New energy ship adaptive navigational speed control method and system based on digital twinning

Abstract

The invention discloses a new energy ship adaptive navigational speed control method and system based on digital twinning, and relates to the related technical field of ship automatic control, and the method comprises the steps: calling geometric parameters of a new energy ship, and carrying out the multi-physics field dynamic analysis; constructing a digital twinborn body of the new energy ship; synchronizing the ship operation data set to the digital twin body for simulation calculation; and constraint is carried out according to a preset navigation target, a navigation speed control strategy is formulated, feedback optimization is carried out on the digital twinborn body, and self-adaptive navigation speed control of the new energy ship is realized. The technical problems that in the prior art, complex operation working conditions of a new energy ship are difficult to accurately perceive, the navigational speed cannot be dynamically optimized according to the real-time state of the ship and external environment changes, the ship navigation efficiency is low, and energy waste is serious are solved. The technical effects that real-time mapping and simulation analysis of the ship operation state are achieved through the new energy ship digital twin, and the ship navigation efficiency and the energy utilization efficiency are improved are achieved.

Description

Technical Field

[0001] The present application relates to the technical field related to ship automatic control, and specifically to a method and system for adaptive speed control of new energy ships based on digital twins. Background Art

[0002] The application of new energy sources such as lithium batteries and hydrogen in ship propulsion has effectively reduced ship carbon emissions and fuel consumption. However, the intermittent energy supply and unstable power output of new energy ships pose numerous challenges to ship speed control. Traditional ship speed control, which is mostly based on fixed models and empirical parameters, is difficult to adapt to the complex and changing operating conditions of new energy ships. When faced with different sea conditions, weather conditions, and changes in ship load, it is often impossible to achieve accurate speed control, resulting in low ship navigation efficiency, serious energy waste, and even affecting the ship's navigation safety. At the same time, traditional control methods lack the ability to perceive and coordinate optimization of the ship's power system and the external environment in real time, affecting the accuracy of ship operation monitoring and control, and failing to fully utilize the navigation performance and energy utilization efficiency of new energy ships.

[0003] Therefore, in the current relevant technologies, there are technical problems such as difficulty in accurately sensing the complex operating conditions of new energy ships and inability to dynamically optimize the speed according to the real-time status of the ship and changes in the external environment, resulting in low ship navigation efficiency and serious energy waste. Summary of the Invention

[0004] This application provides an adaptive speed control method and system for new energy ships based on digital twins, which solves the technical problems in the existing technology that it is difficult to accurately perceive the complex operating conditions of new energy ships, and it is impossible to dynamically optimize the speed according to the real-time status of the ship and changes in the external environment, resulting in low ship navigation efficiency and serious energy waste. It achieves the technical effect of realizing real-time mapping and simulation analysis of the ship's operating status through the digital twin of the new energy ship, thereby improving the ship's navigation efficiency and energy utilization efficiency.

[0005] The present application provides an adaptive speed control method for new energy ships based on digital twins, which includes: retrieving geometric parameters of the new energy ship, performing multi-physical field dynamic analysis according to the geometric parameters, and obtaining new energy power information; introducing environmental perception parameters, and constructing a digital twin of the new energy ship in combination with the new energy power information; synchronizing the real-time collected ship operation data set to the digital twin for simulation calculation to obtain a ship twin operation parameter set; constraining the ship twin operation parameter set according to preset navigation goals, formulating a speed control strategy, executing the speed control strategy to perform feedback optimization on the digital twin, and realizing adaptive speed control of the new energy ship.

[0006] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: hull geometric point cloud identification is performed based on the geometric parameters of the new energy ship to obtain hull surface point cloud data; cabin structure analysis is performed based on the geometric parameters of the new energy ship to obtain cabin structure topology data; position analysis of the power equipment is performed based on the hull surface point cloud data and the cabin structure topology data to determine the power equipment layout coordinates; multi-physics field coupling calculation is performed on the new energy ship according to the power equipment layout coordinates, the hull surface point cloud data, and the cabin structure topology data to generate multi-physics field power data; the multi-physics field power data is integrated to generate a comprehensive power performance index set, the power configuration of the new energy ship is optimized according to the comprehensive power performance index set, and the new energy power information is determined.

[0007] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: performing interactive power calculations between the new energy ship and the fluid based on the power equipment layout coordinates and the hull surface point cloud data, and drawing a ship propulsion efficiency map; performing operating temperature rise calculations on the new energy ship according to the power equipment layout coordinates and the cabin structure topology data, and obtaining equipment thermal evacuation demand information; performing finite element analysis on the new energy ship according to the hull surface point cloud data and the cabin structure topology data to calculate the structural stress field, and generate hull vibration modal parameters; adding the ship propulsion efficiency map, the equipment thermal evacuation demand information, and the hull vibration modal parameters to the multi-physics field power data.

[0008] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: constructing a benchmark digital twin framework based on the geometric parameters of the new energy ship and the new energy power information; extracting the center of gravity of the new energy ship as the origin, constructing a follow-up coordinate system based on the new energy ship, performing spatial unification according to the follow-up coordinate system, and setting spatial benchmark information; extracting multiple ship operation timestamps based on the new energy power information, and setting time benchmark information according to the multiple ship operation timestamps; constructing a space-time alignment engine based on the spatial benchmark information and the time benchmark information; activating the space-time alignment engine, and dynamically mapping the environmental perception parameters and the new energy power information to the benchmark digital twin framework through the space-time alignment engine to generate an environment-power coupling field; performing digital mirroring through the environment-power coupling field to construct the digital twin.

[0009] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: constructing a multi-source operation data acquisition channel for new energy ships, and acquiring the ship operation data set in real time through the multi-source operation data acquisition channel; performing multi-level cleaning on the ship operation data set to generate a standardized twin input data stream; injecting the standardized twin input data stream into the dynamic data bus of the digital twin to generate multi-physical field coupling simulation parameters; performing multi-dimensional simulation according to the multi-physical field coupling simulation parameters, and performing simulation fusion on the multi-dimensional simulation results to generate the ship twin operation parameter set.

[0010] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: setting the data execution priority through the dynamic data bus, allocating the time slots of the standardized twin input data stream according to the data execution priority, and generating multiple data streams to be injected; injecting the multiple data streams to be injected into the dynamic data bus of the digital twin, formulating a multi-physics field simulation task; performing simulation analysis according to the multi-physics field simulation task, and obtaining the multi-physics field coupling simulation parameters.

[0011] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: executing the multi-physics field simulation task to perform motion simulation analysis and generate motion posture simulation parameters; executing the multi-physics field simulation task to perform energy simulation analysis and generate energy efficiency simulation parameters; executing the multi-physics field simulation task to perform structural force simulation analysis and generate structural stress simulation parameters; fusing the motion posture simulation parameters, the energy efficiency simulation parameters, and the structural stress simulation parameters to construct a simulation parameter matrix; performing credibility closed-loop verification on the simulation parameter matrix to generate a simulation parameter health value, and when the simulation parameter health value is higher than a preset health threshold, generating the multi-physics field coupling simulation parameters.

[0012] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: performing dynamic constraint analysis on the ship twin operating parameters according to the preset navigation target, and formulating power constraint conditions and motion constraint conditions; constraining the ship twin operating parameter set according to the power constraint conditions, and generating a ship twin operating power control range; constraining the ship twin operating parameter set according to the motion constraint conditions, and generating a ship twin operating motion control range; performing multi-objective speed optimization on the new energy ship based on the ship twin operating power control range and the ship twin operating motion control range, and generating a multi-objective speed control sequence; adding the multi-objective speed control sequence to the speed control strategy.

[0013] In a possible implementation, the adaptive speed control method for new energy ships based on digital twins also performs the following processing: sending the speed control strategy to the ship actuator for real-time execution recording to obtain the actual speed parameters of the new energy ship; performing deviation critical analysis based on the ship twin operating parameter set, and constructing an error-parameter mapping rule table; synchronizing the actual speed parameters to the error-parameter mapping rule table for matching to obtain an error feedback value; triggering online calibration of the digital twin according to the error feedback value, updating the digital twin and re-simulating the calculation, constructing a data optimization closed loop, and realizing adaptive speed control of the new energy ship.

[0014] The present application also provides an adaptive speed control system for new energy ships based on digital twins, and the system includes: a new energy power information acquisition module, which is used to retrieve the geometric parameters of the new energy ship, perform multi-physical field power analysis according to the geometric parameters, and obtain new energy power information; a digital twin construction module, which is used to introduce environmental perception parameters and construct a digital twin of the new energy ship in combination with the new energy power information; a ship twin operation parameter set acquisition module, which is used to synchronize the real-time collected ship operation data set to the digital twin for simulation calculation to obtain the ship twin operation parameter set; a speed control strategy formulation module, which is used to constrain the ship twin operation parameter set according to the preset navigation target, formulate a speed control strategy, execute the speed control strategy to perform feedback optimization on the digital twin, and realize adaptive speed control of the new energy ship.

[0015] The proposed method and system for adaptive speed control of new energy ships based on digital twins will retrieve the geometric parameters of new energy ships, conduct multi-physics field dynamic analysis, and obtain new energy power information. Environmental perception parameters will be introduced to construct a digital twin of the new energy ship. The ship's operating data set will be synchronized to the digital twin for simulation calculation to obtain the ship's twin operating parameter set. Constraints will be imposed according to preset navigation goals, speed control strategies will be formulated, and feedback optimization will be performed on the digital twin to achieve adaptive speed control of new energy ships. This solves the technical problems in the existing technology of difficulty in accurately sensing the complex operating conditions of new energy ships, inability to dynamically optimize the speed according to the ship's real-time status and changes in the external environment, resulting in low ship navigation efficiency and serious energy waste. This achieves the technical effect of achieving real-time mapping and simulation analysis of the ship's operating status through the digital twin of the new energy ship, thereby improving the ship's navigation efficiency and energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure are briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in precise order. Instead, various steps may be processed in reverse order or simultaneously as needed. Furthermore, other operations may be added to these processes, or one or more operations may be removed from these processes.

[0017] Figure 1 A flow chart of the adaptive speed control method for new energy ships based on digital twins provided in an embodiment of the present application.

[0018] Figure 2 Schematic diagram of the structure of the adaptive speed control system for new energy ships based on digital twins provided in an embodiment of the present application.

[0019] Explanation of the accompanying drawings: new energy power information acquisition module 10, digital twin construction module 20, ship twin operation parameter set acquisition module 30, speed control strategy formulation module 40. DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict, and the terms “first\second” involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. The terms “including” and “having” and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or that are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein are for the purpose of describing the embodiments of this application only.

[0023] The embodiment of the present application provides a new energy ship adaptive speed control method based on digital twin, such as Figure 1 As shown, the method includes:

[0024] Step S100: Retrieve geometric parameters of the new energy ship, perform multi-physics field dynamic analysis according to the geometric parameters, and obtain new energy power information.

[0025] Step S100 also includes step S110, performing hull geometric point cloud identification based on the geometric parameters of the new energy ship to obtain hull surface point cloud data; step S120, performing cabin structure analysis based on the geometric parameters of the new energy ship to obtain cabin structure topology data; step S130, performing position analysis on the power equipment according to the hull surface point cloud data and the cabin structure topology data to determine the power equipment layout coordinates; step S140, performing multi-physics field coupling calculation on the new energy ship according to the power equipment layout coordinates, the hull surface point cloud data, and the cabin structure topology data to generate multi-physics field power data; step S150, fusing the multi-physics field power data to generate a comprehensive power performance index set, optimizing the power configuration of the new energy ship according to the comprehensive power performance index set, and determining the new energy power information.

[0026] Preferably, the geometric parameters of the new energy ship are retrieved, that is, the hull dimensions, cabin layout, equipment installation position and other three-dimensional spatial structural parameters of the new energy ship are obtained through ship design drawings, 3D modeling software (such as CATIA, SolidWorks) or laser scanning, such as ship length, width, depth, hull surface equation, bulkhead position coordinates, etc.; the hull geometric point cloud is identified based on the geometric parameters of the new energy ship, that is, the hull surface is converted into a large number of three-dimensional coordinate points (point cloud) through discretization processing, such as the hull waterline surface, side surface The coordinates (x, y, z) of each point constitute point cloud data to realize digital modeling of the hull shape and obtain the hull surface point cloud data; then the cabin structure analysis is carried out based on the geometric parameters of the new energy ship, and the cabin structure (such as deck, bulkhead, partition) is topologically analyzed to obtain the cabin structure topology data, including determining the spatial position, connection relationship and boundary conditions of each cabin. For example, the bulkhead coordinates are determined by geometric parameters, and the cabin topology diagram (such as a tree structure) is generated to clarify the spatial distribution of the power equipment compartment, cargo hold, cab, etc.

[0027] Preferably, the position analysis of the power equipment is carried out in combination with the hull surface point cloud and the cabin topology data, that is, the installation feasibility of the power equipment (such as motors, battery packs, fuel cell stacks) is analyzed, including the configuration of position constraints to avoid the stress concentration area of ​​the hull and meet the load-bearing limit of the cabin; according to the matching degree between the equipment size and the cabin space, the optimal installation coordinates (such as X=10m, Y=2m, Z=3m) are determined, and finally the power equipment layout coordinates are generated to provide the precise spatial position parameters of the equipment. Then, multi-physics field coupling calculations are performed on the new energy ship according to the power equipment layout coordinates, hull surface point cloud data, and cabin structure topology data. This may include, based on the hull surface point cloud, calculating the water resistance and wave-making resistance of the ship at different speeds in the fluid mechanics field through CFD simulation; analyzing the stress and deformation of the hull and equipment under dynamic loads through finite element analysis (FEA) in the structural mechanics field; calculating the heat distribution and heat dissipation requirements of the power equipment (such as batteries and motors) during operation in the thermal field; and analyzing the electromagnetic field distribution and energy loss of the motor for the electric propulsion unit in the electromagnetic field; specifically, importing the power equipment layout coordinates, hull point cloud, and cabin topology into the multi-physics field simulation software, setting boundary conditions (such as speed, sea conditions, and ambient temperature), and coupling various physical fields to generate multi-physics field power data, such as the hull resistance-power curve at different speeds, the heat loss distribution of the power equipment, and the stress cloud map of the hull structure.

[0028] Preferably, the multi-physical field power data is integrated to extract key indicators, which may include energy efficiency indicators (energy consumption per unit distance, power system efficiency), navigation performance indicators (maximum speed, acceleration response time), and safety indicators (equipment temperature threshold, structural stress safety margin), and then generate a comprehensive power performance indicator set; then the power configuration of the new energy ship is optimized, that is, according to the comprehensive power performance indicator set, the power system parameters (such as motor power, battery capacity, and propeller type) are adjusted through optimization algorithms (such as genetic algorithms and particle swarm algorithms). For example, if the energy consumption index is too high, the battery layout can be optimized to improve the heat dissipation efficiency, or the motor power distribution can be adjusted to reduce resistance loss. Finally, the new energy power information is determined, which may include the optimal layout plan of the power equipment, the power system parameter configuration (such as the motor rated power and the battery pack voltage platform), and the power output characteristic curve under typical working conditions (such as the speed-power correspondence), providing a data basis for adaptive speed control, and thus realizing the accurate modeling and optimization of the new energy ship power system.

[0029] Furthermore, step S140 also includes step S141, performing interactive power calculations on the new energy ship and the fluid based on the power equipment layout coordinates and the hull surface point cloud data, and drawing a ship propulsion efficiency map; step S142, performing operating temperature rise calculations on the new energy ship according to the power equipment layout coordinates and the cabin structure topology data, and obtaining equipment thermal evacuation demand information; step S143, performing finite element analysis on the new energy ship according to the hull surface point cloud data and the cabin structure topology data to calculate the structural stress field, and generate hull vibration modal parameters; step S144, adding the ship propulsion efficiency map, the equipment thermal evacuation demand information, and the hull vibration modal parameters to the multi-physics field power data.

[0030] Preferably, based on the layout coordinates of the power equipment (such as the position of the propeller and the direction of the motor axis) and the point cloud data of the hull surface, the interactive dynamic calculation of the new energy ship and the fluid is performed, that is, the movement of the ship in the water is simulated by computational fluid dynamics (CFD). Specifically, the hull surface grid (point cloud discretization result), the propeller geometric parameters (such as the propeller diameter and the number of blades), and the fluid medium properties (seawater density and viscosity) are used as input parameters to calculate the flow field distribution around the hull, the propeller wake effect and the thrust characteristics, and output the calculation results, that is, the ship propulsion efficiency map, where the horizontal axis is the speed (such as 0-20 knots) and the vertical axis is the propulsion efficiency (%). Different colors or curves represent open water efficiency (the efficiency of the propeller working alone), hull efficiency (the matching efficiency of the hull and the propeller) or the total propulsion efficiency (the comprehensive efficiency after considering the influence of appendage resistance and wake). For example, when the speed is 12 knots, the map shows that the total efficiency of the propeller can reach 78% under a certain layout, while the efficiency drops to 72% when the layout is offset by 0.5 meters.

[0031] Preferably, the operating temperature rise of the new energy ship is calculated based on the power equipment layout coordinates (such as the installation position of the battery pack) and the cabin structure topology data (such as the insulation performance of the bulkhead and the direction of the ventilation duct), that is, a heat conduction-convection model is established. Specifically, the heat source is the power loss of the ship's power equipment (motor, inverter, battery) converted into heat (such as Joule heat during battery charging and discharging), and the heat transfer path is heat dissipation through air convection, bulkhead heat conduction, and forced cooling system (such as liquid cooling pipe). According to the temperature threshold (such as the battery safety temperature ≤55°C), the heat dissipation scheme parameters are determined, and then the thermal evacuation demand information of the output equipment is calculated, which may include a cloud map of the equipment surface temperature distribution (such as the highest temperature point of the battery pack is located in the corner, reaching 65°C) and the cabin air temperature field distribution (such as the temperature in the middle of the power compartment is 12°C higher than the entrance).

[0032] Preferably, finite element analysis is performed on the new energy ship based on the hull surface point cloud data and the cabin structure topology data to calculate the structural stress field. Specifically, finite element meshing is performed based on the hull surface point cloud data, that is, the hull is discretized into thousands of units (such as tetrahedrons and hexahedron units), and the point cloud density determines the mesh accuracy; boundary conditions are determined based on the cabin structure topology data, including determining the hydrostatic pressure, wave load, and power equipment vibration load (such as the periodic force generated by the rotation of the motor), and then the structural dynamics equations are solved to generate the hull vibration modal parameters, including stress concentration areas and vibration modes (natural frequencies and vibration shapes of each order, fatigue hot spots) of key parts of the hull (such as the bow and stern connections). Finally, the ship propulsion efficiency map, equipment thermal evacuation demand information and hull vibration modal parameters are integrated and added to the multi-physics field dynamic data, including ship-related numerical data (such as 75% propulsion efficiency at a certain speed, 52°C maximum equipment temperature, 150MPa maximum hull stress), visualization data (such as efficiency map, temperature cloud map, stress cloud map) and related constraints (such as temperature ≤ 55°C, stress ≤ 80% of the material allowable stress, and vibration frequency avoiding the 12-18Hz range).

[0033] Step S200: introducing environmental perception parameters and building a digital twin of the new energy ship in combination with the new energy power information.

[0034] Step S200 also includes step S210, constructing a benchmark digital twin framework based on the geometric parameters of the new energy ship in combination with the new energy power information; step S220, extracting the center of gravity of the ship as the origin based on the new energy ship, constructing a follow-up coordinate system, performing spatial unification according to the follow-up coordinate system, and setting the spatial benchmark information; step S230, extracting multiple ship operation timestamps based on the new energy power information, and setting the time benchmark information according to the multiple ship operation timestamps; step S240, constructing a space-time alignment engine according to the spatial benchmark information and the time benchmark information; step S250, activating the space-time alignment engine, and dynamically mapping the environmental perception parameters and the new energy power information to the benchmark digital twin framework through the space-time alignment engine to generate an environment-power coupling field; step S260, performing digital mirroring through the environment-power coupling field to construct the digital twin.

[0035] Preferably, environmental perception parameters are introduced, that is, real-time external environmental data are acquired through ship sensors (such as weather stations, radars, GPS), shore-based data (such as ocean forecasts) or satellite remote sensing, which may include meteorological parameters (wind speed, wind direction, temperature, air pressure), sea condition parameters (wave height, wave direction, tidal speed, sea water temperature) and geographical parameters (water depth, channel boundary, obstacle coordinates, such as reefs and other ship positions); then, the geometric parameters of new energy ships (three-dimensional coordinate point cloud of hull, cabin structure dimensions, equipment layout coordinates) and new energy power information (multi-physics field coupling calculation results) are used as input data, and parametric modeling is used to associate the geometric model with the power performance data to construct a benchmark digital twin framework to provide a three-dimensional model of the hull and equipment, as well as input and output of power, thermal, stress and other data.

[0036] Preferably, the center of gravity of the new energy ship is extracted as the origin O, and a following coordinate system O-XYZ that moves with the ship is constructed, wherein the X-axis points to the bow (forward direction), the Y-axis points to the starboard (horizontal direction perpendicular to the X-axis), and the Z-axis is vertically upward (forming a right-handed coordinate system with the X and Y axes). For example, the coordinates of a certain device in the following coordinate system are (10, 1, -2), which means that it is located 10 meters in front of the center of gravity, 1 meter to the starboard, and 2 meters below; then, all geometric and dynamic data are transformed according to the following coordinate system to achieve spatial unification, including converting the hull point cloud data from the global coordinate system to the following coordinate system, and mapping the environmental perception data (such as the direction of water flow velocity) to the relative velocity in the following coordinate system, such as the speed of the water flow relative to the ship is 2m / s along the -X direction.

[0037] Preferably, multiple ship operation timestamps are extracted from the new energy power information, including the start / stop time of the power equipment, the speed change time and the physical field data collection time, and then the time reference information is set according to the multiple ship operation timestamps, that is, the ship start time is set as t=0, and a continuous time axis is established. All data need to be marked with timestamps, for example, a certain propulsion efficiency data corresponds to t=600s, and a certain temperature data corresponds to t=605s, to ensure that the data is called in chronological order during subsequent simulations. Then, a spatiotemporal alignment engine is constructed based on the spatial reference information and time reference information. Specifically, a spatial conversion matrix of the ship's geometric parameters and environmental parameters is established through the moving coordinate system. The time reference information is then associated with the ship's operating status (such as speed and power output) to form a time-state mapping table. Kalman filtering and particle filtering are introduced to perform real-time calibration of spatial coordinates and time series to ensure the accuracy of the spatial reference; interpolation methods (such as cubic spline interpolation) are used to smooth the discrete data points in the time series to ensure the continuity of the time reference; and dynamic updates of spatial coordinates and time series are triggered by receiving real-time collected ship operating data (such as GPS position, attitude sensor data) and environmental data (such as weather radar data).

[0038] Preferably, when the environmental perception parameters (such as wind speed, wave height, water flow speed) or the ship's operating status (such as speed, steering angle) collected in real time change, the spatiotemporal alignment engine is triggered to start, and the environmental perception parameters and new energy power information are dynamically mapped to the benchmark digital twin framework. Specifically, environmental data such as wind speed and water flow are converted from the global coordinate system (such as longitude and latitude) to the ship's tracking coordinate system, and then the battery pack temperature, motor output power and other new energy power information are mapped to the corresponding position of the ship's three-dimensional model; the environmental data and power data collected by different sensors are sorted and synchronized according to a unified time base, and the mapping frequency is adjusted according to the speed of data changes, and finally a multi-dimensional data matrix with unified time and space is generated.

[0039] Preferably, an input layer is set to receive the multidimensional data matrix output by the spatiotemporal alignment engine; a calculation layer is set to call a multi-physical field coupling model for parallel calculation, for example, the fluid dynamics module calculates the external force acting on the ship, the thermodynamics module calculates the internal temperature of the equipment, and the energy flow module calculates the power demand; a feedback layer is set to make the calculation results of each physical field influence each other to form a coupling effect, for example, an increase in hull resistance leads to an increase in motor load, and the increase in motor load leads to an increase in heat generation, and the increase in heat generation further affects the motor efficiency; an output layer is set to generate visualization results of the environment-dynamic coupling field, such as the flow field distribution around the ship, the equipment temperature cloud map, the energy flow path, etc.; and then an environment-dynamic coupling field is generated.

[0040] Preferably, digital mirroring is finally performed through the environment-dynamic coupling field, specifically including combining the three-dimensional model of the ship in the benchmark digital twin framework with the real-time collected hull attitude data (such as roll angle and pitch angle) to generate a geometric mirror image synchronized with the physical ship in real time; mapping the calculation results of the environment-dynamic coupling field to the digital model to form a mirror image of the physical state; and then obtaining the digital mirror output result, and comparing it with the actual operation data of the physical ship, and continuously adjusting the parameters of the coupling field model to ensure that the errors between the two are within an acceptable range, such as the speed prediction error does not exceed ±0.5 knots, and the temperature prediction error does not exceed ±2°C. Finally, a digital twin of the new energy ship is obtained, which can reflect the operation status of the ship in real time, predict future trends, and support simulation-based decision optimization.

[0041] Step S300: synchronize the real-time collected ship operation data set to the digital twin for simulation calculation to obtain a ship twin operation parameter set.

[0042] Step S300 further includes step S310, constructing a multi-source operation data acquisition channel for new energy ships, and obtaining the ship operation data set in real time through the multi-source operation data acquisition channel; step S320, performing multi-level cleaning on the ship operation data set to generate a standardized twin input data stream; step S330, injecting the standardized twin input data stream into the dynamic data bus of the digital twin to generate multi-physics field coupling simulation parameters; step S340, performing multi-dimensional simulation according to the multi-physics field coupling simulation parameters, and fusion-simulating the multi-dimensional simulation results to generate the ship twin operation parameter set.

[0043] Preferably, industrial-grade sensors (high-precision IMU inertial measurement unit, ultrasonic wave height meter, etc.) are deployed to build a sensor network as a multi-source operation data acquisition channel for new energy ships, and the ship operation data set is obtained in real time through the multi-source operation data acquisition channel, which may include collecting hull status (GPS position, attitude angle, acceleration), power system data (battery voltage / current / SOC, motor speed / torque, fuel cell output power), environmental parameters (wind speed / direction, wave height / period, water temperature / salinity, water flow velocity) and ship control system data (speed command, rudder angle command, power mode switching signal and equipment operation status). The ship operation data set is cleaned at multiple levels, including outlier filtering, that is, using the Laida criterion to eliminate abnormal data; frequency normalization, that is, spline interpolation of low-frequency data (structural strain <1Hz) and sliding average filtering of high-frequency data (motor speed >100Hz); unit standardization, that is, uniform conversion to the international system of units and adding dimension labels; null value compensation, that is, predicting missing period data through the LSTM network; confidence labeling, that is, adding precision weights to each data point; and finally generating a standardized twin input data stream.

[0044] Preferably, the standardized twin input data stream is injected into the dynamic data bus of the digital twin. Specifically, the standardized twin input data stream is transmitted to the dynamic data bus of the digital twin through a message queue (such as Kafka). The dynamic data bus classifies the data according to the data type and distributes the data to the corresponding simulation module. For example, the collected sensor data (such as temperature and pressure) is directly mapped to the boundary conditions of the simulation model, the internal parameters of the simulation model are adjusted according to the equipment operating status (such as motor speed and pump valve opening), and the continuously changing data (such as speed and wind direction) are interpolated to ensure the data continuity within the simulation time step. Then, the fluid dynamics parameters are calculated based on the hull geometry and real-time water flow data; the thermal conductivity coefficient and convective heat transfer coefficient are set according to the equipment power and ambient temperature; the elastic modulus, Poisson's ratio and other parameters are determined based on the material properties and load distribution; wherein the pressure distribution obtained by the fluid calculation is used as the load for structural analysis, the temperature field generated by the equipment heat dissipation is used as the input for the fluid density calculation, and the heat source distribution is calculated according to the power system loss, and finally the multi-physics field coupling simulation parameters are generated.

[0045] Preferably, multi-dimensional simulation is performed according to the multi-physics field coupling simulation parameters, that is, distributed computing is used to realize the parallel execution of multi-physics field simulation, and the output of the previous time step is used as the input of the next time step, the continuous simulation results are discretized into space-time grid data, and then the multi-dimensional simulation results are simulated and fused, that is, the results of different physical fields are unified into the ship's moving coordinate system, the results of each field are converted into a unified physical unit, and then the key characteristic parameters (such as resistance coefficient, heat transfer coefficient, vibration frequency) are extracted, and finally a ship twin operation parameter set is generated, which may include navigation performance parameters, equipment status parameters, environmental adaptability parameters and time series data, which can be used for speed optimization, equipment scheduling and fault warning, and adaptive speed control is achieved through the feedback optimization mechanism of the digital twin.

[0046] Furthermore, step S330 also includes step S331, setting the data execution priority through the dynamic data bus, allocating the time slots of the standardized twin input data stream according to the data execution priority, and generating multiple data streams to be injected; step S332, injecting the multiple data streams to be injected into the dynamic data bus of the digital twin, and formulating a multi-physics field simulation task; step S333, performing simulation analysis according to the multi-physics field simulation task, and obtaining the multi-physics field coupling simulation parameters.

[0047] Preferably, the data execution priority is set through a dynamic data bus, that is, key data related to navigation safety (such as rudder angle anomalies, collision warnings) are set to the highest priority; high-frequency changing data are set to the second highest priority, data with a large impact on multi-physical field coupling (such as speed, wind direction) are set to medium priority, and non-critical data that can be delayed (such as equipment maintenance logs) are set to low priority; and the standardized twin input data stream is allocated time slots according to priority, including reserving a fixed proportion of bus bandwidth for data of different priorities (such as 40% for the highest priority, 30% for the second highest priority, 20% for the medium priority, and 10% for the low priority), and dynamically adjusting the time slots according to the real-time load conditions. For example, when the amount of highest priority data surges, the low priority time slots are temporarily occupied, and at the same time, high priority data can interrupt the transmission of low priority data; according to the priority and time slot allocation results, the standardized data stream is divided into multiple independent data streams to be injected, and each data stream to be injected contains information such as timestamp, data type, and priority identifier.

[0048] Preferably, multiple data streams to be injected are injected into the dynamic data bus of the digital twin, and multi-physics field simulation tasks are formulated, including: fluid simulation tasks, which are mapped to the ship hydrodynamic module to process the interaction data between the hull and the fluid (such as speed, draft, and water flow velocity); structural simulation tasks, which are mapped to the hull structure module to process stress and vibration related data (such as acceleration and load distribution); energy flow simulation tasks, which are mapped to the power system module to process energy conversion and distribution data (such as battery power and motor efficiency); thermal management simulation tasks, which are mapped to the thermodynamic module to process equipment heat dissipation and ambient temperature data; when specific data arrives, the corresponding physical field is triggered. simulation task; then simulation analysis is carried out according to the multi-physics field simulation task, including fluid simulation (calculating the flow field around the hull, resistance coefficient, and wave height), structural simulation (using the finite element method to analyze the stress distribution and deformation of the hull under wave loads), energy flow simulation (based on the power electronics model to calculate the battery discharge curve, motor efficiency curve, and energy loss) and thermal management simulation (through the heat conduction equation to simulate the equipment temperature rise process and heat dissipation efficiency), and finally obtain multi-physics field coupling simulation parameters, such as effective power demand, hull fatigue damage rate, and remaining battery life, to facilitate performance evaluation, fault warning, and control strategy optimization of new energy ships.

[0049] Furthermore, step S333 also includes step a, executing the multi-physics field simulation task to perform motion simulation analysis and generate motion posture simulation parameters; step b, executing the multi-physics field simulation task to perform energy simulation analysis and generate energy efficiency simulation parameters; step c, executing the multi-physics field simulation task to perform structural force simulation analysis and generate structural stress simulation parameters; step d, fusing the motion posture simulation parameters, the energy efficiency simulation parameters, and the structural stress simulation parameters to construct a simulation parameter matrix; step e, performing credibility closed-loop verification on the simulation parameter matrix to generate a simulation parameter health value, and when the simulation parameter health value is higher than a preset health threshold, generating the multi-physics field coupling simulation parameters.

[0050] Preferably, a multi-physics simulation task is executed to perform motion simulation analysis, that is, environmental parameters (wind speed and direction, water flow speed) and ship parameters (center of gravity position, moment of inertia, hull waterline area) are used as input data to simulate the six-degree-of-freedom motion of the ship under environmental loads (surge, sway, heave, pitch, roll, bow), and output motion attitude time series, including roll angle amplitude, heave displacement, and bow angular velocity, as motion attitude simulation parameters; a multi-physics simulation task is executed to perform energy simulation analysis, that is, ship power system parameters (battery capacity, motor efficiency curve, fuel cell polarization curve) and ship operating conditions (speed, propulsion power) are used to simulate the six-degree-of-freedom motion of the ship under environmental loads. The system takes the energy flow and loss path of new energy ships as input data, quantifies the energy flow and loss path of new energy ships, and outputs battery discharge power, motor loss, propeller efficiency, energy consumption per unit trip, and comprehensive efficiency of the energy conversion chain as energy efficiency simulation parameters; it performs multi-physics field simulation tasks to perform structural force simulation analysis, that is, using load conditions (wave bending moment, equipment vibration load) and ship structure parameters (hull plate thickness, material yield strength) as input data to evaluate the structural safety of the hull and equipment under dynamic loads, and outputs stress distribution cloud maps (such as the maximum stress at the bow connection and the stress in the middle of the deck) and fatigue damage parameters (such as hot spot stress range and cumulative fatigue damage degree).

[0051] Preferably, the motion posture simulation parameters, energy efficiency simulation parameters and structural stress simulation parameters are integrated to construct a simulation parameter matrix. Example data is shown in Table 1:

[0052] Table 1 Simulation parameter matrix data table

[0053]

[0054] Preferably, a closed-loop credibility verification is performed on the simulation parameter matrix. Specifically, the motion posture (such as the IMU measured roll angle), energy consumption (smart meter data), and stress (strain gauge measurement values) are collected through ship sensors to obtain a simulation result database of the same type of ship under similar working conditions; then the absolute error between the simulation parameters and the measured values ​​is calculated and it is determined whether the simulation results are within the confidence interval. The motion error, energy error, and structural error are then weighted and summed to obtain the health value of the simulation parameters. The preset health threshold is usually set to 0.8 (full score 1.0). When the health value is ≥0.8, the simulation parameters are considered to be credible and the multi-physics field coupling parameters are generated; when the health value is <0.8, the model correction process is triggered (such as adjusting the wave load calculation coefficient) and the simulation is re-simulated until the standard is met, thereby ensuring the simulation accuracy.

[0055] Step S400: Constrain the ship twin operating parameter set according to the preset navigation target, formulate a speed control strategy, execute the speed control strategy to perform feedback optimization on the digital twin, and realize adaptive speed control of the new energy ship.

[0056] Preferably, the preset navigation goals may include specifying an arrival time, specifying a route, limiting energy consumption, ensuring navigation safety, etc. Based on the preset navigation goals, a comprehensive analysis of the ship's twin operating parameters is conducted to generate constraints. For example, if the goal emphasizes energy consumption, upper limits are set for power parameters such as the maximum motor power and propulsion system efficiency; if the goal focuses on navigation time, a lower limit is set for the speed, and the range of motion attitude parameters that are not conducive to fast navigation is restricted. Then, a detailed speed control strategy is formulated based on the ship's current power performance, motion state, hull structure bearing capacity, external environmental conditions, and preset navigation goals. This may include setting target speeds for different navigation stages, such as slow and steady acceleration at the start, maintaining an economic speed during the mid-journey, and slowing down to dock when approaching the destination; and rules for adjusting the speed in real time according to environmental changes, such as reducing speed to reduce energy consumption when encountering headwinds, and appropriately increasing speed to shorten navigation time when encountering tailwinds.

[0057] Preferably, the formulated speed control strategy is sent to the actual actuator of the ship, such as the propeller control system, power distribution system, etc., to drive the ship to adjust the speed according to the strategy. At the same time, various sensors on the ship collect actual operating data in real time, including actual speed, power output, motion posture, etc. The actual collected data is synchronized to the digital twin, and compared with the predicted data in the ship twin operating parameter set to calculate the deviation. Then, based on the deviation result, the digital twin is feedback optimized to make it more accurately reflect the actual operating status of the ship. The digital twin after feedback optimization can more accurately predict the operating status of the ship under different speed control strategies, and then evaluate the effectiveness of the current speed control strategy in real time, and automatically adjust the speed control strategy according to the new environmental changes and ship status, so that the new energy ship always runs at the optimal speed, and finally realize the adaptive speed control of the new energy ship.

[0058] Furthermore, step S400 also includes step S410, performing dynamic constraint analysis on the twin operation parameters of the ship according to the preset navigation target, and formulating power constraint conditions and motion constraint conditions; step S420, constraining the twin operation parameter set of the ship according to the power constraint conditions, and generating a twin operation power control range of the ship; step S430, constraining the twin operation parameter set of the ship according to the motion constraint conditions, and generating a twin operation motion control range of the ship; step S440, performing multi-objective speed optimization on the new energy ship based on the twin operation power control range and the twin operation motion control range of the ship, and generating a multi-objective speed control sequence; step S450, adding the multi-objective speed control sequence to the speed control strategy.

[0059] Preferably, a dynamic constraint analysis is performed on the twin operating parameters of the ship according to the preset navigation goals, taking into account the current power performance, motion state and external environmental conditions of the ship, evaluating the impact of each parameter on the goal achievement, and formulating power constraint conditions, that is, setting restrictions around the operating state of the ship's power system, including the upper limit of battery power, the maximum power of the motor, the output power range of the fuel cell, etc., to prevent over-limit damage to key equipment such as batteries and motors; formulating motion constraint conditions, and formulating constraints for the ship's navigation attitude and structural stress, such as the maximum roll angle, the maximum pitch angle, the maximum speed, the minimum turning radius, etc., to ensure that the ship remains stable in complex sea conditions and prevent structural damage due to excessive movement.

[0060] Preferably, according to the power constraint conditions, the power-related parameters in the ship twin operation parameter set are screened and restricted. Through calculation and analysis, the feasible value range of the power parameters (such as motor speed and propulsion power) is determined while satisfying the power constraint, and the ship twin operation power control range is generated. For example, the motor speed is controlled at 500-1200 rpm, and the propulsion power shall not exceed 300kW; according to the motion constraint conditions, the motion parameters (such as speed, heading angle, roll angle, and pitch angle) in the ship twin operation parameter set are constrained, and the reasonable variation range of these parameters is determined under the premise of ensuring the safe and stable movement of the ship, and the ship twin operation motion control range is generated, such as the speed needs to be maintained at 8-15 knots and the roll angle does not exceed 10 degrees.

[0061] Preferably, a multi-objective speed optimization model is constructed based on the power control interval and motion control interval of the ship twin operation, and multiple objectives such as navigation time, energy consumption, and safety are comprehensively considered to establish an objective function. For example, the weighted sum of navigation time and energy consumption is minimized under the premise of meeting safety and power constraints; then an intelligent optimization algorithm (such as genetic algorithm, particle swarm optimization algorithm) is used to solve the multi-objective speed optimization model, and the optimal solution is searched within the power and motion control interval to determine the optimal speed in different navigation stages; according to the optimization results, multiple speed instructions are generated in chronological order to form a multi-objective speed control sequence, which clarifies the speed that the ship should reach at each time node to achieve multi-objective balance and optimization; finally, the multi-objective speed control sequence is added to the speed control strategy. During the actual navigation of the ship, the speed control strategy dynamically adjusts and precisely controls the ship speed according to the multi-objective speed control sequence based on the real-time collected ship operation data and environmental information, combined with the simulation results of the digital twin, to ensure that the ship can efficiently and safely complete the preset navigation goals.

[0062] Furthermore, step S400 also includes step S460, sending the speed control strategy to the ship actuator for real-time execution recording to obtain the actual speed parameters of the new energy ship; step S470, performing deviation critical analysis based on the ship twin operation parameter set, and constructing an error-parameter mapping rule table; step S480, synchronizing the actual speed parameters to the error-parameter mapping rule table for matching to obtain an error feedback value; step S490, triggering online calibration of the digital twin according to the error feedback value, updating the digital twin and re-simulating the calculation, constructing a data optimization closed loop, and realizing adaptive speed control of the new energy ship.

[0063] Preferably, the speed control sequence is sent to the propulsion system controller (such as a frequency converter, a motor driver) through the ship network. After the actuator receives the instruction, it realizes speed tracking through PID control, and uses a Doppler speed meter, a GPS speed module, etc. to collect the actual speed of the new energy ship, and synchronously records the execution timestamp, the control instruction value and the actual response value to form the actual speed parameter; then, a deviation critical analysis is performed based on the ship twin operation parameter set. Specifically, different deviation thresholds are set according to the ship load (such as cargo capacity) and the severity of the environment, such as the speed deviation critical value of ±0.5 knots (normal working conditions) / ±1 knots (harsh sea conditions), the energy consumption deviation critical value of ±5% (short term) / ±10% (long term), and an error-parameter mapping rule table is constructed based on historical fault data statistics, as shown in Table 2:

[0064] Table 2 Error-parameter mapping rules

[0065] Error type Possible cause parameters Mapping relationship (error → influencing parameter) Speed ​​overshoot>0.5 knots Water flow resistance calculation deviation Water flow speed parameter correction +10% Abnormally high energy consumption Motor efficiency model error Motor loss coefficient correction +5% Roll angle exceeds limit Inadequate wave load simulation Wave spectrum density parameter correction +15%

[0066] Preferably, the actual speed parameters are compared with the twin operation parameters, the absolute error is calculated, and the error trend is analyzed in combination with the time series. Then, the error-parameter mapping rule table is synchronized for matching to obtain the error feedback value. For example, the positive deviation of the speed is 0.4 knots and continues to increase. The water flow resistance calculation is too small, and the feedback value of the water flow speed parameter needs to be increased by 10%. Then, the online calibration of the digital twin is triggered according to the error feedback value, including adjusting the simulation model input parameters (such as correcting the water flow speed from 2m / s to 2.1m / s), dynamically updating the equipment efficiency curve (such as lowering the overall motor efficiency curve based on the high measured energy consumption). 3%), when the error continues to exceed the threshold (such as the speed error is >0.5 knots for 10 consecutive minutes), the model structure optimization is triggered, the digital twin is updated and the multi-physics field coupling simulation calculation is re-performed to generate a new set of ship twin operation parameters, and the dynamic synchronization of the model and the actual operation status is achieved. Then, a complete data optimization closed loop is constructed, the deviation between the actual and twin data is monitored in real time, and the digital twin is dynamically calibrated to more accurately reflect the real state of the ship, which is conducive to the dynamic adjustment of the speed control strategy, so that new energy ships can automatically optimize the speed according to environmental changes and equipment status, realize adaptive speed control, and improve navigation efficiency and safety.

[0067] In the above, refer to Figure 1 The adaptive speed control method of new energy ship based on digital twin according to the embodiment of the present invention is described in detail. Figure 2 The present invention describes an adaptive speed control system for new energy ships based on digital twins according to an embodiment of the present invention.

[0068] The adaptive speed control system for new energy ships based on digital twins according to an embodiment of the present invention is used to solve the technical problems in the prior art that it is difficult to accurately perceive the complex operating conditions of new energy ships and it is impossible to dynamically optimize the speed according to the real-time status of the ship and changes in the external environment, resulting in low ship navigation efficiency and serious energy waste. It achieves the technical effect of realizing real-time mapping and simulation analysis of the ship's operating status through the digital twin of the new energy ship, thereby improving the ship's navigation efficiency and energy utilization efficiency. Figure 2 As shown, the new energy ship adaptive speed control system based on digital twin includes: a new energy power information acquisition module 10, a digital twin construction module 20, a ship twin operation parameter set acquisition module 30, and a speed control strategy formulation module 40.

[0069] The new energy power information acquisition module 10 is used to retrieve the geometric parameters of the new energy ship, perform multi-physical field power analysis according to the geometric parameters, and obtain the new energy power information; the digital twin construction module 20 is used to introduce environmental perception parameters and construct the digital twin of the new energy ship in combination with the new energy power information; the ship twin operation parameter set acquisition module 30 is used to synchronize the real-time collected ship operation data set to the digital twin for simulation calculation to obtain the ship twin operation parameter set; the speed control strategy formulation module 40 is used to constrain the ship twin operation parameter set according to the preset navigation target, formulate the speed control strategy, execute the speed control strategy to perform feedback optimization on the digital twin, and realize the adaptive speed control of the new energy ship.

[0070] The specific configuration of the new energy power information acquisition module 10 will be described in detail below. The new energy power information acquisition module 10 further includes: performing hull geometric point cloud identification based on the geometric parameters of the new energy ship to obtain hull surface point cloud data; performing cabin structure analysis based on the geometric parameters of the new energy ship to obtain cabin structure topology data; performing position analysis on the power equipment based on the hull surface point cloud data and the cabin structure topology data to determine the power equipment layout coordinates; performing multi-physics field coupling calculation on the new energy ship based on the power equipment layout coordinates, the hull surface point cloud data, and the cabin structure topology data to generate multi-physics field power data; fusing the multi-physics field power data to generate a comprehensive power performance index set, optimizing the power configuration of the new energy ship based on the comprehensive power performance index set, and determining the new energy power information.

[0071] The specific configuration of the new energy power information acquisition module 10 will be described in detail below. The new energy power information acquisition module 10 further includes: performing interactive power calculations between the new energy ship and the fluid based on the power equipment layout coordinates and the hull surface point cloud data, and drawing a ship propulsion efficiency map; calculating the operating temperature rise of the new energy ship according to the power equipment layout coordinates and the cabin structure topology data to obtain equipment thermal evacuation demand information; performing finite element analysis on the new energy ship based on the hull surface point cloud data and the cabin structure topology data to calculate the structural stress field and generate hull vibration modal parameters; and adding the ship propulsion efficiency map, the equipment thermal evacuation demand information, and the hull vibration modal parameters to the multi-physics field power data.

[0072] The specific configuration of the digital twin construction module 20 will be described in detail below. The digital twin construction module 20 further includes: constructing a reference digital twin framework based on the geometric parameters of the new energy ship in combination with the new energy power information; extracting the center of gravity of the new energy ship as the origin, constructing a follow-up coordinate system, performing spatial unification according to the follow-up coordinate system, and setting spatial reference information; extracting multiple ship operation timestamps based on the new energy power information, and setting time reference information according to the multiple ship operation timestamps; constructing a spatiotemporal alignment engine based on the spatial reference information and the time reference information; activating the spatiotemporal alignment engine, and dynamically mapping the environmental perception parameters and the new energy power information to the reference digital twin framework through the spatiotemporal alignment engine to generate an environment-power coupling field; and performing digital mirroring through the environment-power coupling field to construct the digital twin.

[0073] The specific configuration of the ship twin operation parameter set acquisition module 30 will be described in detail below. The ship twin operation parameter set acquisition module 30 further includes: constructing a multi-source operation data acquisition channel for new energy ships, and acquiring the ship operation data set in real time through the multi-source operation data acquisition channel; performing multi-level cleaning on the ship operation data set to generate a standardized twin input data stream; injecting the standardized twin input data stream into the dynamic data bus of the digital twin to generate multi-physics field coupling simulation parameters; performing multi-dimensional simulation according to the multi-physics field coupling simulation parameters, and performing simulation fusion on the multi-dimensional simulation results to generate the ship twin operation parameter set.

[0074] The specific configuration of the ship twin operation parameter set acquisition module 30 will be described in detail below. The ship twin operation parameter set acquisition module 30 further includes: setting a data execution priority through the dynamic data bus, allocating time slots of the standardized twin input data stream according to the data execution priority, and generating multiple data streams to be injected; injecting the multiple data streams to be injected into the dynamic data bus of the digital twin, formulating a multi-physics field simulation task; and performing simulation analysis according to the multi-physics field simulation task to obtain the multi-physics field coupling simulation parameters.

[0075] The specific configuration of the ship twin operation parameter set acquisition module 30 will be described in detail below. The ship twin operation parameter set acquisition module 30 further includes: executing the multi-physics field simulation task to perform motion simulation analysis and generate motion posture simulation parameters; executing the multi-physics field simulation task to perform energy simulation analysis and generate energy efficiency simulation parameters; executing the multi-physics field simulation task to perform structural force simulation analysis and generate structural stress simulation parameters; fusing the motion posture simulation parameters, the energy efficiency simulation parameters, and the structural stress simulation parameters to construct a simulation parameter matrix; performing credibility closed-loop verification on the simulation parameter matrix to generate a simulation parameter health value. When the simulation parameter health value is higher than a preset health threshold, the multi-physics field coupling simulation parameters are generated.

[0076] The specific configuration of the speed control strategy formulation module 40 will be described in detail below. The speed control strategy formulation module 40 further includes: performing dynamic constraint analysis on the ship twin operation parameters according to the preset navigation target, formulating power constraint conditions and motion constraint conditions; constraining the ship twin operation parameter set according to the power constraint conditions to generate a ship twin operation power control interval; constraining the ship twin operation parameter set according to the motion constraint conditions to generate a ship twin operation motion control interval; performing multi-objective speed optimization on the new energy ship based on the ship twin operation power control interval and the ship twin operation motion control interval to generate a multi-objective speed control sequence; and adding the multi-objective speed control sequence to the speed control strategy.

[0077] The specific configuration of the speed control strategy formulation module 40 will be described in detail below. The speed control strategy formulation module 40 further includes: issuing the speed control strategy to the ship's actuator for real-time execution recording to obtain the actual speed parameters of the new energy ship; performing deviation criticality analysis based on the ship twin operating parameter set and constructing an error-parameter mapping rule table; synchronizing the actual speed parameters to the error-parameter mapping rule table for matching to obtain an error feedback value; triggering online calibration of the digital twin based on the error feedback value, updating the digital twin and re-simulating the calculation, constructing a data optimization closed loop, and realizing adaptive speed control of the new energy ship.

[0078] The adaptive speed control system for new energy ships based on digital twins provided in an embodiment of the present invention can execute the adaptive speed control method for new energy ships based on digital twins provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0079] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0080] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. The adaptive speed control method of new energy ships based on digital twin is characterized by: The method comprises: Retrieving geometric parameters of the new energy ship, performing multi-physics field dynamic analysis according to the geometric parameters, and obtaining new energy power information; Introducing environmental perception parameters and combining the new energy power information to build a digital twin of the new energy ship; Synchronizing the real-time collected ship operation data set to the digital twin for simulation calculation to obtain the ship twin operation parameter set; The ship twin operating parameter set is constrained according to the preset navigation target, a speed control strategy is formulated, and the speed control strategy is executed to perform feedback optimization on the digital twin to achieve adaptive speed control of new energy ships.

2. The adaptive speed control method for new energy ships based on digital twins according to claim 1 is characterized in that: Retrieving geometric parameters of the new energy ship, performing multi-physics field dynamic analysis according to the geometric parameters, and obtaining new energy power information, the method includes: Performing hull geometric point cloud identification based on the geometric parameters of the new energy ship to obtain hull surface point cloud data; Perform cabin structure analysis based on the geometric parameters of the new energy ship to obtain cabin structure topology data; Performing position analysis on the power equipment based on the hull surface point cloud data and the cabin structure topology data to determine the layout coordinates of the power equipment; Perform multi-physics field coupling calculation on the new energy ship according to the power equipment layout coordinates, the hull surface point cloud data, and the cabin structure topology data to generate multi-physics field power data; The multi-physical field power data are integrated to generate a comprehensive power performance index set, the power configuration of the new energy ship is optimized according to the comprehensive power performance index set, and the new energy power information is determined.

3. The adaptive speed control method for new energy ships based on digital twins according to claim 2 is characterized in that: Performing multi-physics field coupling calculation on the new energy ship according to the power equipment layout coordinates, the hull surface point cloud data, and the cabin structure topology data to generate multi-physics field power data, the method includes: Perform interactive power calculations on the new energy ship and the fluid based on the power equipment layout coordinates and the hull surface point cloud data, and draw a ship propulsion efficiency map; Calculate the operating temperature rise of the new energy ship according to the power equipment layout coordinates and the cabin structure topology data to obtain equipment thermal evacuation demand information; Performing finite element analysis on the new energy ship based on the hull surface point cloud data and the cabin structure topology data to calculate the structural stress field and generate hull vibration modal parameters; The ship propulsion efficiency map, the equipment thermal evacuation demand information, and the hull vibration modal parameters are added to the multi-physics field power data.

4. The adaptive speed control method for new energy ships based on digital twins according to claim 1 is characterized in that: Introducing environmental perception parameters and combining the new energy power information to construct a digital twin of the new energy ship, the method includes: Constructing a benchmark digital twin framework based on the geometric parameters of the new energy ship and the new energy power information; Based on the new energy ship, the center of gravity of the ship is extracted as the origin, a follow-up coordinate system is constructed, and spatial unification is performed according to the follow-up coordinate system to set spatial reference information; extracting multiple ship operation timestamps based on the new energy power information, and setting time reference information according to the multiple ship operation timestamps; Building a spatiotemporal alignment engine according to the spatial reference information and the temporal reference information; activating the spatiotemporal alignment engine, and dynamically mapping the environmental perception parameters and the new energy power information to the benchmark digital twin framework through the spatiotemporal alignment engine to generate an environment-power coupling field; The digital twin is constructed by digitally mirroring the environment-dynamic coupling field.

5. The adaptive speed control method for new energy ships based on digital twins according to claim 1 is characterized in that: The real-time collected ship operation data set is synchronized to the digital twin for simulation calculation to obtain the ship twin operation parameter set, the method comprising: Constructing a multi-source operation data acquisition channel for new energy ships, and acquiring the ship operation data set in real time through the multi-source operation data acquisition channel; Performing multi-stage cleaning on the ship operation dataset to generate a standardized twin input data stream; Injecting the standardized twin input data stream into the dynamic data bus of the digital twin to generate multi-physics coupling simulation parameters; Multi-dimensional simulation is performed according to the multi-physics field coupling simulation parameters, and the multi-dimensional simulation results are simulated and fused to generate the ship twin operation parameter set.

6. The adaptive speed control method for new energy ships based on digital twins according to claim 5 is characterized in that: Injecting the standardized twin input data stream into the dynamic data bus of the digital twin to generate multi-physics coupling simulation parameters, the method comprising: Setting a data execution priority through the dynamic data bus, allocating time slots for the standardized twin input data stream according to the data execution priority, and generating a plurality of data streams to be injected; Injecting the multiple data streams to be injected into the dynamic data bus of the digital twin to formulate a multi-physics field simulation task; Perform simulation analysis according to the multi-physics field simulation task to obtain the multi-physics field coupling simulation parameters.

7. The adaptive speed control method for new energy ships based on digital twins according to claim 6 is characterized in that: Performing simulation analysis according to the multi-physics field simulation task to obtain the multi-physics field coupling simulation parameters includes: Executing the multi-physics field simulation task to perform motion simulation analysis and generate motion posture simulation parameters; Executing the multi-physics field simulation task to perform energy simulation analysis and generate energy efficiency simulation parameters; Executing the multi-physics field simulation task to perform structural force simulation analysis and generate structural stress simulation parameters; The motion posture simulation parameters, the energy efficiency simulation parameters, and the structural stress simulation parameters are integrated to construct a simulation parameter matrix; The simulation parameter matrix is ​​subjected to credibility closed-loop verification to generate a simulation parameter health value, and when the simulation parameter health value is higher than a preset health threshold, the multi-physics field coupling simulation parameter is generated.

8. The method for adaptive speed control of new energy ships based on digital twins according to claim 1, characterized in that: According to the preset navigation target, the twin operation parameter set of the ship is constrained to formulate a speed control strategy, and the method includes: Performing dynamic constraint analysis on the twin ship operating parameters according to the preset navigation target, and formulating dynamic constraint conditions and motion constraint conditions; Constraining the ship twin operation parameter set according to the power constraint condition to generate the ship twin operation power control range; Constraining the ship twin operation parameter set according to the motion constraint conditions to generate the ship twin operation motion control interval; Performing multi-objective speed optimization on the new energy ship based on the ship twin operation power control interval and the ship twin operation motion control interval to generate a multi-objective speed control sequence; The multi-objective speed control sequence is added to the speed control strategy.

9. The method for adaptive speed control of new energy ships based on digital twins according to claim 1, characterized in that: The speed control strategy is executed to perform feedback optimization on the digital twin to achieve adaptive speed control of the new energy ship. The method includes: The speed control strategy is sent to the ship's executive body for real-time execution and recording, thereby obtaining the actual speed parameters of the new energy ship; Performing a critical deviation analysis based on the ship twin operation parameter set and constructing an error-parameter mapping rule table; Synchronize the actual speed parameter to the error-parameter mapping rule table for matching to obtain an error feedback value; The digital twin is calibrated online according to the error feedback value, the digital twin is updated and the simulation calculation is re-performed to build a data optimization closed loop and realize adaptive speed control of the new energy ship.

10. The adaptive speed control system for new energy ships based on digital twins is characterized by: The system is used to implement the adaptive speed control method for new energy ships based on digital twins according to any one of claims 1 to 9, and the system includes: A new energy power information acquisition module is used to retrieve the geometric parameters of the new energy ship, perform multi-physics field power analysis according to the geometric parameters, and obtain new energy power information; A digital twin construction module is used to introduce environmental perception parameters and combine the new energy power information to construct a digital twin of the new energy ship; A ship twin operation parameter set acquisition module is used to synchronize the real-time collected ship operation data set to the digital twin for simulation calculation to obtain the ship twin operation parameter set; The speed control strategy formulation module is used to constrain the ship twin operating parameter set according to the preset navigation target, formulate a speed control strategy, execute the speed control strategy to perform feedback optimization on the digital twin, and realize adaptive speed control of new energy ships.

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