2324 results about "Simulation software" patented technology

The invention provides a fan system multi-physics field coupling simulation and modeling method and device, and the method comprises the steps: building a coupling simulation frame of an electromagnetic field, a temperature field, a flow field and a structural mechanical field through multi-physics field collaborative modeling, employing a finite volume method FVM and multi-body dynamics MBS for collaborative solving, and precisely simulating the dynamic response of a fan under a complex working condition. And real-time simulation and verification: combining an S CADA system and a machine learning algorithm to realize online calibration and dynamic verification of a multi-physics field model, and supporting fan structure stability prediction under extreme conditions of typhoon, turbulence and the like. A multi-physics field coupling simulation software environment is developed, the functions of wake effect analysis, fan array layout optimization and the like are provided, the construction cost of an offshore wind field is reduced, and the power generation efficiency is improved.

The invention discloses a parameter feature-based test case generation method and a related product. In the scheme, a parameter document of target simulation software is obtained; and extracting parameter feature information of the target simulation software based on the parameter document. And on the basis of the parameter feature information, matching a test case template and a code generation rule in a pre-constructed code knowledge base, and generating an initial test case code. And dynamically optimizing the initial test case code according to feedback data generated in a simulation test process to generate a target test case code. According to the technical scheme, the parameter feature information is automatically extracted, the complex dependency relationship between the parameters is accurately analyzed, the test case is automatically generated based on the knowledge base matching template and rule, software changes are adapted in real time in combination with a dynamic optimization mechanism, dynamic and efficient generation of test case codes is achieved, and the test efficiency is improved. The coverage degree and the adaptability of the test case codes are improved, and then the accuracy, the comprehensiveness and the efficiency of the test are improved.

Disclosed is a method for fast automatic calibration of a phased array based on a residual neural network. A phase setting matrix is set and an amplitude and a phase of a array far-field complex signal are measured with a network analyzer to obtain an amplitude and phase vector of the array far-field complex signal. A real part, an imaginary part, and a magnitude of the far-field measured complex signal value are separated and normalized, and mapped to RGB three-channel image data. Datasets are automatically generated according to a preset amplitude-phase error range by a simulation software, the datasets are proportionally divided into a training set and a test set to be input into the residual neural network for training to obtain a calibration model. Measured data is input into the calibration model for automatic estimation of the amplitude-phase error of the phased array.

The invention provides an automatic inspection method and device and a readable storage medium, and relates to the technical field of operation and maintenance management, and the method comprises the steps: automatically logging in a plurality of devices through a pre-written automatic login script of terminal simulation software, and executing an inspection command; obtaining an original log output by the plurality of devices after executing the inspection command, and storing the original log in a local database; preprocessing the stored original log, and extracting a key index in the preprocessed original log by using a preset index extraction rule; and carrying out anomaly detection on the extracted key indexes to obtain the anomaly indexes and cross-device association anomaly results of the corresponding devices. According to the method, the device and the readable storage medium, the problems that the manual inspection efficiency is low, the log analysis intelligence degree is insufficient, intelligent assistance is lacked and potential safety hazards exist in data circulation due to the fact that an existing inspection technology mainly depends on manual operation or a basic script tool can be solved.

The invention provides an intelligent spraying composite robot system based on a large language model and a method thereof, and relates to the field of intelligent robots and automatic spraying, the intelligent spraying composite robot system comprises a chassis, a mechanical arm, a spraying gun, a camera, an instruction receiver and a controller; a mechanical arm and an instruction receiver are carried on the chassis; spray guns and cameras are mounted on the mechanical arms; the instruction receiver receives a natural language voice instruction, analyzes semantics through a large language model, and generates an action instruction; the controller comprises a motion control module, a three-dimensional point cloud data acquisition module, a feature point extraction module, a track planning module and a spraying operation module; the method improves the man-machine interaction, reduces the use threshold of the robot, is easy to operate, gives play to the spraying advantages of the composite robot, does not need to program in mainstream offline simulation software, can generate a spraying path with adjustable and controllable parameters only by collecting the point cloud template of the workpiece and selecting the feature points, and can be widely applied to furniture, furniture and the like. And spraying operation in the fields of automobiles, aerospace and the like.

The invention provides a high-voltage switch cabinet anti-condensation method based on simulation optimization and a storage medium. A three-dimensional physical structure model of the high-voltage switch cabinet is established in simulation software, material attributes and boundary conditions of all parts are set, steady-state or transient simulation calculation is carried out, and distribution of a temperature field, a humidity field and a flow velocity field in the cabinet is obtained. And on the basis of a simulation result, constructing a dew point distribution matrix, identifying condensation risk areas, and extracting geometric center, volume and temperature and humidity characteristics of each risk area. And the arrangement point and the power level of the heater are determined by calculating the heating power required by each condensation risk area, so that the anti-condensation design of the high-voltage switch cabinet is realized. According to the method, the condensation risk area in the cabinet can be accurately identified, the configuration of the heating power is optimized, and the balance and high efficiency of the anti-condensation effect are ensured. According to the invention, the precision and reliability of the anti-condensation design are improved, the problem of excessive heating or insufficient heating is avoided, and the safe and stable operation of the high-voltage switch cabinet in a complex environment is ensured.

The invention provides a mechanical correction optimization method and device for steel structure welding and electronic equipment, and relates to the technical field of steel structure welding.The mechanical correction optimization method for steel structure welding comprises the steps that a steel structure deformation model is obtained through preset simulation software according to obtained design data and welding parameters of a steel structure; based on the steel structure deformation model, a mechanical correction model of the steel structure is established according to the obtained mechanical correction process data; and the mechanical correction model is optimized through mechanical correction simulation, optimized mechanical correction process data are obtained, and the optimized mechanical correction process data are used for conducting mechanical correction on the welded steel structure. According to the method, the mechanical correction process data are optimized through modeling, then the correction process is controlled according to the optimized mechanical correction process data, welding residual stress and deformation are effectively reduced, the alignment precision and the overall performance of a welded joint are improved, and therefore the welding quality is improved.

The invention discloses a model construction method and system based on indoor decoration interactive design, and relates to the technical field of intelligent design, and the method comprises the steps: generating a diversified design sketch through an AI generation tool, collecting customer feedback data, determining customer demands, and generating a basic design scheme; creating an interactive ecology home 3D model by using a parameterized design tool, and adjusting a basic design scheme according to customer requirements; based on the adjusted basic design scheme, optimizing visual requirements of the basic design scheme through a V-Ray rendering engine; based on visual requirements, acoustic simulation software and a sensor are utilized to analyze spatial acoustic performance, ecological integration is completed, and intelligent control and AR interaction of an ecological environment are performed in combination with IoT and a user interface. According to the method, the interactive ecology home 3D model is combined with the AI generation tool, the parametric design, the V-Ray rendering engine, the biological feedback technology, the acoustic simulation software and the IoT and AR application, so that an efficient, flexible and personalized design process is realized.

The invention relates to the technical field of alloy pouring processes, in particular to a magnesium alloy heterogeneous flow overall coordination pouring process which comprises the steps of conducting pouring numerical simulation through simulation software, optimizing pouring design and determining a composite flow guide structure, a mold temperature control scheme and an alloy component regulation and control strategy. Magnesium alloy smelting and refining are conducted; preheating the mold by using an intelligent temperature control system; during the period, the intelligent temperature control system monitors and adjusts the temperature of the mold, and the online alloy adding system and the impurity adsorption filtering device keep the components of the melt uniform and pure; and after pouring is completed, controlling the mold temperature according to a preset cooling curve to slowly and uniformly solidify the melt. The design of the bionic branch-shaped flow dividing structure, the dynamic adjustable flow guide plate and the like reduces casting defects, and the casting forming quality is improved. And on-line alloy adding and impurity adsorption filtering ensure that melt components are stable, and the casting performance is improved.

The invention discloses an urban flood prediction method based on a Bayesian convolutional neural network, and the method comprises the steps: collecting historical rainfall events of a research region, simulating different rainfall events through hydrodynamic simulation software, and obtaining the maximum submerging water depth; selecting characteristic variables influencing waterlogging water depth, wherein the characteristic variables comprise 10 rainfall characteristic variables and 10 spatial characteristic variables; considering uncertainty to construct a Bayesian convolutional neural network prediction model; training the model based on a loss function MAE; and inputting the data in the verification set into the trained model, and calculating the mean value of the output approximate posteriori distribution as the predicted value of the water depth. The method is proposed on the basis of calculating and analyzing the relationship between the characteristic variables and the target variables, effectively fusing different data and considering possible uncertainty sources, not only realizes the prediction of the size and range of the submerged water depth of the research area, but also quantifies the prediction uncertainty, so that the prediction accuracy is improved. And support is provided for real-time flood disaster management.

The invention discloses a method for forecasting dynamic characteristic values of coarse particle solid-liquid two-phase flow in a vertical lifting pipeline, and belongs to the technical field of flow dynamic characteristic value forecasting. In order to solve the problem that the influence of particle motion on surrounding fluid is not considered in the theoretical calculation and numerical simulation of the solid-liquid two-phase flow in the pipe at present, the method comprises the following steps: firstly, carrying out modeling and grid division on a fluid domain; establishing a particle model based on particle material simulation software, and performing discrete control on particles; then based on computational fluid dynamics software, a coupling interface is established through a coupling interface control equation, the computational fluid dynamics software calculates and monitors the state of fluid, the state serves as an external environment of particles and is conveyed to particle material simulation software, and interference caused by movement of the particles is also transmitted to the computational fluid dynamics software through the coupling interface; and based on the initialized coupling interface, the pipeline model and the particle model, realizing coarse particle solid-liquid two-phase flow dynamic characteristic numerical prediction.

A rapid multiphysics inversion method and apparatus for a power device, a device and a storage medium, relating to the technical field of power device inversion. The method comprises: using simulation software to construct a multiphysics simulation model of a power device; constructing a data set on the basis of a predefined input parameter set and output parameter set; by means of using a preset data order reduction method, performing order reduction on the data set, so as to obtain an order-reduced data set and an order reduction matrix; by means of using a preset inversion method, fitting the relationship between the order-reduced data set and the input parameter set, so as to obtain an inversion coefficient matrix; and on the basis of the order reduction matrix, the inversion coefficient matrix and an input parameter set to be inverted, performing rapid inversion on the multiphysics simulation model, so as to obtain a multiphysics inversion result of the power device. The present invention can obviously reduce the amount of calculation while satisfying calculation precision, achieves high calculation efficiency, and can adapt to the requirements for online monitoring and real-time simulation of power devices.

The invention relates to the technical field of gangue filling, in particular to a coal mine gangue roadway type filling method which comprises the following steps: (1) screening gangue, and classifying the gangue into corresponding particle size groups according to particle sizes; (2) designing grading schemes according to the particle size groups divided in the step (1), performing simulation by using PFC2D numerical simulation software to obtain stress-strain curves of the grading schemes, and selecting the grading scheme with the maximum peak stress as the optimal grading scheme; and (3) filling the roadway type filling area according to the optimal grading scheme determined in the step (2). According to the method, the optimal grading scheme is determined by simulating the stress damage process of the internal structure of the original waste rock filling body under different particle size grading schemes through PFC2D, simulation verification shows that the stress concentration condition of the left side and the right side of the filled roadway is improved, the filling body filled in the roadway can replace roadway surrounding rock to bear part of pressure, and the working efficiency is improved. The problem that the crushing pressure is large when small-particle gangue is used in the prior art is solved.

The invention discloses an intelligent optimization method for a multi-type well seam joint control fine injection-production mode, and relates to the technical field of oil-gas field development. The method comprises the following steps: setting a well seam joint control fine injection-production mode, establishing an oil reservoir numerical simulation model in oil reservoir numerical simulation software, obtaining multiple groups of oil reservoir injection-production schemes based on a Latin hypercube sampling method, performing simulation according to each group of oil reservoir injection-production schemes by utilizing the oil reservoir numerical simulation model, generating multiple pieces of sample data, and establishing a sample database; a deep learning agent model is established, after the sample database is utilized to train and train the deep learning agent model, a particle swarm optimization algorithm is adopted to carry out single-target pre-search global optimization to obtain a preferred reference strategy, a reinforcement learning dynamic decision model is established, and a reinforcement learning agent is obtained through training based on a PPO near-end strategy optimization algorithm; and the optimal injection-production development scheme of the oil reservoir is obtained by utilizing the reinforcement learning agent, so that rapid optimization and decision support of the oil reservoir injection-production scheme in a new multi-type well seam joint control mode are realized.

The invention discloses a power generation efficiency optimization method for a floating photovoltaic power generation system. The method comprises the following steps: analyzing the motion response of a floating body in a marine environment, and determining the boundary condition of the floating body swinging under the action of waves; based on hydrodynamic analysis software AQWA, a hydrodynamic analysis model of the floating body is built, and the pitching angle of the floating body is verified; in combination with an inclined surface irradiance calculation model, an improved particle swarm algorithm is adopted for optimization, and the initial inclination angle of the photovoltaic panel when the photovoltaic panel receives solar radiation energy to the maximum extent is solved; in combination with different wave conditions of a certain sea area, simulation software is used for performing dynamic simulation on the floating body and the assembly, the influence of different environmental conditions on the power generation efficiency is analyzed, and the effectiveness of the scheme is verified. According to the method, the optimal initial angle is determined by optimizing the initial mounting inclination angle of the assembly, fully considering the movement condition of the floating body under the action of waves and combining the influence of different wave conditions, the radiation quantity received by the assembly is maximized, and the defects in the aspects of laying design, dynamic adaptability and power generation efficiency in the prior art are overcome.

Disclosed in the present invention are an intelligent liquid cooling plate optimization method and apparatus based on CFD numerical simulation. The method comprises: first, establishing a 3D battery pack model on the basis of liquid cooling plate design parameters and other component design parameters; then, on the basis of the 3D battery pack model, performing thermal simulation modeling and thermal simulation calculation on a battery pack; on the basis of a thermal simulation result, using a particle swarm multi-objective optimization algorithm to optimally calculate locally optimal solutions of the liquid cooling plate design parameters, and determining whether the locally optimal solutions converge; and using a loop iteration mode to calculate the locally optimal solutions of the liquid cooling plate design parameters until the locally optimal solutions converge, and then obtaining globally optimal solutions. Three-dimensional CAD software, CFD simulation software and an optimization interface are interconnected to each other, so that the operation of the whole process of design, simulation and optimization of a liquid cooling plate can be completely and intelligently realized simply by means of inputting key design parameters of the liquid cooling plate in an initial design stage; and an optimal design scheme is obtained by means of implanting the particle swarm multi-objective optimization algorithm. The present invention achieves a high speed and high efficiency.

The invention relates to a vehicle dynamic adjustment method for a side collision accident, and the method comprises the following steps: S1, collecting vehicle body multi-dimensional information data information, vehicle environment information data information and vehicle passenger information data information, and building a real-time updated data model through data fusion; training a neural network according to virtual collision data generated by the vehicle collision simulation software to obtain a collision risk prediction model; s2, inputting data in the model into a collision risk prediction model to obtain the injury degree of a passenger and collision prediction position point information, dividing the state between a vehicle and a potential collision object into different risk levels, and generating a risk map; and S3, the vehicle adjusting system adjusts the height, the speed and the seat posture of a vehicle suspension system and a vehicle safety belt according to the different risk levels, risk prompting is carried out on vehicle passengers so as to reduce the risk levels, and the risk map is updated in real time. According to the invention, the safety of passengers in a side collision accident can be improved.

The invention provides a power system voltage control method and device based on dynamic steady state collaborative correction, and the method comprises the steps: building an electromagnetic transient model for a preset voltage node in electromagnetic transient simulation software PSCAD, simplifying a power grid with the electrical distance to a target region exceeding a preset distance into a dynamic Thevenin equivalent model, initializing load flow calculation in the BPA to obtain a dynamic-steady state hybrid model; updating dynamic Thevenin equivalent parameters of the power system in real time according to the data of the phasor measurement unit of the power system, and synchronizing the dynamic Thevenin equivalent parameters to the BPA; based on the dynamic-steady state hybrid model, the transient overvoltage of the power system is suppressed within the time shorter than the first preset duration, and the steady state voltage of the power system is optimized within the time shorter than the second preset duration in combination with wide-area coordination control, so that the parameter bidirectional correction of the dynamic and steady state models is realized, and the head end voltage prediction error is reduced. And the voltage control robustness is improved.

The invention is suitable for the technical field of vehicles, and provides an automobile bumper parameter determination method and system, and the method comprises the following steps: constructing an automobile bumper with different curvature radiuses and a three-dimensional simulation model of a whole automobile, and dividing the three-dimensional simulation model into a plurality of units through employing a finite element analysis method, so as to simulate the stress distribution and deformation in a collision process; configuring collision parameters, wherein the collision parameters comprise a collision speed, a collision angle and a collision object; simulation software is operated, the conditions of bumpers with different curvature radiuses in the collision process are simulated, a collision simulation result is recorded, and the collision simulation result comprises the deformation condition and energy absorption information of the bumpers; preliminarily determining the curvature radius range of the automobile bumper based on the collision simulation result; and the measurement precision and the measurement stability of the radar in the automobile bumper within the curvature radius range are determined, and the optimal curvature radius range is determined. According to the invention, while the collision performance of the bumper is ensured, the normal work of the radar sensor is also ensured.

The invention provides an optimal design method of an ultralow-temperature multi-load heat insulation support, a support assembly and an experimental research method, and relates to the field of large superfluid helium low-temperature distribution systems. Comprising the following steps: selecting thickness parameters of a casing pipe in each stage of temperature zone of a supporting assembly and a supporting panel as optimization design parameters to carry out parametric modeling, and introducing a stress maximum value and a heat leakage value as target values; and based on the thickness parameters of the cold shield sleeve and the supporting panel of each stage of temperature zone, taking a genetic algorithm as an optimization function, performing iterative calculation in combination with simulation software, obtaining the thickness parameters of the cold shield sleeve and the supporting panel under the optimal boundary, determining the heat leakage value and the maximum stress value of the supporting assembly according to the optimal boundary, and then processing the supporting assembly. By combining various simulation technical means and experimental research, the problems of poor performance of the support assembly, lack of process verification and the like caused by the adoption of a classic model are solved, and the rigidity and robustness of the large-scale superfluid helium transmission and distribution system are effectively optimized and improved.

The present invention provides a solution of a human-computer interaction method and system based on three-dimensional coordinate measurement, and a plurality of solutions for applying same to solve technical problems. An operation body and / or an operator performs input and operation interaction by means of a virtual keyboard and a virtual mouse, or integrates a display picture space and carries out various participatory and interactive direct operations and experiences on object components and objects in virtual and real scenes. Virtual handwriting input, body movement posture recognition, and lip recognition interaction methods are further provided, and virtual mode control and interaction methods such as gesture recognition and virtual touch screen interaction are supported. Contact is not needed and there is no need to touch the screen, and mobility is achieved. The present invention is suitable for the two-dimensional conventional computing field, and particularly suitable for three-dimensional space computing fields (comprising VR, MR, AR, meta-universe, virtual simulation, software games, three-dimensional graphics, three-dimensional animation, and other three-dimensional scenes). Human-computer interaction operations in work and life of people can be greatly facilitated and optimized.

The invention belongs to the technical field of simulation analysis, and particularly relates to a medium-high voltage switch cabinet internal humidity inversion calculation method based on simulation analysis, which comprises the following steps: establishing a geometric model of a switch cabinet, importing the geometric model into finite element simulation software to obtain a simulation analysis model, adding each physical field and computational domain and boundary conditions thereof, and calculating the internal humidity of a medium-high voltage switch cabinet. All the physical fields are coupled, and mesh generation is carried out; performing numerical solution on the simulation analysis model by using a transient solver to obtain a temperature and humidity distribution condition in the switch cabinet; the simulation analysis model is optimized, a simulation data set is constructed, and a PINN is trained; based on the environment temperature and humidity and the operation current collected in the actual operation of the switch cabinet, the trained PINN is used for prediction, and the steady-state relative humidity of the current transformer is obtained. According to the invention, based on the limited boundary monitoring data, efficient and accurate reconstruction of the humidity field of the key area in the switch cabinet is realized, and a feasible path is provided for equipment state sensing and condensation risk early warning.

The invention provides a distribution network lightning arrester transient temperature distribution improvement method based on insertion of an aluminum gasket, and belongs to the technical field of electrical equipment, and the method comprises the steps: constructing a lightning arrester three-dimensional model in simulation software; constructing the lightning arrester conductivity of the coupling temperature; constructing a lightning stroke simulation model of the lightning arrester; lightning stroke transient temperature distribution of the lightning arrester is obtained, and a lightning stroke comparison result before and after addition of the aluminum gasket is obtained; constructing an aluminum gasket thickness-position set; and obtaining the position-thickness optimization relation of the aluminum gasket, constructing a genetic algorithm model according to the aluminum gasket thickness-position set, and obtaining the optimal aluminum gasket thickness based on the position. The method has the advantages that the temperature change of the ZnO valve plate of the lightning arrester under the lightning impulse is obtained, and the transient temperature distribution of the lightning arrester during the lightning impulse is obtained by using the temperature distribution coefficient; comparing the transient temperature distribution of the lightning arrester before and after adding the aluminum gasket to confirm that the temperature distribution of the lightning arrester can be optimized by adding the aluminum gasket; therefore, the method for introducing the aluminum gasket between the lightning arrester valve plates is provided.

Embodiments of the present application relate to the technical field of computers, and provide a verification method and apparatus, an electronic device, and a readable storage medium. The method comprises: downloading software design into a processing system of a programmable logic chip, and burning hardware design corresponding to the software design into a programmable logic area of the programmable logic chip; synchronously operating the hardware design and the software design in the programmable logic chip, and monitoring first operation data of the hardware design and second operation data of the software design; when the first operation data and the second operation data are not matched, taking a hardware snapshot of the programmable logic chip to store state information of the programmable logic chip; and importing the state information into simulation software for simulation, so as to debug the hardware design.

The invention discloses an air suspension and ESC coordination control method and system based on deep learning, and belongs to the field of automobile braking, and the method comprises the following steps: S1, collecting historical data of vehicle driving, generating extreme working condition data by using vehicle dynamics simulation software, and forming a training data set; s2, constructing a double-branch fusion control model, and training the double-branch fusion control model; s3, vehicle state parameters and road surface condition data are collected in real time; s4, after feature extraction and fusion are carried out on the processed multi-source parameters, the trained double-branch fusion control model is input, and an optimal control strategy is generated; and S5, the ESC executes the optimal control strategy and collects vehicle state data after execution to form a control closed loop. By the adoption of the air suspension and ESC coordinated control method and system based on deep learning, the deep learning and the vehicle dynamics model are combined, the vehicle motion state can be monitored in real time, accurate control is conducted according to real-time data, and the potential out-of-control situation is avoided.

The invention discloses a reciprocity theorem-based array antenna multi-beam pattern synthesis method, which comprises the following steps of: establishing an array antenna model in electromagnetic simulation software, and extracting a radiation pattern of each antenna unit; defining the number and direction of to-be-formed beams and the gain ratio between the beams; establishing an array antenna energy transmission efficiency transfer function, calculating scattering parameters of each antenna unit of the array antenna through a reciprocal theorem and coordinate transformation, and constructing a scattering parameter matrix of a multi-antenna system; automatically adjusting parameters by using a particle swarm algorithm, and dynamically regulating and controlling the gain proportion between the beams; the optimal excitation value of each antenna unit is obtained, and a target beam is generated after actual loading. According to the invention, the multi-beam synthesis result of the array antenna is more convenient, more stable and more flexible.

The invention relates to the technical field of port operation simulation software systems, and particularly discloses a quay crane operation process simulation system and method for port intelligent driving. The quay crane operation process simulation system comprises a data interaction module, a quay crane motion simulation module, a service simulation module, a simulation control module, an operation backtracking module, an analysis and optimization module and a simulation display module. The method has the beneficial effects that a complex port operation process is completely mapped to a digital space through fine dynamic modeling and coding, a port manager can visually observe and analyze the whole operation process in a virtual environment through full-process digitization, and potential problems can be found and solved in time; based on the constructed 3D simulation environment, natural environment data and random events are combined to carry out work process simulation, meanwhile, simulation data are fed back to a simulation system to carry out closed-loop control, simulation errors are reduced, and the work process simulation authenticity is improved.

The invention relates to a heavy-duty commercial vehicle train hybrid energy management equivalent factor adaptive method, which comprises the steps of classifying operation conditions based on cloud historical data of the operation conditions, and calculating an optimal equivalent factor under each operation condition in an off-line manner by utilizing simulation software after classification is completed; selecting a working condition updating period taking mileage as a reference, identifying the working condition according to the characteristic parameters in the period, and obtaining a corresponding optimal equivalent factor as a reference equivalent factor of the next control period; the equivalent factors are adjusted in real time based on the whole vehicle state parameters; adjusting equivalent factors considering terrain prediction according to the difference between the allowable maximum SOC before downhill and the current SOC in combination with front terrain prediction; corresponding control instructions are sent to the motor and the engine; periodically updating the reference equivalent factor to realize continuous loop iteration of the optimal equivalent factor; and the fuel economy of the whole vehicle is improved.

In order to solve the problems of high energy consumption and unbalanced comfort of a traditional static control strategy of the air conditioning system during environment change, a building three-dimensional model is constructed, and sensor data and energy consumption simulation software are fused to construct a joint simulation environment. The improved extreme learning machine neural network is used for predicting the air conditioner energy consumption and the personnel thermal comfort degree, the network structure and parameters are optimized through the rotary particle swarm optimization, and the prediction precision and generalization ability are improved. And then, in combination with a Newton-Raphson multi-objective optimization algorithm, solving an air conditioner temperature set value optimal dynamic sequence in a rolling manner, and balancing energy consumption and comfort through a Pareto frontier solution set. Through dynamic simulation and data driving optimization, precise regulation and control of the air conditioner are achieved, and the thermal comfort degree is improved.

The invention provides a visual underwater sensor network simulation method, and relates to the technical field of underwater sensor networks, and the method comprises the steps: configuring network simulation parameters which comprise topological structure parameters, channel parameters and simulation parameters; inputting the channel parameters into an underwater acoustic calculation tool to generate an underwater acoustic multipath channel for simulation; the bit error rate BER of the multi-carrier MFSK underwater acoustic communication algorithm under the underwater acoustic multipath channel condition is calculated, and the bit error rate BER is input into the OTcl script; performing network simulation on the configured OTcl script by using an underwater network simulator; and displaying a network simulation result through a visual interface. The underwater sensor network simulation result can be displayed through the visual interface, the defect that current NS2-based underwater sensor network simulation software does not have a visual interface is overcome, a good man-machine interaction interface can be provided for a user, the development efficiency is improved, and the user is helped to better evaluate the performance of the underwater sensor network.