71 results about "Thermal optimization" patented technology

The invention provides an intelligent adjustment method for distributed air treatment equipment, and belongs to the technical field of air treatment equipment, and the method comprises the steps: inputting a personnel distribution image into an airflow field reconstruction model based on a graph neural network, outputting three-dimensional space flow field distribution data, calculating a personnel intensity index, and predicting an average thermal sensation index value; an air supply adjustment double-layer game model is established based on the data, the air supply angle and the air supply speed of an electric side supply nozzle and the air supply quantity of a lower air supply outlet are solved, an actuator is controlled to adjust air supply parameters, and the target air outlet temperature and the refrigerant flow of the heat exchanger are calculated through a thermodynamic entropy production minimization heat exchange optimization algorithm; and feedback correction is performed according to the actually predicted average thermal sensation index deviation to form closed-loop control, so that the technical problem that the distributed air treatment equipment is difficult to adjust the air supply parameters in real time according to the personnel distribution dynamic change so as to ensure the thermal comfort and the energy efficiency at the same time is solved.

The invention relates to the technical field of motors, and discloses a high-temperature-resistant direct-current coreless gear motor and a test system, and the system comprises a temperature monitoring module, a current regulation and control module, a heat dissipation optimization module, a load response module, a cloud analysis module and a virtual verification module. By arranging the temperature monitoring module, multi-dimensional temperature data during operation of the motor can be acquired in real time, and a temperature distribution diagram can be generated, so that the system can comprehensively sense the internal thermal state of the motor and accurately identify local overheating risk points, thereby improving the operation reliability and safety of the motor under a high-temperature working condition; through cooperative operation and closed-loop control of the current regulation and control module, the heat dissipation optimization module and the load response module, according to real-time temperature and load changes, driving current parameters and heat dissipation resource distribution can be dynamically adjusted, and the heat dissipation efficiency is improved. And the output performance and the torque stability of the motor under high-temperature and high-load conditions are ensured.

Aspects of the present disclosure generally relate to systems and methods for flight control of aircrafts driven by electric propulsion systems and in other types of vehicles. In some embodiments, a system of an aircraft is disclosed, configured to determine one or more desired commands for the aircraft, retrieve engine information for at least one electric propulsion unit (EPU) of a plurality of EPUs of the aircraft, wherein the engine information includes at least one time-based metric for temperature associated with the at least one EPU, generates control commands based on the received engine information, and controls effectors according to the generated control commands to meet the desired commands of the aircraft.

The invention belongs to the technical field of overall aerodynamic design of helicopters, and particularly relates to an infrared suppressor fairing of a helicopter and an air heat optimization design method of the infrared suppressor fairing. The fairing comprises a fairing body, a shutter air inlet, a square protective net air inlet, a second-stage exhaust pipe and a first-stage mixed exhaust pipe. The front of the fairing body is regarded as a half ellipse which is laterally cut along a long axis; a shutter air inlet is formed in the front portion of the fairing body, and the plane of a shutter is crescent A square protective net air inlet is formed in front of the top of the fairing body; an oval second-stage exhaust pipe is arranged behind the top of the fairing body so that high-temperature exhaust can be further cooled by means of downwash airflow of the rotor wings. A first-stage mixed exhaust pipe is sleeved in the second-stage exhaust pipe; and the primary mixing exhaust pipe is connected with an outlet of the transmitter. According to the method, the problem that the pneumatic performance and the thermal performance are difficult to consider in a traditional design method is solved, comprehensive optimization of the pneumatic performance and the thermal performance of the fairing is achieved, and a pneumatic design scheme of the infrared suppressor fairing is formed.

Optimal control of multiple heating, ventilation, and air-conditioning units in an open-plan space demands fast and accurate thermodynamic modeling. Prior methods lack scalability required for effective control in large open-plan offices primarily due to air-mixing interactions. The present disclosure describes a physics-informed graph neural network (PI-GNN) to overcome these challenges. Specifically, thermodynamic interactions are modeled as edges between nodes that represent cells. Further, a modeling approach is used that allows explicit modeling of wall and window surface temperatures which are commonly ignored. The method of present disclosure utilizes PI-GNN as a state-estimator that employs a receding-horizon approach for optimal HVAC control. PI-GNNs are adapted for building HVAC control by incorporating a time-resetting strategy to handle time-dependent ambient conditions and therefore set-points. The method of the present disclosure outperforms a regular PINN model and other baseline control strategies on thermal model accuracy, computation time, energy consumption, and user comfort.

The invention relates to a heat dissipation analysis and optimization method for an IGBT module, and the method comprises the steps: obtaining the electrical parameters and working conditions of the IGBT module, and calculating the total power loss during the operation of the IGBT module based on the electrical parameters and working conditions. Based on the total power loss and the physical structure of the IGBT module, a thermal resistance network model of a semiconductor junction region and a cooling environment and a Cauer type thermal impedance model based on dynamic characteristics are established. Inputting the total power loss into the thermal resistance network model and the Cauer type thermal impedance model, calling a finite element simulation algorithm to solve a temperature distribution field of the IGBT chip, and determining the total equivalent thermal resistance. And when the junction temperature or the total equivalent thermal resistance of the IGBT chip does not meet the set index, positioning the heat dissipation bottleneck and generating a heat dissipation optimization strategy. And executing a heat dissipation optimization strategy, and updating the thermal resistance network model and the Cauer type thermal impedance model after executing the heat dissipation optimization strategy so as to update the temperature distribution field and the total equivalent thermal resistance.

The invention discloses a heat supply unit deep peak regulation and heat supply optimization operation method based on multi-mode collaboration, and particularly relates to the technical field of thermal power generation and heat supply, and the method comprises the steps of S1, system modeling and parameter identification, S2, thermoelectric load prediction, S3, multi-objective optimization solution, S4, operation decision and feedback, and S5, data agent mapping acceleration. According to the method, the thermoelectric load is accurately predicted through mechanism and data dual-drive modeling, and based on the target of maximizing the economic benefits of the whole plant, the optimal cooperation scheme of multiple operation modes such as heat supply, power supply and deep peak regulation is dynamically solved by utilizing the multi-target optimization algorithm on the premise of ensuring the safety of the unit, so that the power supply efficiency is improved. Finally, production is guided through an online decision-making and closed-loop feedback system, and safe, economical and flexible operation of the unit under the working condition of deep peak regulation is achieved.

The invention provides a centralized heating optimal scheduling method and system based on multi-heat-source dynamic matching, and the method comprises the steps: constructing a thermal load prediction model, and fusing various types of data to generate a thermal load demand dynamic curve in the next 24 hours; establishing a dynamic priority ranking model, and generating a heat source priority sequence; generating a multi-heat-source cooperative operation strategy; constructing a multi-heat-source dynamic matching optimization model to obtain an optimal scheduling strategy; heat sources are adjusted in real time through the central control system, and dynamic correction is conducted by combining pipe network feedback data; and periodically updating the thermal load prediction and dynamic priority ranking model. According to the method, a bidirectional LSTM neural network is fused with data to construct a high-precision thermal load prediction model, and a curve is generated in combination with a feature pyramid network; meanwhile, related data are periodically combined, the weight of the LSTM neural network is updated through an incremental learning algorithm, the weight of the priority ranking model is adjusted through a gradient descent method, the adaptability of the prediction model is continuously optimized, and the prediction precision is improved.

The invention relates to the technical field of heat dissipation of electronic equipment, in particular to a chip heat dissipation optimization system based on a multi-layer stacking structure. A heat conduction module; a heat dissipation module; a heat recovery module; the temperature monitoring and control module monitors the temperature of each layer of chip and the temperature difference of an inlet and an outlet of cooling liquid in real time, judges the working state of the whole system and controls the whole system; by arranging the heat conduction and heat dissipation modules, adopting heat conduction pores in gradient distribution and a mixed phase change material, and combining a nano-porous graphene substrate, cooperation of hot spot rapid heat conduction and non-hot spot buffer energy storage is achieved, the defect that a traditional phase change material is single is overcome, the dual-mode cooling pore channel design is achieved, seamless switching between a conventional system and an emergency system is achieved, and the energy storage efficiency is improved. The heat dissipation capacity is greatly improved, 0.1 mm resolution ratio temperature field reconstruction is achieved through the temperature monitoring and control module, hot spots are predicted 300 ms ahead of time, and temperature control is more accurate.

A semiconductor device is made by calculating a thermal resistance matrix for the semiconductor device. A plurality of maximum junction temperatures for the plurality of die of the semiconductor device is selected. A plurality of power envelope surfaces are calculated for the semiconductor device based on the thermal resistance matrix and the maximum junction temperatures. A plurality of powers is selected for the plurality of die. The plurality of powers are compared against the plurality of power envelope surfaces to determine a plurality of risk values.

The invention belongs to the field of numerical control machine tool temperature monitoring, and provides a method for monitoring a machine tool lead screw temperature field in real time by using numerical control motion data, which comprises the following steps: when a machine tool feed shaft structure is blocked, in the irregular rotation motion process of a lead screw, under the condition that the lead screw temperature data cannot be directly measured by a measuring instrument, determining the temperature field of the lead screw; and real-time monitoring of the temperature field of the lead screw is realized. Firstly, the feeding speed, the mechanical coordinates and the feeding load of a machine tool are collected from a numerical control system, then the friction heat and the temperature of a ball bearing pair are deduced, then the friction heat of a rolling bearing and a ball screw pair is calculated, and finally the temperature field of a ball screw is calculated. According to the invention, the temperature field of the ball screw in a complex motion state is calculated in real time by fully utilizing data which is easy to measure and can be collected in the motion process of the ball screw and combining a heat source heat generation mechanism and a structure heat transfer mechanism, so that online monitoring of the temperature field of the ball screw is realized. Technical support can be provided for machine tool thermal optimization design, thermal error compensation, machine tool digital twinborn body construction and the like.

The invention discloses a supercritical gas-fired boiler based on tower type arrangement and a thermal optimization control method, and relates to the field of supercritical gas-fired boilers, the supercritical gas-fired boiler comprises a hearth, a burner, a water cooling wall, a heating surface in the boiler, a header outside the boiler, an economizer and a tubular air preheater. The periphery of the hearth is wrapped by an ash bucket water-cooled wall, a spiral tube coil water-cooled wall and a vertical tube coil water-cooled wall, in-furnace heating surfaces are sequentially arranged in the smoke flowing direction and are suspended through in-furnace suspension tubes, and an out-furnace collecting box is suspended through out-furnace suspension tubes; the economizer is divided into an upper stage and a lower stage, is arranged by adopting sequential tube bundles and is provided with a bypass, and a denitration reactor is arranged between the upper stage and the lower stage; the suspension pipe is made of high-strength alloy steel, a working medium flows in the suspension pipe, and a heating surface and related parts are made of alloy materials with adaptive performance. The invention has the technical effects of high safety of the wall temperature of the heated surface, small deviation, small occupied area, low smoke, wind, steam and water resistance, smooth expansion system, adaption to the rapid variable load requirement, excellent environmental protection property, reliable operation and the like.

The invention relates to the technical field of server heat dissipation optimization control, and discloses a server heat dissipation optimization control method and system based on environmental parameters, and the method comprises the steps: obtaining a heat distribution data set, screening out an abnormal region set, selecting temperature change information and temperature values as region temperature features, and carrying out the K-means clustering to obtain a second region set, screening high-risk areas with the ventilation flow speed lower than a threshold value and the humidity higher than the threshold value, determining a heat transfer path in combination with a real-time airflow direction, screening out a high-risk path, constructing an evaluation system to calculate an overheat risk evaluation value, and if the overheat risk evaluation value exceeds the pre-estimated threshold value, selecting an adjustment operation from a preset control strategy library as a preliminary scheme; and adjusting the scheme according to the applicability of the scheme. And extracting an instruction issuing device from the adjustment scheme, performing parameter deviation correction according to execution, and determining a final scheme if an execution effect meets a preset heat dissipation target. The method solves the defect that in the prior art, spatial relevance and dynamic heat conduction cannot be fused to form a precise heat dissipation strategy.

This invention discloses a method and device for optimizing and controlling the hydrothermal environment of green roofs based on modified matrix synergy, belonging to the field of green building technology. The method involves acquiring meteorological parameters and roof structure requirements of the target area to determine the hydrothermal control objectives, and customizing a modified matrix formula composed of garden soil, gravel, and wood chip biochar, pretreated for porosity optimization. A layered structure is constructed, and sensors collect data such as matrix moisture content, roof temperature, and rainfall intensity in real time. Based on a coupling algorithm, the porosity and height of the water storage and drainage layer are dynamically adjusted to achieve hydrothermal control through the synergistic effect of the modified matrix's water retention and thermal insulation properties and vegetation evapotranspiration. The control effect is periodically evaluated, and the matrix ratio and water storage and drainage layer parameters are iteratively updated. The device employs an intelligent modular adjustable ventilated water storage and drainage layer, with built-in sensors and a drive motor, and a distributed data acquisition and control module to achieve intelligent control. This invention solves the problems of poor adaptability and weak hydrothermal control capabilities of traditional green roofs.

The present application relates to the technical field of sports building light heat optimization, and more particularly to a method for balancing and optimizing the light heat environment of a retractable roof sports building based on a generative adversarial network and a genetic algorithm. The method comprises the following steps: obtaining retractable roof shape data; parameterizing the retractable roof shape data to generate a two-dimensional grayscale image of the retractable roof; performing fluid dynamics and light heat environment numerical simulation on the retractable roof shape data to obtain environment simulation data of the retractable roof; pairing the two-dimensional grayscale image of the retractable roof with the environment simulation data of the lower space of the retractable roof to obtain an input-output image pair; and using the generative adversarial network to predict the wind speed distribution of the input-output image pair to generate a wind speed distribution prediction value of the retractable roof. The present application realizes intelligent optimization of the light heat balance of a retractable roof sports building by combining a generative adversarial network and a genetic algorithm, and solves the deficiencies of traditional methods in flexibility, optimization accuracy and computational efficiency.

The invention discloses a three-dimensional chip thermal perception optimization method based on tensor data flow, and relates to the field of integrated circuits, and the method comprises the steps: firstly, starting from the angle of tensor data flow, providing a collaborative thermal optimization process combining a network, an architecture, physics and packaging; then, based on a quantitative modeling tensor data flow energy optimization method, automatically identifying the most energy-saving tensor data flow under given three-dimensional chip constraints by using a heuristic optimization method; and finally, providing a thermal sensing three-dimensional architecture spatial layout method, simplifying the spatial layout problem of the SRAM macro block into an affine mapping optimization problem, and optimizing an affine mapping relationship through a heuristic optimization method to obtain the spatial layout with optimal thermal performance. According to the method, the tensor calculation characteristics are optimized in a targeted manner, so that the three-dimensional stacked SRAM chip meets the thermal reliability requirement in a high-density integration scene.

The invention provides a distributed heat supply optimization system and method based on the Internet of Things, and belongs to the technical field of heat supply optimization. The system is characterized in that a data acquisition module acquires multi-modal data by using a synchronous acquisition technology and a dynamic acquisition strategy; the feature extraction module performs multi-dimensional feature extraction and constructs a voiceprint feature library capable of being dynamically updated; the acoustic diagnosis module is used for identifying fault types and positioning fault points; the model construction module is used for constructing a thermal inertia digital twinborn model to obtain a thermal dynamic prediction result; the sequence generation module is used for establishing a multi-objective optimization model and generating a self-adaptive pulse control sequence; and the execution and optimization module implements a self-adaptive pulse control sequence through an intelligent actuator, so that autonomous and iterative evolution of the distributed heat supply optimization system is realized. According to the system, heat supply does not meet the requirement in advance, the energy efficiency and the comfort degree are improved, fault diagnosis is intelligent and early, the maintenance efficiency is greatly improved, the system efficiency is maximized, and the system is autonomous and personalized.

The application relates to an intelligent composite energy storage heating system and belongs to the technical field of energy storage heating. The system outputs a high-precision heat supply and demand prediction result through an energy supply and demand prediction module; a storage regulation and decision module generates a comprehensive judgment through a storage state-health degree two-dimensional collaborative evaluation mechanism, and outputs a storage medium dynamic regulation and control strategy, a phase change heat storage component control scheme and a corrected energy start-stop threshold value relying on a hierarchical coupling regulation and control mechanism; a heat exchange optimization module constructs a multi-objective collaborative regulation and control mechanism, dynamically adjusts the contact matching mode, the flow channel adaptation form and the heat medium conveying rhythm of the heat medium and crude oil, and generates optimal heat exchange output; and an energy regulation and control module suppresses energy fluctuation based on a fluctuation grading buffer mechanism, triggers an emergency regulation and control scheme, and simultaneously corrects a subsequent prediction trend judgment benchmark. Through collaborative application of multiple mechanisms, the application effectively guarantees stable operation of the system under working condition fluctuation and mutation scenes, and is suitable for crude oil heating and other energy storage heating scenes.

The invention belongs to the technical field of aero-engine cooling design and flow heat exchange optimization, and provides a turbine blade cooling turbulence rib construction method, system and configuration based on level set topological optimization and a blade. The method comprises the steps that a fluid-solid coupling calculation model containing a cooling channel fluid domain and a blade wall surface solid domain is constructed, defining a level set function to implicitly represent the two-phase region; establishing a unified control equation set covering a full computational domain based on the function, and introducing a flow velocity suppression mechanism into a solid domain to carry out single-domain coupling solution of fluid flow and solid heat conduction; according to the physical field solution, constructing an optimization model taking the cooling performance as a target function and the volume fraction of the turbulent flow rib as a constraint, and calculating the sensitivity of the target function to a level set function; using the sensitivity to drive a level set function update to evolve a spoiler rib boundary; iterating until convergence and outputting the final geometric configuration of the turbulent flow rib. According to the invention, the irregular turbulent flow structure with high heat exchange efficiency and low flow resistance can be automatically generated without presetting a rib type.

The invention relates to the technical field of sports building photo-thermal optimization, in particular to a retractable roof sports building photo-thermal environment balance optimization method based on a generative adversarial network and a genetic algorithm. The method comprises the following steps: obtaining form data of the retractable roof; performing parametric modeling on the form data of the retractable roof to generate a two-dimensional grayscale image of the retractable roof; performing fluid dynamics and photo-thermal environment numerical simulation on the form data of the retractable roof to obtain environment simulation data of the retractable roof; carrying out image pairing on the two-dimensional grayscale image of the retractable roof and the simulation data of the lower space environment of the retractable roof to obtain an input-output image pair; and performing wind speed distribution prediction on the input-output image pair by using a generative adversarial network, and generating a wind speed distribution prediction value of the retractable roof. According to the method, the generative adversarial network and the genetic algorithm are combined, intelligent optimization of photo-thermal balance of the retractable roof sports building is achieved, and the defects of flexibility, optimization precision and calculation efficiency of a traditional method are overcome.

This invention relates to an intelligent microchannel heat exchanger and its control method, belonging to the field of heat exchanger technology. It includes a sensor system, a control system, a drive mechanism, adjustable ribs, and heat pipes. The sensor system monitors the temperature and flow rate parameters of the fluid in real time and collects surface temperature data of the heat pipes. The control system receives input signals from the sensor system based on a microprocessor, performs real-time analysis and decision-making through a built-in heat exchange optimization algorithm, and sends corresponding control commands to the drive mechanism. The drive mechanism is linked with multiple adjustable ribs, and by driving their rotation, dynamically adjusts the geometry of the corresponding flow channels, thereby achieving active control of the fluid distribution. The heat pipes directly contact the object to be cooled to maximize the heat transfer area. By adjusting the angle of the ribs, the cross-sectional shape and flow path structure of the microchannels can be changed to adapt to the heat exchange requirements under different operating conditions, achieving efficient and adaptive heat dissipation performance.

The application relates to a lithium ion battery low-temperature preheating charging segmentation optimization method and system based on reinforcement learning, which comprises the following steps: establishing a thermal-electric coupling model of a battery, and establishing state transition expressions of voltage, temperature and SOC; when the battery temperature is lower than a preset switching temperature, starting a high-frequency pulse preheating optimization process based on reinforcement learning; when the battery temperature reaches the preset switching temperature, entering a heating charging process based on reinforcement learning, and adaptively switching among three modes of heating, charging and simultaneous heating and charging, so as to realize safe and rapid charging at low temperature. Through deep reinforcement learning technology, the preheating and charging stages are segmented and optimized, the parameters in the preheating and charging process are accurately controlled, rapid preheating and efficient charging are realized, battery damage is reduced, and the service life of the battery is significantly prolonged.

This invention belongs to the field of aero-engine cooling design and flow heat transfer optimization technology. It provides a method, system, configuration, and blade for constructing turbine blade cooling fringe based on level set topology optimization. The method includes: constructing a fluid-structure interaction (FSI) computational model encompassing the fluid domain of the cooling channel and the solid domain of the blade wall; defining a level set function to implicitly represent the two-phase region; establishing a unified set of governing equations covering the entire computational domain based on this function; introducing a velocity suppression mechanism in the solid domain to perform single-domain coupling solution of fluid flow and solid heat conduction; constructing an optimization model based on the physical field solution, with cooling performance as the objective function and fringe volume fraction as the constraint; calculating the sensitivity of the objective function to the level set function; using this sensitivity to drive the level set function update to evolve the fringe boundary; iterating until convergence to output the final fringe geometry. This invention does not require pre-setting the fringe type and can automatically generate irregular fringe structures with high heat transfer efficiency and low flow resistance.

The application discloses a tunnel fire-fighting water-electric heat tracing heating optimization method, system, device and medium, and relates to the technical field of tunnel fire-fighting. The method comprises the following steps: acquiring associated data of tunnel fire-fighting; the associated data comprises water use time, a physical network, an environmental temperature and a pipe-in-water temperature; a time-environmental temperature-pipe-in-water temperature network model is constructed according to the associated data; the nodes in the time-environmental temperature-pipe-in-water temperature network model are determined by discretizing the water use time; a target function is constructed based on the time-environmental temperature-pipe-in-water temperature network model; an electric heat tracing heating optimization model is constructed according to the target function and conditional constraints, and the heating time is controlled by using the electric heat tracing heating optimization model. The application can realize efficient utilization of electric energy, play a role in energy saving and emission reduction, and meet the needs of the development of tunnel fire-fighting water-electric heat tracing heating technology in future highland and cold environment.

The application belongs to the technical field of transformer heat dissipation, and discloses a SiC power electronic converter heat dissipation system multi-objective heat optimization method, which can add temperature uniformity as an optimization target to multi-objective optimization design, and form a three-dimensional multi-objective optimization design method together with pressure drop and thermal resistance. The final optimization result is that the Pin-Fin heat dissipation structure (which is different channel width, depth and spacing when applied to microchannels, and other heat dissipation structures can be analogized in this way) with different diameters, lateral spacings and longitudinal spacings along the heat accumulation direction, and such a structure can make the corresponding chip have different junction flow thermal resistances, so as to compensate for the chip temperature non-uniformity caused by fluid heat accumulation. The working efficiency of the heat dissipation system can be effectively improved, and the temperature non-uniformity of the power electronic converter can be effectively reduced.

The application belongs to the technical field of heat supply control application, and particularly discloses a multi-variable heat supply optimization control system for a desuperheater and pressure reducer set based on load prediction technology, which comprises a desuperheating and pressure reducing control module, a desuperheater and a pressure reducer, the desuperheating and pressure reducing control module is connected with the desuperheater and the pressure reducer, the desuperheating and pressure reducing control module is composed of a target load prediction optimization algorithm unit, a data relay unit, an artificial intervention target meeting input unit, a multi-variable fuzzy decoupling controller and a Kalman filter.The application has the beneficial effect that the system can design a multi-variable dynamic decoupling module according to the mutual coupling relationship between temperature and pressure, eliminate the coupling influence between the temperature regulation loop and the pressure regulation loop, and when the system needs to quickly increase the load, give a larger opening degree instruction to the pressure regulating door and the temperature regulating door, so that the system can quickly increase the pressure while maintaining the temperature stable, and when the system flow is close to the flow set value, switch to the steady-state controller for flow control.

The invention relates to the technical field of cooling towers, and discloses a ventilation cooling tower anti-freezing and heat exchange optimization energy-saving method, which comprises the following steps: S1, monitoring multi-region parameters of a cooling tower in real time, including inlet water temperature difference, outlet water temperature difference, air wet bulb temperature and tower wall icing thickness distribution, S2, dynamically dividing an anti-freezing priority region of the cooling tower according to the multi-region parameters, wherein the high-frequency vibration area and the low-temperature air outlet area are automatically marked as a first-level anti-freezing area, S3, an anti-freezing early warning model based on historical icing data is established, and when it is detected that the icing thickness acceleration of any sub-area in the first-level anti-freezing area exceeds a preset threshold value, a gradient response mechanism is triggered. According to the method, the freezing phenomenon is accurately inhibited by monitoring the multi-region parameters of the cooling tower in real time, dynamically dividing the anti-freezing priority regions and combining a gradient response mechanism, differential measures can be taken according to freezing risks of different regions, and the problems of high energy consumption and response lag in a traditional anti-freezing method are effectively avoided.

The invention relates to a carbon dioxide energy storage and heat energy storage synergetic efficient heat exchange method and system.The method comprises the steps that the operation working condition of a carbon dioxide energy storage system is determined, and corresponding target heat exchange requirements are obtained and comprise the carbon dioxide side target outlet temperature, the heat energy storage side target outlet temperature and the target heat exchange power; operating data of the carbon dioxide side and the heat energy storage side are collected, and a heat exchange model used for representing heat exchange amount distribution, end temperature difference distribution and pressure drop distribution is established; determining a model boundary condition according to the working condition and a target heat exchange demand, constraining the heat flow direction to point to the heat energy storage unit under the energy charging working condition, and constraining the heat flow direction to point to the carbon dioxide side under the energy releasing working condition; and irreversible loss evaluation indexes such as entropy production, exergy loss and exergy efficiency are calculated based on the heat exchange model, a heat exchange optimization problem which takes minimization of the evaluation indexes as a target and meets preset constraint conditions is constructed, and the optimal control quantity is solved and issued to an execution mechanism to implement heat exchange control.

The application provides a multilevel weight evaluation method for wellhead clean heating optimization scheme, and belongs to the technical field of oilfield wellhead heating. The technical scheme is as follows: a multilevel weight evaluation method for wellhead clean heating optimization scheme comprises the following steps: establishing a wellhead heating test platform, establishing a multilevel evaluation system, the first layer is a criterion layer including technical benefits, economic benefits and social benefits; the technical benefits include primary energy utilization rate, technical maturity and equipment maintainability; the economic benefits include investment, operation cost and investment recovery period; the social benefits include resource availability, policy support and balanced energy structure; the weights of the three criterion layers are determined by experts; the weights of each sublayer index are determined by using independent weights; the comprehensive scores of all schemes are calculated, and the highest score is the optimal scheme. The application is based on the wellhead heating test platform, simulates field conditions, is accurate in data, and can objectively and accurately evaluate the wellhead clean heating optimization scheme.

The present application belongs to the field of wireless charging system heat dissipation, and particularly relates to a cooling optimization method for a wireless charging system. The present application establishes a two-dimensional thermal network composed of multiple heat transfer paths from the heat source to the environment for the wireless charging system. The traditional thermal resistance model only considers the copper material of the coil and the ferrite material of the magnetic core, and the degree of detail is limited, so it cannot accurately reflect the temperature of the heat generating components. The improved thermal model considers the main factors affecting heat conduction and dissipation such as potting material, thermal interface material and fluid state, thereby producing more accurate results while maintaining relatively low computational complexity, suitable for iterative thermal design and optimization algorithm implementation of the wireless charging system. The present application proposes a multi-objective thermal optimization method and process for a magnetic coupler based on the Pareto front, which considers temperature rise, weight and cost as objective functions, and helps the wireless charging system to achieve higher power density and lighter weight.