate switching threshold according to the power demand characteristics of different mission stages of the ship, so that the state machine can adapt to different navigation states and the degree of power grid disturbance. The mode decision module employs a fuzzy adaptive control algorithm based on a refined mathematical model, including the following steps: The input variable fuzzification unit converts the power grid frequency deviation, voltage deviation, and load mutation rate into corresponding fuzzy sets. The fuzzy rule base unit is constructed based on the operational experience and historical fault data of ship power systems, and establishes a mapping relationship between the input fuzzy set and the switching threshold adjustment amount. The adaptive adjustment unit dynamically adjusts the rule base parameters according to the ship's mission phase and the DAB converter's operating status. The deblurring unit uses the centroid method to calculate the final output switching threshold adjustment.

5. The integrated energy management system for energy storage and conversion for shipboard integrated power systems according to claim 1, characterized in that: The energy storage device includes a lithium-ion battery pack and a supercapacitor pack, which are connected in parallel via an internally integrated DAB converter. The lithium-ion battery pack provides continuous energy, while the supercapacitor pack provides instantaneous power compensation.

6. The integrated energy management system for energy storage and conversion for shipboard integrated power systems according to claim 1, characterized in that: The state machine includes a normal operation state, a power grid disturbance state, a load change state, and an emergency state, and the states are switched through preset switching conditions. The switching conditions include ship power grid frequency deviation, voltage deviation, and load mutation rate. The energy management controller dynamically adjusts the switching threshold between each state based on the soft switching boundary conditions generated by the refined mathematical model. The energy management controller also dynamically adjusts the modulation strategy of the DAB converter based on the voltage and current stress generated by the refined mathematical model. The modulation strategies include phase-shift modulation, pulse width modulation, and hybrid modulation. The energy management controller switches between different modulation strategies according to the real-time operating conditions of the ship's integrated power system.

7. An integrated energy management method for energy storage and conversion in shipboard integrated power systems, characterized in that, The integrated energy management system for energy storage and conversion for shipboard integrated power systems as described in any one of claims 1-6 includes the following steps: A refined mathematical model of the DAB converter is constructed based on time-domain analysis and frequency-domain Fourier series expansion. Based on a refined mathematical model, a state machine is applied to manage the switching between complex operating modes of the ship's integrated power system; Real-time monitoring of shipboard power grid parameters, energy storage device status, and load demand; Based on real-time monitoring data and refined mathematical models, power grid stability indicators and load demand change rates are calculated. Based on power grid stability indicators and load demand change rate, the optimal working mode is determined by state machine. Adjust the modulation strategy and operating parameters of the DAB converter according to the determined operating mode; When a ship's electrical grid failure or load change is detected, the system switches to the corresponding operating mode via a state machine to maintain a stable power supply to the ship's critical loads.

8. The integrated energy management method for energy storage and conversion in shipboard integrated power systems according to claim 7, characterized in that, The construction of the refined mathematical model of the DAB converter includes the following steps: The parasitic parameter characteristics of switching devices, magnetic components and wiring structures in DAB converters are analyzed through offline experiments and finite element simulation. A parameterized model is established based on the analysis results. A time-domain model considering the influence of parasitic parameters is established, wherein the time-domain model is a time-domain equivalent circuit model; The periodic waveform is decomposed into harmonic components using the Fourier series expansion method, and a frequency domain model is established. By combining the time-domain model and the frequency-domain model, the soft-switching boundary of the DAB converter under different operating conditions is generated; Based on the calculation results, the optimized operating point for return power and the optimized parameters for voltage and current stress are generated. Parameter reduction processing includes the following steps: The multiphysics coupling model is decomposed into multiple single-physics sub-models; Sensitivity analysis was performed on each sub-model to identify key parameters that significantly affect system performance; Based on experimental data, key parameters are fitted to establish a mapping relationship between parameters and system performance; The mapping relationship is transformed into a simplified lookup table or polynomial expression for use in real-time control systems.

9. The integrated energy management method for energy storage and conversion in shipboard integrated power systems according to claim 7, characterized in that, The state machine switching conditions are determined through the following steps: The soft-switching boundary conditions under different operating conditions are calculated based on the refined mathematical model described above. Analyze the impact of grid frequency deviation, voltage deviation and load mutation rate on the operating characteristics of DAB converter; Determine the optimal switching threshold between each state so that the DAB converter can maintain high efficiency in different operating modes; The switching threshold is dynamically adjusted based on the power demand characteristics of the ship at different mission stages.

10. The integrated energy management method for energy storage and conversion in shipboard integrated power systems according to claim 7, characterized in that, The steps for adjusting the modulation strategy and operating parameters of the DAB converter include: Based on the voltage and current stress generated by the refined mathematical model, the optimal modulation strategy is selected; Intelligent switching between phase-shift modulation, pulse-width modulation, and hybrid modulation; Adjust the modulation parameters to optimize the return power of the DAB converter under soft-switching conditions; The modulation parameters are dynamically optimized based on the real-time operating conditions of the ship's integrated power system to ensure maximum efficiency.

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