58 results about "Thermal model" patented technology

A power supply apparatus (100) comprises an inverter (110), voltage and current measuring devices (120a, 120b), a temperature sensor (130), and an operation circuit (140). The inverter (110) comprises change-over switches (SW1-SW6). The voltage and current measuring devices (120a, 120b) are configured to measure the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6). The temperature sensor (130) is configured to measure an initial temperature (T[0]) in an initial state. The operation circuit (140) is coupled to the voltage and current measuring devices (120a, 120b) and the temperature sensor (130). The operation circuit (140) is configured to: execute a power model (142), and calculate a first transient power of the change-over switches (SW1-SW6) on the basis of the initial temperature (T[0]), the voltage (V1), and the current (I1); and execute a thermal model (144), and calculate a first transient ideal temperature of the change-over switches (SW1-SW6) on basis of the first transient power. The power supply apparatus (100) calculates, in real time, the transient temperature of channel interfaces of the change-over switches (SW1-SW6) by measuring the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6) of the inverter (110). The present invention also relates to a temperature measurement method (500) for a power supply apparatus, and an electrical system (ES1).

A robot control device (10) that controls a robot on which at least one motor (M) is mounted, includes at least one memory (30) that stores a thermal model of an amplifier (50) that supplies a current to the motor (M), and at least one processor (40) that estimates an actual heat generation amount of the amplifier (50) based on a heat generation amount of the amplifier when the current is supplied to the motor calculated using the thermal model, and a base heat amount corresponding to a base temperature that is a temperature of the amplifier (50) immediately before the current is supplied to the motor (M).

This invention relates to the field of battery technology and discloses an equivalent circuit model suitable for flow batteries. The pump loss power is calculated using a pump loss model, and this parameter is output to a thermal model and an electrical characteristic model. The actual operating temperature is calculated using the thermal model and output to the electrical characteristic model. The electrical characteristic model calculates the total resistance of the battery stack and inputs it into the thermal model, thus forming a coupling relationship with the thermal model. The predicted terminal voltage is calculated and input into an operating state estimation module. The maximum discharge capacity and ohmic internal resistance of the battery stack are corrected using an aging model. The corrected maximum discharge capacity and ohmic internal resistance are then input into the operating state estimation module and the electrical characteristic model, respectively. The operating state estimation module estimates the operating state of the flow battery. By integrating electrochemical characteristics, fluid dynamics, aging effects, and thermal effects, the system behavior and operating characteristics of the flow battery are comprehensively described.

The application provides a kind of energy storage battery state simulation and prediction system and method based on digital twinning, aiming at solving the problems of inaccurate state modeling, insufficient perception granularity, uninterpretable prediction and response lag of existing energy storage system.The method uses equivalent thermal model, electrochemical model and aging mechanism model to model the battery, introduces adaptive gating parameter fusion mechanism and data characteristics, realizes cross-scale state mapping and feature reconstruction from cell to system level;Using the electric-thermal-aging coupling relationship to generate baseline trajectory, combined with the data-driven residual correction mechanism to realize multi-time domain closed-loop prediction, identify potential faults and risks in advance through multi-time domain anomaly judgment system;Build a three-dimensional topological model to dynamically display state parameters, generate hierarchical alarm signals and provide operation suggestions.The system constructed by the application has high precision, interpretability, prediction and visualization capabilities, which can significantly improve the intelligent operation and maintenance level of energy storage battery system.

The application discloses a power battery thermal simulation reduced-order modeling method and device. The method comprises the following steps: based on a heat conduction differential equation containing an internal heat source, a three-dimensional temperature field calculation model of an electric core is established; a lumped parameter thermal model of each component of a battery system except the electric core is established, and the components at least comprise heat conduction glue and a cold plate; the three-dimensional temperature field calculation model and the lumped parameter thermal model are coupled for simulation, and a highest temperature time sequence and a lowest temperature time sequence of the electric core are obtained. Through coupling the three-dimensional temperature field calculation model of the electric core based on the heat conduction differential equation and the lumped parameter thermal model of the peripheral components such as the heat conduction glue and the cold plate, the accuracy of the highest and lowest temperature prediction of the power battery is remarkably improved under the premise of ensuring the simulation calculation efficiency and meeting the long-term life simulation demand, and an efficient and reliable technical means is provided for the accurate evaluation of the battery life, the optimization of the thermal management strategy and the safe design of the battery system.

The application provides a steam curing concrete temperature field prediction method based on coupling of CEMHYD3D and Abaqus, first, based on component mix proportion and steam curing temperature boundary, a cement-based micro-hydration model is established in CEMHYD3D to obtain cumulative heat release curve, heat release rate and induction period characteristic parameters; then a segmented hydration heat release model considering the influence of the induction period is constructed, the end time of the induction period and the heat release characteristics are determined, and the internal heat source term changing with time is formed. Then the model is written as Abaqus user subroutine HETVAL, a finite element model of transient temperature field of concrete components under steam curing is established, and transient solution is carried out after setting the initial and boundary conditions. The method solves the characterization defects of the traditional empirical model, and effectively improves the prediction accuracy and reliability of the temperature rise, peak temperature and temperature history in the steam curing stage.

The application discloses a salt mist heat dissipation test analysis method and system based on thermal simulation, and belongs to the technical field of material testing and analysis, which comprises the following steps: applying an alternating thermal load to a test sample in a salt mist test environment, synchronously collecting real-time temperature field distribution and three-dimensional surface morphology data of the test sample, and generating synchronous monitoring data; based on the synchronous monitoring data, extracting dynamic corrosion characteristic parameters, and correcting a thermal simulation model of an initial state of the test sample to generate a corrected thermal model; using the corrected thermal model to simulate heat dissipation performance, obtaining simulation results; comparing and verifying the simulation results with the real-time temperature field distribution to generate a verified thermal model; and based on the verified thermal model, predicting an evolution trend of the heat dissipation performance of the test sample. The application can realize evaluation analysis and evolution trend prediction of the heat dissipation performance of a material under a salt mist corrosion condition by using the coupling effect of alternating thermal load and a salt mist environment, combining dynamic corrosion characteristics with a thermal simulation model.

The application discloses a kind of construction methods of lithium ion battery multiscale multidimensional electrochemistry-force-thermal coupling model, it is related to lithium ion battery coupling model development field, specific steps are as follows: (1) according to the electrochemistry, force and thermal model solution problem determines model scale;(2) based on the model scale determined, select appropriate model dimension to simplify model;(3) select monomer battery, obtain its electrochemistry parameter, thermal physical property parameter and stress related parameter;(4) determine the electrochemistry-force-thermal model coupling mechanism of multiscale multidimension, construct multiscale multidimensional electrochemistry-force-thermal model;(5) based on the electrochemistry-force-thermal model established, can compare lithium ion battery charging and discharging process diffusion stress and thermal stress difference and similarity.The application can systematically clarify the interrelation of battery internal electrochemistry process, stress generation and temperature change, can provide theoretical guidance for battery charging and discharging process thermal design, structure design and optimization.

Temperature monitoring systems and methods in power electronics determine at least one temperature based on the operating characteristics of the power electronics system. These operating characteristics are used to determine power loss using a model of the power electronics system. The power loss is then used to determine the temperature using a thermal model of the power electronics system. The temperature can be used to control the power electronics system, for example, by controlling cooling (such as fan speed), compensating for temperature effects on the power electronics system or its components, or shutting down components or systems if overheating is detected.

The application discloses a billet temperature prediction method and system for a ring heating furnace, and relates to the technical field of billet heating process monitoring. The method comprises the following steps: obtaining initial data and furnace position information of a billet, and establishing a dynamic temperature field model based on a furnace circumference angle distribution; a two-dimensional non-steady-state heat conduction model of the billet in a furnace heating process is established; based on the temperature field distribution of the billet at the current time, the heat transfer of the furnace to the billet is taken as a third type of boundary condition, the two-dimensional non-steady-state heat conduction model is subjected to spatial discretization processing, the alternating direction implicit method is used for time advancing, and the three-diagonal matrix algorithm is used for solving the discrete equation set, so that the temperature field distribution of the billet at the next time is obtained; the obtained temperature field distribution is taken as the temperature field distribution of the new current time, the temperature field distribution at the next time is continuously calculated, and the temperature field distribution of the billet from the furnace entry time to the furnace exit time is obtained. The application can realize accurate calculation of the billet temperature in the furnace heating process.

This application discloses a method, equipment, and medium for coke oven thermal management, comprising: collecting multi-source data from the entire coking process; constructing a coke oven thermal database based on the multi-source data; training a coke oven thermal model based on the coke oven thermal database; constructing an intelligent agent cluster based on the coke oven thermal model, comprising predictive intelligent agents, decision-making intelligent agents, and collaborative intelligent agents, wherein the predictive intelligent agents predict thermal demand, coke quality, energy consumption and emissions, and equipment status; the decision-making intelligent agents make decisions on energy regulation, combustion optimization, furnace temperature control, and production rhythm based on the prediction results; and the collaborative intelligent agents coordinate conflicts and optimize the overall decisions of each intelligent agent to generate the final thermal management command; the thermal management command is sent to the coke oven control system for execution, and each preset indicator is monitored in real time. When any preset indicator deviates from the corresponding threshold, the corresponding intelligent agent is triggered to make dynamic adjustments.

The present application relates to the field of building thermal technology, solves the problem that the existing technology is not accurate, not complete, and poor in environmental adaptability for evaluating the heat storage performance of the envelope structure, and provides an envelope structure heat storage efficiency evaluation method, device, equipment and storage medium, a target test piece containing a functional material is prepared; a cross-characteristic change temperature interval experiment is carried out by using a dynamic thermal and humid climate wind tunnel, nonlinear thermal response data is obtained; a discrete numerical model of enthalpy method is constructed, parameter inversion is carried out with the minimum root mean square error of the theoretical surface heat flow and the measured heat flow as the target, and the thermal physical property parameters and the effective specific heat capacity curve are obtained; a thermal network model is constructed based on the inversion parameters, the hourly heat flow of each node of the test piece is simulated, and the multi-dimensional heat storage efficiency evaluation index of the envelope structure is calculated. The present application couples high-precision wind tunnel experiment, nonlinear heat transfer model and inversion algorithm, accurately quantifies the dynamic heat storage performance of the envelope structure, and provides a precise and practical solution for the heat storage efficiency evaluation of functional envelope structure.

This invention discloses a park-level optimal scheduling method considering the thermal inertia of heating networks and buildings, belonging to the field of park-level optimal scheduling. The method includes: first, establishing an unsteady heat transfer model for the heating network pipelines and dynamic heat transfer equations for the building envelope, quantifying the coupling effect between the dynamic characteristics of the heating network and the thermal inertia of the buildings; second, optimizing and adjusting the gas turbine and gas boiler to quickly respond to fluctuations in wind and solar power output at the minute-level, and smoothing the load curve using the thermal inertia of the heating network pipelines and buildings; finally, setting a temperature elasticity range based on the PMV-PPD model, and dynamically adjusting the heating power to maintain the indoor temperature within a comfortable range. This invention, through the quantification of thermal inertia and coordinated optimization of scheduling, achieves a synergistic improvement in the economy, low carbon footprint, and comfort of the integrated energy system, providing an innovative solution for the optimal scheduling of park-level energy systems.

This invention discloses a method, system, and equipment for simulating drilling circulation temperature based on the drill string eccentricity effect, belonging to the field of petroleum drilling engineering technology. The simulation method includes: acquiring the parameters of the target well; establishing thermal models for various heat source items in the horizontal section of the target well, including drill bit rock breaking heat source item, drill string-wellbore friction heat source item, drill string vibration heat source item, viscous heat dissipation heat source item, and electronic component working heat source item, based on the horizontal section drill string eccentricity effect and thermal model; establishing a wellbore heat balance model under the horizontal section drill string eccentricity effect; and solving the wellbore heat balance model under the horizontal section drill string eccentricity effect. This invention provides fundamental theoretical and applicable methodological support for drilling circulation temperature simulation research considering the horizontal section drill string eccentricity effect and complex heat source items. It is applicable to deep shale gas wells and has high practical value and application prospects.

This application provides a method, apparatus, device, medium, and program product for establishing a battery thermal model, belonging to the field of battery technology. The method for establishing a battery thermal model includes: establishing an initial reduced-order thermal model based on at least one thermodynamic parameter of a battery device, wherein the battery device includes at least one cell, and the initial reduced-order thermal model includes at least one thermal resistance to be identified corresponding to each cell; identifying parameters of the initial reduced-order thermal model based on a target temperature to obtain simulated thermal resistance values ​​corresponding to each of the at least one thermal resistance to be identified; and determining the battery thermal model based on the simulated thermal resistance values ​​corresponding to each of the at least one thermal resistance to be identified and the initial reduced-order thermal model. The battery thermal model is used for thermal simulation of the battery device. This method can reduce computational load and improve simulation efficiency.

This invention proposes a collaborative design method for the electrical-thermal-structural aspects of a high-frequency transformer in a CLLC resonant converter, considering voltage gain. Based on the high-frequency transformer's structural parameters, a mathematical model is established between the transformer's losses and structural parameters. The value of the magnetizing inductance is determined based on the CLLC resonant converter's voltage gain, further narrowing the constraint range. Using transformer losses as the heat source, and combined with the high-frequency transformer's structural parameters, a detailed thermal model of the high-frequency transformer is further established to calculate the temperature of key nodes. Finally, through the constraint relationship between losses, core area product, and temperature rise, the selectable range of transformer structural parameters is determined, and the core selection range is clarified.

Temperature monitoring systems and processes in power electronics determine at least one temperature based on the operating characteristics of the power electronics system. The operating characteristics are used to determine a power loss using a model of the power electronics system. The power loss is then used to determine the temperature using a thermal model of the power electronics system. The temperature can be used to control the power electronics system, for example, by enabling cooling control such as fan speed control, compensating for temperature effects on the power electronics system or its components, or shutting down components or systems when overheating is detected. Figure for the abstract: [Fig 2]

The application discloses a battery thermal management control method and system, based on the established battery thermal model and refrigeration system model, the system state change in the future period is predicted, and the parameter set and temperature set point of the lower controller are dynamically optimized by solving a multi-objective penalty function; the lower control algorithm is executed in a second preset period, the optimized parameter set and temperature set point are used to generate control instructions; the control instructions are output to the cooling execution unit to adjust the battery temperature. The application effectively suppresses the frequent action of the execution mechanism and prolongs the service life of the equipment.

This invention discloses a Bayesian identification and uncertainty quantification method for data center thermal dynamics models, comprising the following steps: S1, establishing a data center thermal dynamics model containing parameters to be estimated; S2, constructing a Bayesian parameter inference model based on real-time measurements; S3, completing parameter estimation, model generation, and uncertainty quantification using a hierarchical adaptive importance sampling algorithm based on the Hammer algorithm. This invention combines physical mechanism modeling with measurement-driven Bayesian inference, utilizing the Hammer algorithm to enhance the global exploration capability of high-dimensional parameter spaces. It effectively addresses the strong nonlinearity and poor prior knowledge issues of data center thermal models without relying on Gaussian assumptions, overcoming the shortcomings of traditional optimization methods that only obtain point estimation results and are highly dependent on initial priors. Simultaneously, it balances modeling accuracy and computational efficiency, enabling high-precision modeling and uncertainty quantification analysis of data center thermal states under single or multiple measurement conditions.

This invention provides a battery thermal management control method based on a fractional-order thermal model and a rolling time-domain chimpanzee algorithm. It introduces fractional-order calculus theory to reconstruct the battery's thermal dynamic equations, capturing the memory characteristics of the thermal system with high fidelity; constructs a rolling time-domain control architecture to achieve proactive prediction and intervention of future thermal states; and replaces the traditional iterative algorithm with an improved chimpanzee optimization algorithm that integrates a lens imaging back-learning mechanism. This invention aims to systematically innovate from three dimensions: mechanism modeling, control architecture, and optimization algorithm, thereby achieving multi-objective synergistic optimization of system energy efficiency, temperature control accuracy, and temperature uniformity while ensuring the safe operation boundary of the battery.

The application discloses an edge computing-based immersion liquid cooling system energy efficiency optimization method and system, relates to the technical field of data-driven control, and comprises the following steps: S1, data acquisition; S2, data processing; S3, edge short-term prediction and thermal approximation modeling; S4, multi-target quantization and constraint construction; S5, mixed control solving and instruction generation; and S6, closed-loop execution and online. The application realizes joint optimization of the cooling side and the IT side under the condition of low delay by coupling short-term load prediction, a physical approximation thermal model and adjustable multi-target optimization in real time at the edge end and taking expert rules as a safety bottom. The mechanism can reduce excessive conservative control actions and frequent switching under the premise of guaranteeing temperature rise and reliability constraints, thereby achieving a better trade-off between energy efficiency optimization and device operation stability, and improving overall operation economy and system life.

This invention discloses a method, system, device, and medium for modeling the electro-magnetic-thermal coupling characteristics of a three-phase integrated high-temperature superconducting cable. The method includes: establishing an electrical model based on the equivalent circuit of parallel multilayer tapes; considering interlayer and interphase electromagnetic coupling in the current distribution model to obtain the current in each tape layer; establishing a critical characteristic and equivalent resistance calculation model using the gold extended model considering magnetic field anisotropy and combining it with power-law relations, and calculating AC losses; establishing a two-dimensional heat transfer model considering interlayer thermal resistance with AC losses as a heat source term, and correcting the circumferential non-uniform convection heat transfer conditions and interphase heat conduction channels through angular weighting functions and shape factors; iterating based on time parameters, feeding the temperature field and equivalent resistance back to the current distribution model to achieve closed-loop updates, and outputting electro-magnetic-thermal coupling simulation results, thereby providing a calculation model that more closely matches the actual operating conditions for the steady-state and fault condition simulation of a three-phase integrated high-temperature superconducting cable.

The present application belongs to the technical field of numerical simulation of microstructure evolution in additive manufacturing process, and provides a method for predicting microstructure morphology of alloy solidification based on a phase field-lattice Boltzmann method multi-scale model.The present application introduces laser parameters and alloy parameters into a flow and heat transfer model of a macroscopic molten pool, extracts parameters of a local position in the macroscopic molten pool that needs to be simulated, substitutes the extracted parameters into a phase field-lattice Boltzmann model, obtains microstructure simulation data packets for visual processing, and obtains the microstructure morphology of alloy solidification.The method of the present application is a multi-scale method, is directed to additive manufacturing, and can more comprehensively establish a connection between process parameters and microstructure.Based on the phase field-lattice Boltzmann model, the influence of flow is considered in the process of microstructure growth, and the result is more accurate.The present application can effectively simulate the mechanism of the effect of the flow field on the dendrite front in the process of dendrite growth, and can simulate how the flow field affects the solute distribution at the dendrite tip.

An arrangement of a supply unit (2) comprising an industrial control system, wherein the supply unit (2) is assigned to a superior computing unit (3), wherein the supply unit (2) comprises at least one electronic component (100), wherein the at least one electronic component (100) has at least one electronic device (108, 109), wherein the supply unit (2) is configured to calculate a first temperature (T1) of the at least one electronic device (108, 109) by means of a first thermal model (M1), and the superior computing unit (3) is configured to calculate a second temperature (T2) of the at least one electronic device (108, 109) by means of a second thermal model (M2), wherein the supply unit (2) and the superior computing unit (3) jointly act such that at least the first temperature (T1) or the second temperature (T2) of the at least one electronic device (108, 109) is calculated.

This invention discloses a smart management system and method for integrated energy storage inverter cabinets, relating to the field of energy storage system control technology. The method includes: real-time monitoring of the operating data of the energy storage inverter system; establishing a historical strategy performance database; predicting the temperature rise trajectory of the filter within a preset time window based on the current filter temperature, ambient temperature, and heat dissipation status using a thermal model during grid-to-off-grid switching; using the temperature rise trajectory as a key constraint; based on the strategy performance under similar operating conditions in the historical strategy performance database; and combining the current dominant operating mode and the power supply priority of key loads, ensuring that the filter temperature does not enter a preset risk range; dynamically calculating and selecting control strategy parameters that achieve a balance between switching smoothness, harmonic suppression level, and strategy execution risk; and executing the control strategy parameters. This invention reduces strategy execution risk by dynamically outputting the globally optimal strategy through multi-dimensional coupling.

The application discloses a battery simulation model construction method, device, equipment and medium, and belongs to the technical field of new energy storage. The method comprises the following steps: obtaining cell parameters, charging and discharging data and production line statistical data of a battery; the battery comprises a plurality of single cells connected in series and in parallel; a three-dimensional thermal model and a physical and chemical model of a single cell are established according to the cell parameters; the dynamics parameters in the physical and chemical model of each single cell are calibrated according to the charging and discharging data by using a genetic algorithm, and a plurality of single cell pseudo two-dimensional models are obtained; a multi-cell coupling model is established according to the plurality of single cell pseudo two-dimensional models and the series-parallel connection topological structure of the battery; the multi-cell coupling model is corrected according to the production line statistical data by using a Monte Carlo simulation method, and a multi-cell electrochemical model of the battery is obtained; and the multi-cell electrochemical model and the three-dimensional thermal model are coupled to obtain a simulation model of the battery. The application can solve the problem of low precision of existing cell simulation.

The application discloses a kind of inversion measurement method, system and medium for the thermal physical parameters of porous medium, belong to material thermal physical parameter measurement technical field, method is: obtaining temperature measurement data;Obtain heat transfer model, wherein, heat transfer model is used to dynamically correct apparent specific heat and target thermal conductivity according to the temperature value of porous medium at current time, to calculate the temperature value of next time, target thermal conductivity is determined according to first model parameter and second model parameter, first model parameter is used to characterize solid heat conduction, and second model parameter is used to characterize pore thermal radiation, heat transfer model is one-dimensional heat transfer model determined according to energy conservation equation in target heat transfer direction;According to temperature measurement data, the first model parameter and the second model parameter in heat transfer model are inverted, to obtain first target parameter and second target parameter, therefore, by implementing the application, it can realize to improve measurement accuracy.

The application discloses a motor temperature control method and device based on a digital twin thermal model and a medium, and relates to the technical field of data processing. The method comprises the following steps: a centralized parameter thermal network model containing three nodes of windings, a stator core and a motor shell is constructed, and real-time collected motor electrical parameters, shell temperatures and wellbore fluid physical property parameters are combined to dynamically update the convective heat transfer boundary conditions and accurately calculate motor losses as heat sources, and then a winding hot spot temperature reflecting an insulation safety limit is reconstructed; on the basis, under the premise of keeping the electromagnetic torque constant, the hot spot temperature is taken as feedback to generate a current vector control instruction to drive a frequency converter to actively adjust the motor operating state. The method effectively solves the model inaccuracy caused by the fixed thermal boundary in the traditional temperature control technology, the extensive control caused by the dependence on the shell temperature, and the passive response defects of the lack of working condition adaptive adjustment capability.

This application discloses an adaptive optimization method and system for thermal coupling parameters of automotive backlight panels, relating to the field of parameter simulation optimization technology. The specific implementation scheme is as follows: A full-envelope operating condition script is compiled; a thermal model and thermal coupling parameter set are imported; thermal simulations are automatically run in batches sequentially using the full-envelope operating condition script; raw datasets for each operating condition segment are collected; risky operating condition segments are screened; thermal coupling parameter perturbation groups are applied to each risky operating condition segment; high-risk operating condition segments are identified; parameter inversion is performed on each high-risk operating condition segment; and the thermal coupling parameter update strategy for each high-risk operating condition segment is determined, along with the optimal thermal coupling parameter version. This invention can improve the prediction accuracy of the thermal model under complex or extreme operating conditions, thereby avoiding problems such as underestimated junction temperature peaks, distorted hotspot locations, and drifting temperature rise rates. This provides a scientific and reliable data basis for the structural design, safety margin setting, and temperature control strategy optimization of automotive backlight panel radiators.

This application discloses an adaptive temperature field control method and system for annealing furnaces used in pipe fitting processing, relating to the field of adaptive control. It constructs a basic thermal model based on first principles and a data-driven adaptive residual model, driven by real-time perceived operating conditions, achieving a deep integration of physical mechanisms and data intelligence. This allows for real-time identification and compensation of dual dynamic disturbances caused by long-term furnace performance drift and short-term batch switching of pipe fittings. Based on this, high-precision and forward-looking prediction of future temperature field dynamics can be achieved. Finally, using a rolling optimization mechanism of model predictive control, the optimal heating power sequence that balances multiple process objectives and physical constraints is solved online. This enables a closed-loop intelligent control system that moves from passive compensation for temperature field changes to forward-looking adaptive tracking of process curves, thereby improving the accuracy and stability of the high-end pipe fitting heat treatment process.